system

Abstract

We provide the system. [Solution] A system that includes means for searching for an appropriate hospital (doctor) based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a hospital, and means for managing each user's medical history and prescription history.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Currently, it takes a lot of time and effort for patients to find a hospital or doctor suitable for their symptoms. Also, it is difficult for patients to manage their own medical records and prescription histories.

Means for Solving the Problems

[0005] The present invention provides means for searching for an appropriate hospital (doctor) based on the affected part or symptoms specified by a user, displaying the result, reducing the time required for searching for a hospital, and managing the medical records and prescription histories for each user. Thereby, patients can efficiently find a hospital or doctor suitable for their symptoms and can easily manage their own medical records and prescription histories.

Brief Description of the Drawings

[0006] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 1 of Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of Embodiment 2. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2. [Figure 15] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 3 of Example 3. [Figure 16]It is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3. [Figure 17] It is a sequence diagram showing the processing flow of the data processing system in Example 1 of Form Example 1 when combined with an emotion engine. [Figure 18] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] It is a sequence diagram showing the processing flow of the data processing system in Example 2 of Form Example 2 when combined with an emotion engine. [Figure 20] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] It is a sequence diagram showing the processing flow of the data processing system in Example 3 of Form Example 3 when combined with an emotion engine. [Figure 22] It is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. [Figure 23] It is a sequence diagram showing the processing flow of the data processing system in other embodiments.

Embodiments for Carrying Out the Invention

[0007] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0008] First, the language used in the following description will be explained.

[0009] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (TENSOR PROCESSING UNIT (registered trademark)), etc.

[0010] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0011] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0012] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0014] [First Embodiment]

[0015] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0016] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0019] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0022] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0026] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0027] "Example of form 1"

[0028] The system of the present invention has a function to search for an appropriate hospital (doctor) based on the affected area and symptoms specified by the user. Specifically, when the user enters their affected area and symptoms on the interface, the system searches the database for information on hospitals and doctors and displays the results to the user. This function allows the user to efficiently find a hospital or doctor suitable for their symptoms.

[0029] "Example of form 2"

[0030] Furthermore, the system of the present invention has a function to manage each user's medical history and prescription history. Specifically, the system stores information such as hospitals and doctors the user has visited in the past, diagnoses, and prescribed medications in a database, allowing the user to refer to this information at any time. This function allows users to easily manage their own medical history and prescription history.

[0031] "Example of form 3"

[0032] For example, if a user specifies "headache" as the affected area, the system searches its database for hospital and doctor information and displays headache specialists and hospitals that can treat headaches to the user. It also saves information such as hospitals and doctors the user has visited for headaches in the past, diagnoses, and prescribed medications, allowing the user to access this information at any time.

[0033] The following describes the processing flow for each example of the form.

[0034] "Example of form 1"

[0035] Step 1: The user enters their affected area and symptoms on the system interface. Step 2: The system searches its database for hospital and doctor information and extracts hospitals and doctors suitable for the affected area and symptoms entered by the user.

[0036] Step 3: The system displays the extracted hospital and doctor information to the user.

[0037] "Example of form 2"

[0038] Step 1: The user enters their medical history and prescription history into the system.

[0039] Step 2: The system saves the medical history and prescription history entered by the user to the database.

[0040] Step 3: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[0041] "Example of form 3"

[0042] Step 1: The user enters "headache" as the affected area into the system.

[0043] Step 2: The system searches the database for hospital and doctor information and extracts headache specialists and hospitals that can treat headaches.

[0044] Step 3: The system displays the extracted hospital and doctor information to the user.

[0045] Step 4: The user enters information into the system, such as the hospitals and doctors they have visited in the past for headaches, their diagnoses, and the medications they have been prescribed.

[0046] Step 5: The system saves the information entered by the user to the database.

[0047] Step 6: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[0048] (Example 1)

[0049] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0050] There is a challenge in that it is difficult for users to quickly and accurately find the appropriate medical institution based on their body part and symptoms. Furthermore, there is a need to efficiently manage and update each user's health information as needed.

[0051] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0052] In this invention, the server includes means for searching for an appropriate medical institution based on the body part or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. As a result, users can quickly find an appropriate medical institution and manage and update their health information efficiently.

[0053] A "user" refers to an individual who uses the system to search for appropriate medical institutions based on their own body parts and symptoms.

[0054] "Body parts and symptoms" refers to information related to a user's health condition that they enter when searching for a medical institution.

[0055] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[0056] "Searching" refers to the process of examining information within a database based on conditions specified by the user and finding appropriate results.

[0057] "Display" refers to outputting search results to the device in a format that is easy for the user to understand.

[0058] "Health information" refers to data related to a user's health status, such as their medical history and prescription history.

[0059] "Management" refers to the process of organizing health information and updating or correcting it as needed.

[0060] A "server" refers to a computer system that receives input from users, searches a database, and returns the results.

[0061] A "terminal" refers to a device that a user uses to access a system through an interface.

[0062] As an embodiment of this invention, the following system is constructed.

[0063] The server generates a program that searches for appropriate medical institutions based on the body parts and symptoms specified by the user. This program consists of multiple components, including a user interface, database access, and a search algorithm. Specifically, the server implements the search algorithm using Python and manages medical institution information using a MySQL® database.

[0064] The user uses the terminal's interface to input information about their body parts and symptoms. The terminal sends this input to the server. The server searches its database for information on medical institutions based on the received information. The search results are returned to the terminal and displayed to the user.

[0065] For example, if a user enters "stomach ache," the server searches its database for medical institutions specializing in "gastroenterology." The search results might display "local gastroenterology clinics" or "gastrointestinal hospitals in the city."

[0066] An example of a prompt to input into the generating AI model might be: "Create a program that searches for appropriate medical institutions based on the symptoms entered by the user. Use MySQL as the database and implement the search algorithm in Python."

[0067] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0068] Step 1:

[0069] The user accesses the device's interface and enters information about their body parts and symptoms. This entered data is saved on the device in text format. This data serves as foundational information for identifying the user's health problems.

[0070] Step 2:

[0071] The terminal sends the information entered by the user to the server as an HTTP request. This request contains data about the user's symptoms. The server receives this request and prepares to look up the database.

[0072] Step 3:

[0073] The server parses the received user information and queries a MySQL database. The database contains information such as the medical institution's specialty, location, and operating hours. The server uses a search algorithm implemented in Python to identify the medical institution best suited to the user's symptoms. The input is the user's symptom data, and the output is a list of appropriate medical institutions.

[0074] Step 4:

[0075] The server returns the search results to the terminal in JSON format. This result includes the name, address, and contact information of the medical institution. The server then processes the data to convert it into a format that is easy for the user to understand.

[0076] Step 5:

[0077] The device displays the received search results in a user-friendly format. Users can view detailed information about medical institutions on the screen and contact them as needed. The displayed information helps users make quick decisions when selecting a medical institution.

[0078] (Application Example 1)

[0079] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0080] In modern society, it is crucial for users to quickly and accurately find medical institutions that are appropriate for their symptoms. However, traditional methods present challenges, such as time-consuming information searches and difficulty for users to select the right medical institution. Furthermore, the lack of efficient means to manage and update users' health information as needed can lead to a decline in the quality of medical services.

[0081] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0082] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. This enables users to quickly find an appropriate medical institution and allows for efficient management and updating of health information.

[0083] A "user" is an individual who uses the system to search for medical institutions based on their own symptoms.

[0084] "Affected area or symptoms" refers to the physical ailments or medical conditions that users enter when searching for medical institutions.

[0085] A "medical institution" refers to a facility that provides medical services, such as a hospital or clinic.

[0086] "Searching" is the act of finding appropriate information from a database based on conditions specified by the user.

[0087] "Health information" refers to a user's medical history, prescription history, and other personal information related to medical care.

[0088] A "smart device" refers to a portable electronic device with internet connectivity, such as a smartphone or tablet.

[0089] "Real-time" refers to information being processed and provided to the user immediately.

[0090] "Expert advice" refers to advice provided to users by professionals with medical knowledge.

[0091] The invention will now be described in terms of embodiments for carrying out the invention. This invention is a system in which a user inputs their symptoms using a smart device and searches for an appropriate medical institution. The system consists of a server, a user terminal, and a database.

[0092] The server searches for medical institution information in its database based on the affected area and symptoms specified by the user, and displays the results on the user's terminal. The server is built using Python and Flask, and uses SQLite for its database. The server receives user input and generates search results in real time.

[0093] The user terminal is a smart device such as a smartphone or tablet, and provides an interface for the user to input symptoms. The user terminal displays the search results received from the server and provides the information in a format that the user can easily understand.

[0094] For example, when a user enters "headache," the server searches the database and suggests nearby neurology clinics. This allows the user to quickly find an appropriate medical facility.

[0095] By using generative AI models, it is also possible to provide expert advice based on the user's symptoms. An example of a prompt message would be: "Based on the symptoms entered by the user, please suggest the most suitable medical institution. Example: For headaches, suggest a neurology hospital."

[0096] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0097] Step 1:

[0098] The user launches the application on their smart device and accesses the symptom input screen. The user enters their affected area and symptoms in text format. The entered data is sent from the user's device to the server.

[0099] Step 2:

[0100] The server analyzes the symptom data received from the user. This analysis uses natural language processing techniques to extract keywords from the input text. Based on the extracted keywords, the server searches for medical institution information in the database.

[0101] Step 3:

[0102] The server generates the results of a database search. The search results include a list of medical institutions suitable for the user's symptoms. The server sends the search results to the user's terminal.

[0103] Step 4:

[0104] The user terminal displays the search results received from the server. The display is in a format that is easy for the user to understand. The user can select the appropriate medical institution from the displayed list.

[0105] Step 5:

[0106] The server uses a generative AI model to generate expert advice based on the user's symptoms. Symptom data is input into the AI ​​model using prompts to obtain appropriate advice. The resulting advice is then sent to the user's terminal.

[0107] Step 6:

[0108] The user terminal displays expert advice received from the server. Users can use this advice to decide on a healthcare provider and their next course of action.

[0109] (Example 2)

[0110] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0111] In modern healthcare, it is crucial for users to efficiently manage their health information and quickly find appropriate medical facilities. However, traditional systems have problems such as users not being able to easily access past health information and the time it takes to search for medical facilities. Furthermore, there were challenges in ensuring the security of health information and obtaining appropriate advice based on that information.

[0112] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0113] In this invention, the server includes means for searching for an appropriate medical institution based on symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing each user's health information. This enables users to efficiently manage their own health information and quickly search for an appropriate medical institution.

[0114] A "user" refers to an individual who uses the system to manage their own health information and search for medical institutions.

[0115] "Symptoms" refers to changes in health conditions or physical state that users specify when searching for medical institutions.

[0116] "Medical institutions" refer to facilities such as hospitals and clinics where users can receive medical treatment.

[0117] "Search results" refer to information about medical institutions provided by the system based on the conditions specified by the user.

[0118] "Health information" refers to medical-related data such as a user's medical history, prescription history, and diagnosis results.

[0119] A "database" refers to an information management system used to store and manage users' health information.

[0120] "Encryption" refers to a technology that transforms data to protect users' health information and prevent third parties from easily accessing it.

[0121] A "generative AI model" refers to artificial intelligence technology that provides advice and predictions based on a user's health information.

[0122] "Advice" refers to suggestions and recommendations provided by the generative AI model based on the user's health information.

[0123] This system enables users to efficiently manage their health information and quickly find appropriate medical facilities. The following describes embodiments for carrying out the invention.

[0124] The server stores user-entered health information in a database. The database uses a relational database management system such as MySQL. When users enter their past medical history and prescription history via a dedicated terminal or web application, the server receives this information and stores it in the database. The stored data is encrypted using the AES encryption algorithm to ensure security.

[0125] Users can search for and retrieve their own health information from their devices. The server queries the database based on the user's search criteria and retrieves the relevant information. The retrieved data is displayed on the user's device through an interface using React.js. This allows users to intuitively check the information.

[0126] Furthermore, by utilizing generative AI models, it is possible to provide advice based on the user's health information. Users can receive advice from the AI ​​model by entering prompts. For example, by entering a prompt such as, "Generate important information to tell my doctor at my next appointment," the AI ​​model will analyze the user's health information and generate appropriate advice.

[0127] This system allows users to centrally manage their health information and use it to their advantage when receiving medical treatment at a healthcare facility.

[0128] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0129] Step 1:

[0130] Users enter their past medical and prescription history using a dedicated terminal or web application. This information includes hospital names, doctor names, diagnoses, and the names and dosages of prescribed medications. This information is then transmitted to the server via a form.

[0131] Step 2:

[0132] The server receives health information submitted by users and stores it in a database. MySQL is used for the database, managing each user's information as a separate record. During storage, the data is encrypted using the AES encryption algorithm to ensure security. The input is the user's health information, and the output is the encrypted database record.

[0133] Step 3:

[0134] If a user wants to check their past medical history or prescription history, they enter search criteria on their device. For example, they can specify specific conditions such as "diagnosis results from March 2023."

[0135] Step 4:

[0136] The server queries the database based on the user's search criteria and retrieves the relevant information. The retrieved data is displayed on the user's device through an interface using React.js. The input is the user's search criteria, and the output is health information as search results.

[0137] Step 5:

[0138] Users can receive advice based on their past medical history data using a generative AI model. Users input prompts and receive advice from the AI ​​model. For example, a user might input a prompt such as, "Generate important information I should tell my doctor at my next appointment." The server uses the AI ​​model to analyze the user's health information and generate appropriate advice. The input consists of prompts and health information, while the output is the advice from the AI ​​model.

[0139] (Application Example 2)

[0140] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0141] In modern healthcare systems, users are required to efficiently manage their health information and easily understand how to choose healthcare providers, pay medical expenses, and access insurance coverage. However, traditional systems have the problem that this information is scattered, making it difficult for users to quickly obtain the information they need.

[0142] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0143] This invention includes a server that provides means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, means for managing each user's health information, means for managing the payment history and insurance coverage status of medical expenses based on the user's health information, and means for allowing the user to check past medical expense payments and insurance coverage status. As a result, users can centrally manage their own health information and efficiently select medical institutions and manage their medical expenses.

[0144] A "user" is an individual who uses the system to manage their own health information, select medical institutions, and manage their medical expenses.

[0145] "Health information" refers to data that includes information such as the user's medical history, prescription history, diagnosis results, medical expense payment history, and insurance coverage status.

[0146] A "medical institution" refers to facilities such as hospitals and clinics that are searched based on the affected area or symptoms specified by the user.

[0147] "Medical expenses" refer to the costs that users pay for medical consultations and treatments at medical institutions.

[0148] "Insurance coverage status" refers to information indicating the extent to which the user's insurance covers medical expenses.

[0149] "Search functionality" refers to a feature that finds appropriate medical institutions based on conditions specified by the user and displays the results.

[0150] "Management means" refers to a function that stores users' health information in a database and allows for updates and retrieval as needed.

[0151] As an embodiment of this invention, a system is provided that manages users' health information and efficiently manages the selection of medical institutions and medical expenses. The system consists of an application installed on a terminal such as a smartphone and a server that operates on the cloud.

[0152] The server searches for appropriate medical institutions based on the affected area and symptoms specified by the user and displays the results on the terminal. A database management system (e.g., MySQL) is used for the search to quickly retrieve information on medical institutions. Furthermore, the server manages the user's medical expense payment history and insurance coverage status based on the user's health information. This involves retrieving the user's past medical data and insurance information from the database and performing calculations.

[0153] The device will allow users to check their past medical payment history and insurance coverage through the application. A front-end framework (e.g., React Native) will be used to build the user interface and display the information in a visually clear and easy-to-understand manner.

[0154] For example, when a user opens the app and enters "Show me my medical expense payment history for the past 3 months," the server retrieves the relevant information from the database and displays it on the device. An example of a prompt that uses a generative AI model to analyze user input and provide appropriate information is, "Retrieve the user's medical expense payment history for the past 3 months and display it, including insurance coverage status."

[0155] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0156] Step 1:

[0157] The user launches the application using their device and provides input to retrieve specific information. For example, they might enter a prompt such as, "Show me my medical expense payment history for the past three months." The entered prompt is then analyzed by a generative AI model to identify the type of information needed.

[0158] Step 2:

[0159] The terminal sends a request to the server based on the parsed prompt. The request includes the user ID and the type of information requested (e.g., medical expense payment history). The server parses the received request and uses a database management system (e.g., MySQL) to search for the relevant information in the user's health information database.

[0160] Step 3:

[0161] The server calculates medical expense payment history and insurance coverage status based on information retrieved from the database. Past medical data and insurance information are used for the calculations. The calculation results are formatted in a user-friendly format.

[0162] Step 4:

[0163] The server sends the formatted information to the terminal. The terminal then uses a frontend framework (e.g., React Native) to visually display the received information on the user interface. The user can review the displayed information and decide on the next action as needed.

[0164] (Example 3)

[0165] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0166] In the modern healthcare system, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, it is difficult to manage and easily access past diagnoses and prescription histories when needed. This can lead to users missing opportunities to receive appropriate medical care.

[0167] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0168] This invention includes a server that searches for and displays appropriate medical institutions based on body parts and symptoms specified by the user, means for reducing the time required to search for medical institutions, and means for managing each user's health history and medication history. As a result, users can quickly find appropriate medical institutions and easily manage and refer to past diagnosis results and prescription history.

[0169] A "user" is an individual who uses the system to search for medical institutions based on their own health status and symptoms, and manages that information.

[0170] "Body part" refers to a specific area of ​​the body where the user experiences symptoms, and is information used as a basis for searching for medical institutions.

[0171] "Symptoms" refer to physical or mental abnormalities or discomforts experienced by the user, and serve as the basis for information used when searching for medical institutions.

[0172] A "medical institution" refers to facilities such as hospitals and clinics that provide medical care to address the user's symptoms.

[0173] "Searching" is the process of finding appropriate medical institutions from a database based on the conditions specified by the user.

[0174] "Health history" refers to information about a user's past diagnoses and treatments, and is data that users use to manage their own health status.

[0175] "Medication history" refers to information about medications a user has been prescribed in the past, and is data that users use to manage their own drug therapy.

[0176] "Management" refers to the process of saving a user's health history and medication history, and making it possible to update and refer to it as needed.

[0177] One embodiment of this invention is to provide a system that allows users to quickly find appropriate medical facilities based on their symptoms and to manage their past health and medication history.

[0178] The server receives information about body parts and symptoms entered by the user through their terminal and searches its database. This database contains information such as the specialty and location of medical institutions, and searches are performed using a database management system such as SQL. The server sends the search results to the user's terminal and displays them in a format that the user can easily understand.

[0179] Users can input information about past diagnoses and prescribed medications through their devices. The server stores this information in a database, making it accessible to users when needed. This allows users to manage their health and stay informed about the information necessary to receive appropriate medical care.

[0180] For example, if a user enters "headache" as a symptom, the server will display information such as "headache specialist clinics" and "neurology hospitals." It will also save information about past visits to "headache specialist clinics," diagnoses of "migraines," and prescriptions for "ibuprofen," allowing the user to refer to this information.

[0181] By utilizing generative AI models, systems can be designed and improved. An example of a prompt message is, "Design a system that searches for information on specialists and hospitals corresponding to the affected area specified by the user, and allows the user to save and refer to past diagnostic results and prescribed medications." The flow of specific processing in Example 3 will be explained using Figure 15.

[0182] Step 1:

[0183] The user inputs symptoms and body parts through the terminal's interface. The entered information is sent from the terminal to the server. For example, if the user inputs "headache," the terminal sends this information to the server in real time.

[0184] Step 2:

[0185] The server searches the database based on the received symptom information. The input is information about "headaches," and the server uses an SQL query to extract information about relevant medical institutions from the database. The output is a list of medical institutions that can treat headaches. Specifically, the server searches for information on "headache specialist clinics" and "neurology hospitals."

[0186] Step 3:

[0187] The server sends the search results to the user's device. The device displays the received information to the user. Specifically, the device displays a list of "headache specialist clinics" and "neurology hospitals" on the screen, allowing the user to select one.

[0188] Step 4:

[0189] The user enters information about past diagnoses and prescribed medications into the terminal. The entered information is sent from the terminal to the server and stored in the database. Specifically, if the user enters information that they were diagnosed with "migraine" and prescribed "ibuprofen," the server saves this information to the database.

[0190] Step 5:

[0191] Users can access their saved health and medication history. The device retrieves information from the server upon user request and displays it on the screen. Specifically, when a user wants to review past diagnostic results, the device retrieves information from the server and displays a history of being diagnosed with "migraine."

[0192] (Application Example 3)

[0193] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0194] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, the procedures for paying medical expenses after consultations and managing past medical history are also cumbersome. There is a need to solve these problems and provide convenient healthcare services for users.

[0195] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0196] In this invention, the server includes means for searching for an appropriate medical institution based on a body part or symptom specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing each user's medical history and prescription history; means for performing electronic payment after the consultation; and means for generating prompt messages to search for relevant medical institutions using a generative AI model. This makes it possible for users to quickly find an appropriate medical institution, easily make payments after the consultation, and easily manage their past medical history.

[0197] A "user" is an individual who uses the system to search for medical institutions and manage their medical history.

[0198] "Body parts and symptoms" refers to information about a user's health condition that they specify when searching for a medical institution.

[0199] "Medical institutions" refer to hospitals and clinics that can treat the user's symptoms.

[0200] "Search methods" refer to functions that allow users to find appropriate medical institutions based on the information they specify.

[0201] "Display means" refers to functions that provide search results to users visually.

[0202] "Time-saving measures" refer to features that streamline the search process for medical institutions, thereby reducing the time it takes for users to obtain results.

[0203] "Medical history / prescription history" refers to records of medical treatments and medications prescribed to the user in the past.

[0204] "Management means" refers to a function for saving and updating a user's medical history and prescription history as needed.

[0205] "Electronic payment methods" refer to functions that allow users to pay medical expenses online after a medical consultation.

[0206] A "generative AI model" is a technology that uses artificial intelligence to generate prompt messages based on user input and search for appropriate medical institutions.

[0207] A "prompt sentence" is an instruction sentence used by a generative AI model when searching for medical institutions.

[0208] The system for implementing this invention allows users to search for medical institutions and manage their medical history using terminals such as smartphones and computers. The system exchanges data between a server and the user terminal and provides appropriate information according to the user's requests.

[0209] The server generates prompt messages using a generative AI model based on the body parts and symptoms specified by the user, searching for relevant medical institutions. Based on these prompt messages, it retrieves information on appropriate medical institutions from the database and displays it on the user's terminal. This allows the user to quickly find the appropriate medical institution.

[0210] The server also provides functionality for electronic payment after consultations. Users can pay for their medical services online, and the payment information is stored on the server. Furthermore, the server manages the user's medical history and prescription history, allowing users to view and update this information.

[0211] For example, when a user enters "headache," the server generates a prompt message saying, "The user is complaining of a headache. Please list medical institutions that can treat headaches." Based on this prompt message, the AI ​​model searches for appropriate medical institutions and displays the results on the user's terminal. The user can then select a medical institution from the displayed list and make an appointment. After the consultation, the user pays the medical fees using the electronic payment function, and the history is automatically updated.

[0212] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0213] Step 1:

[0214] The user uses a device to input information about body parts and symptoms. The entered information is then sent from the device to the server.

[0215] Step 2:

[0216] The server uses a generative AI model to generate a prompt message based on the user's input information received. Specifically, it creates a prompt message in the format of, "The user is reporting symptoms. Please list medical institutions that can treat these symptoms." This prompt message is then sent to the generative AI model.

[0217] Step 3:

[0218] The generative AI model analyzes the prompt text and searches the database for information on appropriate medical institutions. The search results are returned to the server.

[0219] Step 4:

[0220] The server sends the medical institution information received from the generated AI model to the user's terminal. The user's terminal visually displays the received information to the user. The user can then select a medical institution from the displayed list and make an appointment.

[0221] Step 5:

[0222] After the consultation, the user makes an electronic payment using a terminal. The terminal sends the payment information to the server. The server processes the payment information and completes the user's payment.

[0223] Step 6:

[0224] The server updates the user's medical history and prescription history. The updated information is stored in a database for the user to review later. The user can review and update their history as needed.

[0225] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0226] "Example of form 1"

[0227] One embodiment of the present invention involves a system that combines a user's emotions with an emotion engine. This system searches for an appropriate hospital (doctor) based on the affected area or symptoms specified by the user and displays the results. Furthermore, the emotion engine recognizes the user's emotions and adjusts the search results for hospitals (doctors) based on those emotions. For example, if the user is feeling anxious, the emotion engine uses that information to prioritize displaying hospitals (doctors) that can provide the user with a sense of security.

[0228] "Example of form 2"

[0229] Another embodiment of the present invention is a system that adjusts the display method of medical history and prescription history based on the user's emotions. This system manages the medical history and prescription history for each user, allowing users to check their own medical history and prescription history and update it as needed. Furthermore, the emotion engine recognizes the user's emotions and adjusts the display method of the medical history and prescription history based on those emotions. For example, if the user is confused, the emotion engine uses that information to display the medical history and prescription history in a simpler and easier-to-understand format.

[0230] "Example of form 3"

[0231] Another embodiment of the present invention is a system that adjusts the display method of medical history and prescription history based on the user's emotions. This system manages the medical history and prescription history for each user, allowing users to check their own medical history and prescription history and update it as needed. Furthermore, the emotion engine recognizes the user's emotions and adjusts the display method of the medical history and prescription history based on those emotions. For example, if the user is confused, the emotion engine uses that information to display the medical history and prescription history in a simpler and easier-to-understand format.

[0232] The following describes the processing flow for each example of the form.

[0233] "Example of form 1"

[0234] Step 1: The user accesses the system and enters their symptoms and affected areas.

[0235] Step 2: The system searches for a suitable hospital (doctor) based on the entered information.

[0236] Step 3: Simultaneously, the emotion engine recognizes the user's emotions.

[0237] Step 4: The emotion engine adjusts search results based on the emotions it recognizes, prioritizing hospitals (doctors) that can provide the user with a sense of security.

[0238] "Example of form 2"

[0239] Step 1: The user accesses the system and checks their medical and prescription history.

[0240] Step 2: The emotion engine recognizes the user's emotions.

[0241] Step 3: Based on the emotions it recognizes, the emotion engine adjusts how the medical history and prescription history are displayed, presenting them in a simpler and easier-to-understand format if the user is confused.

[0242] (Example 1)

[0243] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0244] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, the inability to select a medical institution that takes the user's emotional state into consideration means that user anxiety cannot be alleviated. Additionally, there is a need to effectively manage and update users' health information as needed.

[0245] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0246] In this invention, the server includes means for searching for appropriate medical institutions based on body parts or symptoms specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the search results based on those emotions; and means for managing each user's health information. As a result, users can quickly find medical institutions suitable for their symptoms, make choices that take their emotions into consideration, and easily manage and update their health information.

[0247] A "user" is an individual who uses the system to input information about their health condition and search for appropriate medical institutions.

[0248] "Body parts and symptoms" refers to specific information about one's own health status that the user inputs into the system.

[0249] A "medical institution" refers to a facility or specialist that provides medical care and treatment tailored to the user's health condition.

[0250] "Search results" refer to a list of appropriate medical institutions presented by the system based on the information entered by the user.

[0251] "Analyzing emotions" is the process of evaluating a user's emotional state based on their input information and past data.

[0252] "Health information" refers to personal information about a user's health, such as their medical history and prescription history.

[0253] "Managing" refers to the process of organizing users' health information and updating or verifying it as needed.

[0254] As an embodiment of this invention, the following system is constructed.

[0255] The server runs a program that searches for appropriate medical facilities based on the body parts and symptoms specified by the user. This program includes a user interface, a database search function, and a sentiment analysis engine. The user interface is implemented as a web browser or mobile application. When the user enters symptoms into the interface, the device sends that information to the server.

[0256] The server searches the database based on the information it receives. This database contains information about medical institutions, and a relational database management system such as MySQL or PostgreSQL is used. The server uses SQL queries to search for medical institutions that are suitable for the user's symptoms.

[0257] Furthermore, the server uses a sentiment analysis engine to recognize the user's emotions. This sentiment analysis engine analyzes the user's emotions using natural language processing techniques. Specifically, it might use Python libraries such as NLTK or Transformers. Once the sentiment engine recognizes the user's emotions, the server adjusts the search results based on those emotions.

[0258] As a concrete example, consider a case where a user enters "headache" and "anxiety." The server searches its database for medical institutions specializing in headaches and then uses an emotion engine to prioritize displaying medical institutions that can alleviate the user's anxiety.

[0259] An example of a prompt message to input into a generative AI model might be, "The user entered a headache and is feeling anxious. Please search for an appropriate medical institution." Based on this prompt message, the generative AI model will generate appropriate search results.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0261] Step 1:

[0262] The user enters information about their body parts and symptoms into the interface. The entered information is sent to the terminal in text format. Specifically, when the user enters "I have a headache," the terminal prepares to send this information to the server.

[0263] Step 2:

[0264] The terminal sends the information entered by the user to the server as an HTTP request. The input data is packaged in JSON format and sent to the server. This allows the server to receive the user's symptom information.

[0265] Step 3:

[0266] The server searches the database based on the received symptom information. Specifically, it generates an SQL query to search for medical institution information within the database. The input is the user's symptom information, and the output is a list of relevant medical institutions.

[0267] Step 4:

[0268] The server analyzes the user's emotions using an emotion analysis engine. The input consists of the user's symptom information and past history, and the emotions are evaluated using natural language processing techniques. The output is the user's emotional state.

[0269] Step 5:

[0270] The server adjusts search results based on the results of sentiment analysis. The input is a list of medical institutions and the user's emotional state, and the output is a list of adjusted medical institutions. Specifically, if the user is feeling anxious, the server prioritizes selecting medical institutions that can provide a sense of security.

[0271] Step 6:

[0272] The server sends the adjusted search results to the terminal. The output is a list of adjusted medical institutions, and the terminal receives this information.

[0273] Step 7:

[0274] The terminal displays search results received from the server to the user. The user can review the displayed information on medical institutions and select an appropriate one. Specifically, by selecting a "relaxing hospital," the user can receive medical services with peace of mind.

[0275] (Application Example 1)

[0276] Next, Application Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0277] In the modern medical environment, it is difficult for users to quickly and accurately find a medical institution suitable for their symptoms. In addition, since there is a lack of services that consider users' feelings in the selection of medical institutions and integrate medical examination reservations and electronic payments, it is required to reduce users' anxiety and improve convenience.

[0278] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0279] In this invention, the server includes means for searching for an appropriate medical institution based on the affected part or symptoms specified by the user and displaying the result, means for recognizing the user's emotion and adjusting the search result of the medical institution based on the emotion, and means for providing an integrated service of medical examination reservation and electronic payment. As a result, the user can quickly find a medical institution suitable for their symptoms, make a reassuring choice according to their emotion, and can consistently perform from medical examination reservation to payment.

[0280] A "user" is an individual who uses the system to search for a medical institution suitable for their symptoms and make a medical examination reservation and electronic payment.

[0281] The "affected part or symptoms" refer to the physical discomfort or medical condition specified by the user when searching for a medical institution.

[0282] A "medical institution" is a facility such as a hospital or clinic that provides appropriate medical treatment for the user's symptoms.

[0283] "Search results" refer to a list of medical institutions presented by the system based on the conditions specified by the user.

[0284] "Means of recognizing emotions" refers to technology that analyzes the user's emotional state and adjusts the search results for medical institutions based on that information.

[0285] "Appointment booking" is the process of booking an appointment in advance at a medical institution of the user's choice.

[0286] "Electronic payment" refers to a method of paying for medical consultations and treatments online.

[0287] A description of the embodiment for carrying out the invention will be provided.

[0288] The system that realizes this invention mainly consists of a server and a user terminal. The server searches for an appropriate medical institution based on the affected area and symptoms specified by the user and displays the results on the user terminal. The user terminal is a mobile information terminal such as a smartphone or tablet and provides an interface for the user to input symptoms.

[0289] The server analyzes the user's emotions using an emotion recognition API (e.g., Microsoft® Azure®'s Emotion API). When the user enters symptoms, the server recognizes the user's emotions through this API and adjusts the search results for medical institutions based on those emotions. For example, if the user is feeling anxious, the server will prioritize displaying medical institutions that can provide a sense of security.

[0290] Furthermore, the server provides a service that integrates appointment scheduling and electronic payment. Users can book appointments at their chosen medical institutions and pay for consultations and treatments online. This process improves user convenience and reduces anxiety.

[0291] For example, if a user enters "headache" and is feeling anxious, the server uses an emotion recognition API to analyze that emotion and prioritizes displaying medical facilities that provide a relaxing environment. An example of a prompt to input into the generative AI model would be, "If the user is feeling anxious, what kind of medical facilities should be prioritized?"

[0292] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0293] Step 1:

[0294] The user uses a terminal to input information about their affected area and symptoms on the interface. The entered data is sent to the server. The input data is text information about the user's symptoms.

[0295] Step 2:

[0296] The server searches a database of medical institutions based on the received symptom data. Using a search algorithm, it generates a list of medical institutions suitable for the symptoms. The output is a list of medical institutions as search results.

[0297] Step 3:

[0298] The server analyzes the user's emotions using an emotion recognition API. It estimates the emotional state using user input data and image data acquired from the device's camera. The output is data indicating the user's emotional state.

[0299] Step 4:

[0300] The server adjusts the search results for healthcare facilities based on emotional state data. For example, if an emotional state indicating anxiety is detected, healthcare facilities that can provide a sense of security will be prioritized and placed higher in the list. The output is a list of the adjusted healthcare facilities.

[0301] Step 5:

[0302] The server sends the adjusted list of medical institutions to the user terminal. The user checks the list on the terminal and selects the desired medical institution. The information of the selected medical institution is displayed to the user.

[0303] Step 6:

[0304] After the user selects the desired medical institution, a medical examination reservation is made using the terminal. The server sends the reservation information to the medical institution to confirm the reservation. The output is the reservation confirmation information.

[0305] Step 7:

[0306] The user makes an electronic payment using the terminal. The server processes the payment through the payment system and notifies the user of the completion of the payment. The output is the confirmation information of the completion of the payment.

[0307] (Example 2)

[0308] Next, Example 2 of Embodiment 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0309] In modern medical information management systems, it is important for users to efficiently manage their own health information and quickly search for necessary medical institutions. However, in conventional systems, the display of information according to the user's emotions is not considered, and it may be difficult to understand the information. In addition, since the input and update of information are complicated, there is a problem that it is difficult for users to appropriately manage their own health information.

[0310] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0311] In this invention, the server includes means for searching for appropriate medical institutions based on body parts or symptoms specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the display format of health information based on those emotions; and means for the user to input health information and transmit it to the server. This allows the user to efficiently manage their own health information, and the display of information according to their emotions makes it easier to understand the information.

[0312] A "user" refers to an individual who uses the system to manage their own health information and search for medical institutions.

[0313] "Body part" refers to the specific part of the body where the user experiences symptoms.

[0314] "Symptoms" refer to specific conditions or signs that a user perceives as abnormal in their health.

[0315] "Medical institutions" refer to facilities such as hospitals and clinics that users visit to receive medical treatment or diagnosis.

[0316] "Searching" refers to the process of finding a suitable medical institution based on the criteria specified by the user.

[0317] "Health information" refers to medical-related information such as the user's medical history, prescription history, and diagnosis results.

[0318] "Emotions" refer to the user's psychological state and are analyzed to adjust the way information is displayed.

[0319] "Display format" refers to the layout and style used when presenting information to the user.

[0320] "Input" refers to the act of a user providing information to a system.

[0321] A "server" refers to a computer system that processes user requests and manages information.

[0322] A "database" refers to an information system used to systematically store and manage users' health information.

[0323] A description of embodiments for carrying out this invention will be given.

[0324] This system aims to allow users to efficiently manage their health information and quickly find necessary medical facilities. Users input their health information using a dedicated application or web browser and send it to the server. The terminal sends the information entered by the user to the server as an HTTP request. In this case, the data is typically sent in JSON format.

[0325] The server analyzes the received information and stores it in a database such as MySQL or PostgreSQL. The data is stored linked to the user ID, making it easy to search later. When a user wants to view their health information, they send a request from their device, and the server retrieves the relevant information from the database.

[0326] Furthermore, the server uses sentiment analysis APIs to analyze the user's emotions. For example, it can utilize Microsoft Azure's sentiment analysis API or Google Cloud's natural language API. Based on the user's emotions, the server adjusts the display format of health information and sends it to the device. This makes the information easier for the user to understand.

[0327] As a concrete example, consider a case where a user is prescribed a new medication. The user opens the application and clicks the "Add New Medication" button. The device sends the name and dosage of the medication entered by the user to the server. The server saves this information to the database and returns a message to the device confirming that the information has been saved. Later, if the user wants to check their prescription history, they click the "View Prescription History" button in the application. The server retrieves the information from the database, organizes it according to the user's mood, and sends it to the device. The device displays the information to the user, allowing them to check their prescription history.

[0328] An example of a prompt to input into a generative AI model is, "How can I display the medical history based on the user's emotions?" This prompt allows the AI ​​model to suggest ways to display information that are appropriate to the user's feelings.

[0329] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0330] Step 1:

[0331] The user enters their health information. The user enters health information, such as medical history and prescription history, using a dedicated application or web browser. The entered data is converted to JSON format by the terminal. Specifically, the user clicks a button labeled "Add New Medication" and enters the name and dosage of the medication.

[0332] Step 2:

[0333] The terminal sends input data to the server. The terminal sends the JSON-formatted data entered by the user to the server as an HTTP request. The input is the user's health information, and the output is the transmission of data to the server. Specifically, the terminal sends data to the server when the send button is pressed.

[0334] Step 3:

[0335] The server saves the data to a database. The server parses the received JSON data and saves it to a database such as MySQL or PostgreSQL. The input is health information received from the terminal, and the output is a message indicating that the data has been successfully saved to the database. Specifically, the server stores the data associated with the user ID.

[0336] Step 4:

[0337] The user sends a request to view their health information. The user sends a request from their device to view their health information through an application or web browser. The input is the user's viewing request, and the output is the request sent to the server. Specifically, the user clicks a button labeled "View Prescription History".

[0338] Step 5:

[0339] The server retrieves information from the database. The server receives a request from the user and retrieves the corresponding health information from the database. The input is the user's request, and the output is the retrieved health information. Specifically, the server executes a database query to retrieve the information.

[0340] Step 6:

[0341] The emotion engine analyzes the user's emotions. The server uses an emotion analysis API to analyze the user's emotions. The input is the user's past behavior data and input data, and the output is the user's emotional state. Specifically, the server sends data to the emotion analysis API and receives the analysis results.

[0342] Step 7:

[0343] The server sends information to the terminal in a format appropriate to the user's emotions. Based on the analysis results of the emotion engine, the server adjusts the display format of the health information and sends it to the terminal. The input is the acquired health information and emotion analysis results, and the output is the adjusted information. Specifically, the server summarizes and sends the information concisely.

[0344] Step 8:

[0345] The terminal displays information to the user. The terminal displays information received from the server to the user. The input is the processed information from the server, and the output is the display of information to the user. Specifically, the terminal displays information on the screen, and the user checks their own health information.

[0346] (Application Example 2)

[0347] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0348] In today's healthcare environment, users are expected to manage their health information appropriately and smoothly select healthcare providers and pay medical expenses. However, it is a difficult challenge for users to properly understand and utilize information in accordance with their emotional state. In particular, referring to past health information and making appropriate decisions when paying medical expenses can be burdensome for users.

[0349] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0350] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing health information for each user; means for recognizing the user's emotions and adjusting the way health information is displayed based on those emotions; and means for referring to past health information when paying medical expenses and assisting with payment. As a result, users can appropriately understand information according to their emotional state and smoothly select a medical institution and pay medical expenses.

[0351] A "user" is an individual who uses the system to manage their own health information, select medical institutions, and pay for medical expenses.

[0352] A "medical institution" refers to facilities such as hospitals and clinics that users visit to improve their health or receive diagnoses.

[0353] "Health information" is a general term for medical-related data such as a user's medical history, prescription history, and diagnosis results.

[0354] "Emotions" refer to the user's psychological state, which the system recognizes and uses to adjust how information is displayed.

[0355] "Payment" refers to a monetary transaction that a user makes for medical services.

[0356] A "server" is a computer system that manages users' health information and performs tasks such as searching for medical facilities and recognizing emotions.

[0357] A description of the embodiment for carrying out the invention will be provided.

[0358] The system that realizes this invention consists of a user's smartphone or tablet and a server located in the cloud. The server manages the user's health information and runs programs for searching for medical institutions and performing emotion recognition. Specifically, the server stores the user's health information using a database management system (e.g., Firebase) and analyzes the user's emotions using an emotion recognition engine (e.g., Affectiva SDK).

[0359] When a user searches for a medical facility using their device, the server searches for an appropriate facility based on the affected area or symptoms specified by the user and displays the results on the device. Furthermore, the server analyzes the user's emotions through the camera and microphone using an emotion recognition engine and adjusts how health information is displayed based on those emotions. For example, if the user is feeling anxious, the server displays information concisely and supports the payment process.

[0360] As a concrete example, when a user is paying at a hospital, they launch the app, and the camera reads their facial expression. If the emotion is recognized as "anxiety," the server briefly displays past health information and suggests payment methods. In this case, a generative AI model can be used to display information and suggest payment methods that are appropriate for the user.

[0361] An example of a prompt would be, "Please tell me how to analyze the user's emotions, concisely display past health information, and support payment." Using this prompt, the generative AI model can provide the user with the most relevant information.

[0362] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0363] Step 1:

[0364] The user launches the application on their device and begins searching for a medical institution. As input, the user specifies the affected area and symptoms. The device then sends this information to the server.

[0365] Step 2:

[0366] The server searches its database for appropriate medical institutions based on the received information about the affected area and symptoms. It uses a database management system (e.g., Firebase) to extract information about relevant medical institutions. The server then generates search results as output and sends them to the terminal.

[0367] Step 3:

[0368] The terminal displays the search results for medical institutions received from the server to the user. The user reviews the displayed information and selects a medical institution as needed.

[0369] Step 4:

[0370] After the user selects a medical institution, the device uses its camera and microphone to collect the user's emotions. It acquires the user's facial expressions and voice data as input.

[0371] Step 5:

[0372] The server uses an emotion recognition engine (e.g., Affectiva SDK) to analyze collected facial and voice data and recognize the user's emotions. It then generates and sends the recognized emotion information as output to the terminal.

[0373] Step 6:

[0374] The device adjusts how health information is displayed based on emotional information received from the server. For example, if the user is feeling anxious, the information will be displayed more concisely.

[0375] Step 7:

[0376] When a user pays for medical expenses, the terminal refers to past health information and suggests a payment method. The server uses a generative AI model to generate a payment method suitable for the user. The prompt message used is, "Please tell me how to analyze the user's emotions, concisely display past health information, and support payment."

[0377] Step 8:

[0378] The terminal displays the generated payment method to the user, and the user pays the medical expenses using the suggested method.

[0379] (Example 3)

[0380] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0381] In modern medical information systems, it is difficult for users to quickly and accurately find a medical institution suitable for their symptoms. Furthermore, the display of information is often not tailored to the user's emotional state, making it difficult to understand. Additionally, managing users' medical and prescription histories is cumbersome, and there are challenges in easily accessing past treatment records.

[0382] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0383] In this invention, the server includes means for searching for an appropriate medical institution based on a body part or symptom specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the way information is displayed based on those emotions; and means for saving and making the user's past medical history accessible. As a result, the user can quickly find an appropriate medical institution, understand information more easily through emotion-based display, and easily access their past medical history.

[0384] A "user" refers to an individual who uses the system to search for medical information and manage their medical history.

[0385] "Body part" refers to a specific area of ​​the body where the user experiences symptoms.

[0386] "Symptoms" refer to physical or mental abnormalities experienced by the user.

[0387] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[0388] "Searching" refers to the act of finding relevant information from a database based on conditions specified by the user.

[0389] "Display" refers to the act of making search results and information visually accessible to users.

[0390] "Emotions" refer to the user's psychological state and are the subject of analysis by the system.

[0391] "Medical history" refers to the records of medical services a user has received in the past.

[0392] "Saving" refers to the act of recording information in a database so that it can be referenced later.

[0393] "Referencing" refers to the act of a user checking saved information.

[0394] To implement this invention, the server, terminal, and user must each fulfill their respective roles. The server uses a database management system to search for medical institutions based on the body parts and symptoms specified by the user. Specifically, the server uses a database management system such as MySQL and executes SQL queries to extract relevant information.

[0395] The server analyzes the user's emotions using emotion recognition software. For example, it uses an emotion recognition API to recognize emotions from text or voice input by the user. Based on this information, the server adjusts how the information is displayed and provides it in a format that is easy for the user to understand.

[0396] The terminal provides an interface for users to input information and view search results from the server. Through the terminal, users can input body parts and symptoms and view the search results.

[0397] For example, if a user enters "headache," the server will display a message such as "Looking for a doctor specializing in headaches" and provide a list of relevant doctors and hospitals. It will also display information about medical institutions the user has visited in the past, their diagnoses, and the medications they have been prescribed.

[0398] An example of a prompt to the generative AI model might be, "Please tell me how to search for doctors related to the affected area specified by the user and display the information based on emotion." Using this prompt, the generative AI model can be asked to specify a particular processing method. The flow of the specific processing in Example 3 will be explained using Figure 21.

[0399] Step 1:

[0400] The user uses a terminal to access the system and enter information about body parts and symptoms. The entered information is sent to the server. For example, the user might type "headache" and press the submit button.

[0401] Step 2:

[0402] The server uses a database management system to search for medical institutions based on the user's input information. The server executes an SQL query to extract information about doctors and hospitals related to "headache" from the database. The input is the user's symptom information, and the output is a list of relevant medical institutions.

[0403] Step 3:

[0404] The server sends the search results to the user's device. The device displays the received information to the user. Specifically, the device displays a "list of headache specialists" on the screen. The input is the search results from the server, and the output is information that the user can visually confirm.

[0405] Step 4:

[0406] The server analyzes the user's emotions using emotion recognition software. The emotion recognition API determines the emotion based on the text and voice data entered by the user. The input is the user's emotion data, and the output is the result of the emotion analysis.

[0407] Step 5:

[0408] The server adjusts how information is displayed based on the analyzed emotions. For example, if the server determines that the user is confused, it converts the information into a simpler, easier-to-understand format and sends it to the terminal. The input is the result of the emotion analysis, and the output is the adjusted information display.

[0409] Step 6:

[0410] The server stores the user's past medical history in a database and makes it accessible as needed. Specifically, the server updates the medical history so that the user can review it later. The input is new medical information, and the output is the updated medical history.

[0411] (Application Example 3)

[0412] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0413] In today's healthcare environment, it is difficult for users to quickly find a medical institution that is appropriate for their symptoms. Furthermore, managing medical history, displaying information in a way that responds to emotions, and choosing payment methods for medical expenses all present significant challenges for users. To address these challenges, a flexible system that meets user needs is necessary.

[0414] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0415] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing each user's medical history; means for analyzing the user's emotions and adjusting the display method of the medical history according to those emotions; and means for suggesting a payment method for medical expenses. As a result, the user can quickly and appropriately select a medical institution, receive information displayed according to their emotions, and choose the optimal payment method.

[0416] A "user" refers to an individual who uses the system to search for medical institutions or manage their medical history.

[0417] "Affected area or symptoms" refers to the body part or health condition that a user specifies when searching for a medical institution.

[0418] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[0419] "Search method" refers to a function that finds appropriate medical institutions based on the conditions specified by the user.

[0420] "Medical history" refers to data that includes a user's past medical records and information about prescribed medications.

[0421] "Means of analyzing emotions" refers to functions that recognize the user's emotional state and adjust the system's operation based on that information.

[0422] "Means for adjusting the display method" refers to a function that changes the way information is presented according to the user's emotions.

[0423] "Means of suggesting payment methods" refers to a function that presents users with the most suitable method for paying medical expenses.

[0424] The system for implementing this invention consists of a user's smartphone or tablet and a server in the cloud. The server searches for appropriate medical institutions based on the affected area or symptoms specified by the user and displays the results on the user's device. A database management system (e.g., Firebase) is used for the search to enable rapid information provision.

[0425] The server also manages the user's medical history and analyzes the user's emotions using an emotion analysis engine (e.g., Microsoft Azure's Emotion Analysis API). This allows the display of the medical history to be adjusted according to the user's emotions. For example, if the user is feeling anxious, the information may be displayed simply to provide reassurance.

[0426] Furthermore, the server has a function to suggest payment methods for the user's medical expenses. It takes into account the user's past payment history and current emotional state to suggest the most suitable payment method.

[0427] As a concrete example, when a user opens the app after a consultation, the sentiment analysis engine detects anxiety from the user's facial expressions and voice. It retrieves past medical history from Firebase and suggests a simple payment method (e.g., one-click payment). An example of a prompt to input into the generating AI model is, "If the user is feeling anxious after a consultation, please refer to their past medical history and suggest the most suitable payment method."

[0428] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0429] Step 1:

[0430] The user uses a device to input information about the affected area and symptoms. The device sends this information to the server. The entered information is stored on the server as data indicating the user's current health status.

[0431] Step 2:

[0432] Based on the received information about the affected area and symptoms, the server uses a database management system (e.g., Firebase) to search for appropriate medical institutions. A list of medical institutions is generated as a search result and sent to the device.

[0433] Step 3:

[0434] The terminal displays a list of medical institutions received from the server to the user. The user selects a desired medical institution from this list. The selected information is sent to the server for the next processing step.

[0435] Step 4:

[0436] The server analyzes the user's emotions using an emotion analysis engine (e.g., Microsoft Azure's Emotion Analysis API) based on the user's selection. It uses the user's voice and facial expression data as input and outputs the emotional state as the analysis result.

[0437] Step 5:

[0438] The server adjusts how the user's medical history is displayed based on the results of sentiment analysis. For example, if the user is feeling anxious, the data is processed to display information in a simpler way before being sent to the device.

[0439] Step 6:

[0440] The server considers the user's past payment history and current emotional state to suggest the most suitable payment method for medical expenses. The suggested payment method is sent to the terminal and displayed to the user.

[0441] Step 7:

[0442] The user reviews and selects a payment method displayed on their device. The selected payment method is sent to the server, and the payment process is initiated.

[0443] (Other examples)

[0444] Next, other embodiments will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0445] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, efficiently managing and updating users' health information is crucial, but doing so manually is time-consuming. Additionally, generating prompts to search for appropriate medical institutions based on user input requires specialized knowledge, making it difficult for the average user.

[0446] The identification process performed by the identification processing unit 290 of the data processing device 12 in other embodiments is realized by the following means.

[0447] In this invention, the server includes means for providing an interface for the user to input a specified body part or symptom; means for generating prompts to instruct the user to search for an appropriate medical institution using a generative AI model based on the input information; and means for searching for a medical institution using the generated prompts and formatting the results to display them in a user-friendly format. This enables the user to quickly and efficiently find an appropriate medical institution.

[0448] A "user" refers to an individual who uses the system to input their health information and search for appropriate medical institutions.

[0449] A "device" is a device used by a user to input information or view search results, and includes smartphones and personal computers.

[0450] A "server" refers to a computer system that receives input information from users, generates prompts using a generative AI model, and performs searches for medical institutions.

[0451] A "generative AI model" refers to an artificial intelligence model that generates prompts based on user input and searches for appropriate medical institutions.

[0452] A "prompt" refers to a text-based instruction generated to tell a generative AI model to perform a specific action.

[0453] An "interface" refers to a component of software that provides a screen or form for users to input information.

[0454] A "database" refers to a digital information management system used to store and manage information about medical institutions and users' health information.

[0455] This invention is a system that enables users to quickly find appropriate medical facilities based on their symptoms. The system consists of a user's terminal, a server, and a generative AI model.

[0456] Users input body parts and symptoms through the device's interface. This interface is implemented as a form on a web browser or as an input screen in a mobile application. For example, when a user inputs symptoms such as "headache" and "dizziness," the information is sent to the system.

[0457] The server generates prompt messages using a generative AI model based on the information received from the user. This generative AI model uses a natural language processing model such as OpenAI's GPT series. An example of a prompt message is, "Please search for the most suitable medical institution based on the symptoms entered by the user."

[0458] The generated prompt sentence is input into a generative AI model, which provides instructions for searching for an appropriate medical institution. The generative AI model analyzes the prompt sentence and retrieves information about relevant medical institutions from a database. This database contains information such as the medical institution's location, medical specialties, and operating hours.

[0459] The server formats the search results obtained from the generated AI model and sends them to the terminal in a format that the user can easily understand. The terminal displays the search results in a list format or by placing pins on a map.

[0460] Furthermore, the server stores and manages each user's health information in a database. This database includes information about the user's past medical history and health status. Users can check their health information through their terminal and update it as needed. For example, if a new symptom appears after a medical examination, that information can be added.

[0461] This system allows users to quickly and efficiently find appropriate medical facilities. Furthermore, the use of a generative AI model enables flexible searches based on user input.

[0462] The flow of specific processing in other embodiments will be explained using Figure 23.

[0463] Step 1:

[0464] The user uses the terminal's interface to input information about body parts and symptoms. The entered information includes specific symptoms such as "headache" and "dizziness." This information is sent from the terminal to the server. The entered data is used as basic data to identify the user's symptoms.

[0465] Step 2:

[0466] The server generates prompt messages for input into the generative AI model based on the symptom information received from the user. Specifically, the server creates a prompt message in the format of "Please search for the most suitable medical institution based on the symptoms entered by the user." This prompt message functions as an instruction to the generative AI model.

[0467] Step 3:

[0468] The server inputs the generated prompt text into the generation AI model. The generation AI model analyzes the prompt text and retrieves information about relevant medical institutions from the database. Based on the input prompt text, the generation AI model searches for information such as the location, medical specialties, and operating hours of medical institutions and outputs a list of the most suitable medical institutions.

[0469] Step 4:

[0470] The server formats the search results obtained from the generating AI model and converts them into a format that is easy for the user to understand. Specifically, it formats the search results into a list format or a format where pins are placed on a map. This formatted result is sent to the terminal and displayed to the user.

[0471] Step 5:

[0472] The server stores and manages each user's health information in a database. Users can check their health information through their terminal and update it as needed. For example, if new symptoms appear after a medical examination, they can add that information. The database holds information about the user's past medical history and health status, supporting the user's health management.

[0473] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0474] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0475] Other examples of generative AI include Gemini® (registered trademark) (Internet search). <url: https: gemini.google.com ?hl="ja">) are some examples.

[0476] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0477] [Second Embodiment]

[0478] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0479] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0480] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0481] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0482] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0483] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0484] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0485] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0486] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0487] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0488] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0489] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0490] "Example of form 1"

[0491] The system of the present invention has a function to search for an appropriate hospital (doctor) based on the affected area and symptoms specified by the user. Specifically, when the user enters their affected area and symptoms on the interface, the system searches the database for information on hospitals and doctors and displays the results to the user. This function allows the user to efficiently find a hospital or doctor suitable for their symptoms.

[0492] "Example of form 2"

[0493] Furthermore, the system of the present invention has a function to manage each user's medical history and prescription history. Specifically, the system stores information such as hospitals and doctors the user has visited in the past, diagnoses, and prescribed medications in a database, allowing the user to refer to this information at any time. This function allows users to easily manage their own medical history and prescription history.

[0494] "Example of form 3"

[0495] For example, if a user specifies "headache" as the affected area, the system searches its database for hospital and doctor information and displays headache specialists and hospitals that can treat headaches to the user. It also saves information such as hospitals and doctors the user has visited for headaches in the past, diagnoses, and prescribed medications, allowing the user to access this information at any time.

[0496] The following describes the processing flow for each example of the form.

[0497] "Example of form 1"

[0498] Step 1: The user enters their affected area and symptoms on the system interface. Step 2: The system searches its database for hospital and doctor information and extracts hospitals and doctors suitable for the affected area and symptoms entered by the user.

[0499] Step 3: The system displays the extracted hospital and doctor information to the user.

[0500] "Example of form 2"

[0501] Step 1: The user enters their medical history and prescription history into the system.

[0502] Step 2: The system saves the medical history and prescription history entered by the user to the database.

[0503] Step 3: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[0504] "Example of form 3"

[0505] Step 1: The user enters "headache" as the affected area into the system.

[0506] Step 2: The system searches the database for hospital and doctor information and extracts headache specialists and hospitals that can treat headaches.

[0507] Step 3: The system displays the extracted hospital and doctor information to the user.

[0508] Step 4: The user enters information into the system, such as the hospitals and doctors they have visited in the past for headaches, their diagnoses, and the medications they have been prescribed.

[0509] Step 5: The system saves the information entered by the user to the database.

[0510] Step 6: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[0511] (Example 1)

[0512] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0513] There is a challenge in that it is difficult for users to quickly and accurately find the appropriate medical institution based on their body part and symptoms. Furthermore, there is a need to efficiently manage and update each user's health information as needed.

[0514] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0515] In this invention, the server includes means for searching for an appropriate medical institution based on the body part or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. As a result, users can quickly find an appropriate medical institution and manage and update their health information efficiently.

[0516] A "user" refers to an individual who uses the system to search for appropriate medical institutions based on their own body parts and symptoms.

[0517] "Body parts and symptoms" refers to information related to a user's health condition that they enter when searching for a medical institution.

[0518] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[0519] "Searching" refers to the process of examining information within a database based on conditions specified by the user and finding appropriate results.

[0520] "Display" refers to outputting search results to the device in a format that is easy for the user to understand.

[0521] "Health information" refers to data related to a user's health status, such as their medical history and prescription history.

[0522] "Management" refers to the process of organizing health information and updating or correcting it as needed.

[0523] A "server" refers to a computer system that receives input from users, searches a database, and returns the results.

[0524] A "terminal" refers to a device that a user uses to access a system through an interface.

[0525] As an embodiment of this invention, the following system is constructed.

[0526] The server generates a program that searches for appropriate medical institutions based on the body parts and symptoms specified by the user. This program consists of multiple components, including a user interface, database access, and a search algorithm. Specifically, the server implements the search algorithm using Python and manages medical institution information using a MySQL database.

[0527] The user uses the terminal's interface to input information about their body parts and symptoms. The terminal sends this input to the server. The server searches its database for information on medical institutions based on the received information. The search results are returned to the terminal and displayed to the user.

[0528] For example, if a user enters "stomach ache," the server searches its database for medical institutions specializing in "gastroenterology." The search results might display "local gastroenterology clinics" or "gastrointestinal hospitals in the city."

[0529] An example of a prompt to input into the generating AI model might be: "Create a program that searches for appropriate medical institutions based on the symptoms entered by the user. Use MySQL as the database and implement the search algorithm in Python."

[0530] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0531] Step 1:

[0532] The user accesses the device's interface and enters information about their body parts and symptoms. This entered data is saved on the device in text format. This data serves as foundational information for identifying the user's health problems.

[0533] Step 2:

[0534] The terminal sends the information entered by the user to the server as an HTTP request. This request contains data about the user's symptoms. The server receives this request and prepares to look up the database.

[0535] Step 3:

[0536] The server parses the received user information and queries a MySQL database. The database contains information such as the medical institution's specialty, location, and operating hours. The server uses a search algorithm implemented in Python to identify the medical institution best suited to the user's symptoms. The input is the user's symptom data, and the output is a list of appropriate medical institutions.

[0537] Step 4:

[0538] The server returns the search results to the terminal in JSON format. This result includes the name, address, and contact information of the medical institution. The server then processes the data to convert it into a format that is easy for the user to understand.

[0539] Step 5:

[0540] The device displays the received search results in a user-friendly format. Users can view detailed information about medical institutions on the screen and contact them as needed. The displayed information helps users make quick decisions when selecting a medical institution.

[0541] (Application Example 1)

[0542] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0543] In modern society, it is crucial for users to quickly and accurately find medical institutions that are appropriate for their symptoms. However, traditional methods present challenges, such as time-consuming information searches and difficulty for users to select the right medical institution. Furthermore, the lack of efficient means to manage and update users' health information as needed can lead to a decline in the quality of medical services.

[0544] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0545] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. This enables users to quickly find an appropriate medical institution and allows for efficient management and updating of health information.

[0546] A "user" is an individual who uses the system to search for medical institutions based on their own symptoms.

[0547] "Affected area or symptoms" refers to the physical ailments or medical conditions that users enter when searching for medical institutions.

[0548] A "medical institution" refers to a facility that provides medical services, such as a hospital or clinic.

[0549] "Searching" is the act of finding appropriate information from a database based on conditions specified by the user.

[0550] "Health information" refers to a user's medical history, prescription history, and other personal information related to medical care.

[0551] A "smart device" refers to a portable electronic device with internet connectivity, such as a smartphone or tablet.

[0552] "Real-time" refers to information being processed and provided to the user immediately.

[0553] "Expert advice" refers to advice provided to users by professionals with medical knowledge.

[0554] The invention will now be described in terms of embodiments for carrying out the invention. This invention is a system in which a user inputs their symptoms using a smart device and searches for an appropriate medical institution. The system consists of a server, a user terminal, and a database.

[0555] The server searches for medical institution information in its database based on the affected area and symptoms specified by the user, and displays the results on the user's terminal. The server is built using Python and Flask, and uses SQLite for its database. The server receives user input and generates search results in real time.

[0556] The user terminal is a smart device such as a smartphone or tablet, and provides an interface for the user to input symptoms. The user terminal displays the search results received from the server and provides the information in a format that the user can easily understand.

[0557] For example, when a user enters "headache," the server searches the database and suggests nearby neurology clinics. This allows the user to quickly find an appropriate medical facility.

[0558] By using generative AI models, it is also possible to provide expert advice based on the user's symptoms. An example of a prompt message would be: "Based on the symptoms entered by the user, please suggest the most suitable medical institution. Example: For headaches, suggest a neurology hospital."

[0559] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0560] Step 1:

[0561] The user launches the application on their smart device and accesses the symptom input screen. The user enters their affected area and symptoms in text format. The entered data is sent from the user's device to the server.

[0562] Step 2:

[0563] The server analyzes the symptom data received from the user. This analysis uses natural language processing techniques to extract keywords from the input text. Based on the extracted keywords, the server searches for medical institution information in the database.

[0564] Step 3:

[0565] The server generates the results of a database search. The search results include a list of medical institutions suitable for the user's symptoms. The server sends the search results to the user's terminal.

[0566] Step 4:

[0567] The user terminal displays the search results received from the server. The display is in a format that is easy for the user to understand. The user can select the appropriate medical institution from the displayed list.

[0568] Step 5:

[0569] The server uses a generative AI model to generate expert advice based on the user's symptoms. Symptom data is input into the AI ​​model using prompts to obtain appropriate advice. The resulting advice is then sent to the user's terminal.

[0570] Step 6:

[0571] The user terminal displays expert advice received from the server. Users can use this advice to decide on a healthcare provider and their next course of action.

[0572] (Example 2)

[0573] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0574] In modern healthcare, it is crucial for users to efficiently manage their health information and quickly find appropriate medical facilities. However, traditional systems have problems such as users not being able to easily access past health information and the time it takes to search for medical facilities. Furthermore, there were challenges in ensuring the security of health information and obtaining appropriate advice based on that information.

[0575] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0576] In this invention, the server includes means for searching for an appropriate medical institution based on symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing each user's health information. This enables users to efficiently manage their own health information and quickly search for an appropriate medical institution.

[0577] A "user" refers to an individual who uses the system to manage their own health information and search for medical institutions.

[0578] "Symptoms" refers to changes in health conditions or physical state that users specify when searching for medical institutions.

[0579] "Medical institutions" refer to facilities such as hospitals and clinics where users can receive medical treatment.

[0580] "Search results" refer to information about medical institutions provided by the system based on the conditions specified by the user.

[0581] "Health information" refers to medical-related data such as a user's medical history, prescription history, and diagnosis results.

[0582] A "database" refers to an information management system used to store and manage users' health information.

[0583] "Encryption" refers to a technology that transforms data to protect users' health information and prevent third parties from easily accessing it.

[0584] A "generative AI model" refers to artificial intelligence technology that provides advice and predictions based on a user's health information.

[0585] "Advice" refers to suggestions and recommendations provided by the generative AI model based on the user's health information.

[0586] This system enables users to efficiently manage their health information and quickly find appropriate medical facilities. The following describes embodiments for carrying out the invention.

[0587] The server stores user-entered health information in a database. The database uses a relational database management system such as MySQL. When users enter their past medical history and prescription history via a dedicated terminal or web application, the server receives this information and stores it in the database. The stored data is encrypted using the AES encryption algorithm to ensure security.

[0588] Users can search for and retrieve their own health information from their devices. The server queries the database based on the user's search criteria and retrieves the relevant information. The retrieved data is displayed on the user's device through an interface using React.js. This allows users to intuitively check the information.

[0589] Furthermore, by utilizing generative AI models, it is possible to provide advice based on the user's health information. Users can receive advice from the AI ​​model by entering prompts. For example, by entering a prompt such as, "Generate important information to tell my doctor at my next appointment," the AI ​​model will analyze the user's health information and generate appropriate advice.

[0590] This system allows users to centrally manage their health information and use it to their advantage when receiving medical treatment at a healthcare facility.

[0591] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0592] Step 1:

[0593] Users enter their past medical and prescription history using a dedicated terminal or web application. This information includes hospital names, doctor names, diagnoses, and the names and dosages of prescribed medications. This information is then transmitted to the server via a form.

[0594] Step 2:

[0595] The server receives health information submitted by users and stores it in a database. MySQL is used for the database, managing each user's information as a separate record. During storage, the data is encrypted using the AES encryption algorithm to ensure security. The input is the user's health information, and the output is the encrypted database record.

[0596] Step 3:

[0597] If a user wants to check their past medical history or prescription history, they enter search criteria on their device. For example, they can specify specific conditions such as "diagnosis results from March 2023."

[0598] Step 4:

[0599] The server queries the database based on the user's search criteria and retrieves the relevant information. The retrieved data is displayed on the user's device through an interface using React.js. The input is the user's search criteria, and the output is health information as search results.

[0600] Step 5:

[0601] Users can receive advice based on their past medical history data using a generative AI model. Users input prompts and receive advice from the AI ​​model. For example, a user might input a prompt such as, "Generate important information I should tell my doctor at my next appointment." The server uses the AI ​​model to analyze the user's health information and generate appropriate advice. The input consists of prompts and health information, while the output is the advice from the AI ​​model.

[0602] (Application Example 2)

[0603] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0604] In modern healthcare systems, users are required to efficiently manage their health information and easily understand how to choose healthcare providers, pay medical expenses, and access insurance coverage. However, traditional systems have the problem that this information is scattered, making it difficult for users to quickly obtain the information they need.

[0605] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0606] This invention includes a server that provides means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, means for managing each user's health information, means for managing the payment history and insurance coverage status of medical expenses based on the user's health information, and means for allowing the user to check past medical expense payments and insurance coverage status. As a result, users can centrally manage their own health information and efficiently select medical institutions and manage their medical expenses.

[0607] A "user" is an individual who uses the system to manage their own health information, select medical institutions, and manage their medical expenses.

[0608] "Health information" refers to data that includes information such as the user's medical history, prescription history, diagnosis results, medical expense payment history, and insurance coverage status.

[0609] A "medical institution" refers to facilities such as hospitals and clinics that are searched based on the affected area or symptoms specified by the user.

[0610] "Medical expenses" refer to the costs that users pay for medical consultations and treatments at medical institutions.

[0611] "Insurance coverage status" refers to information indicating the extent to which the user's insurance covers medical expenses.

[0612] "Search functionality" refers to a feature that finds appropriate medical institutions based on conditions specified by the user and displays the results.

[0613] "Management means" refers to a function that stores users' health information in a database and allows for updates and retrieval as needed.

[0614] As an embodiment of this invention, a system is provided that manages users' health information and efficiently manages the selection of medical institutions and medical expenses. The system consists of an application installed on a terminal such as a smartphone and a server that operates on the cloud.

[0615] The server searches for appropriate medical institutions based on the affected area and symptoms specified by the user and displays the results on the terminal. A database management system (e.g., MySQL) is used for the search to quickly retrieve information on medical institutions. Furthermore, the server manages the user's medical expense payment history and insurance coverage status based on the user's health information. This involves retrieving the user's past medical data and insurance information from the database and performing calculations.

[0616] The device will allow users to check their past medical payment history and insurance coverage through the application. A front-end framework (e.g., React Native) will be used to build the user interface and display the information in a visually clear and easy-to-understand manner.

[0617] For example, when a user opens the app and enters "Show me my medical expense payment history for the past 3 months," the server retrieves the relevant information from the database and displays it on the device. An example of a prompt that uses a generative AI model to analyze user input and provide appropriate information is, "Retrieve the user's medical expense payment history for the past 3 months and display it, including insurance coverage status."

[0618] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0619] Step 1:

[0620] The user launches the application using their device and provides input to retrieve specific information. For example, they might enter a prompt such as, "Show me my medical expense payment history for the past three months." The entered prompt is then analyzed by a generative AI model to identify the type of information needed.

[0621] Step 2:

[0622] The terminal sends a request to the server based on the parsed prompt. The request includes the user ID and the type of information requested (e.g., medical expense payment history). The server parses the received request and uses a database management system (e.g., MySQL) to search for the relevant information in the user's health information database.

[0623] Step 3:

[0624] The server calculates medical expense payment history and insurance coverage status based on information retrieved from the database. Past medical data and insurance information are used for the calculations. The calculation results are formatted in a user-friendly format.

[0625] Step 4:

[0626] The server sends the formatted information to the terminal. The terminal then uses a frontend framework (e.g., React Native) to visually display the received information on the user interface. The user can review the displayed information and decide on the next action as needed.

[0627] (Example 3)

[0628] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0629] In the modern healthcare system, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, it is difficult to manage and easily access past diagnoses and prescription histories when needed. This can lead to users missing opportunities to receive appropriate medical care.

[0630] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0631] This invention includes a server that searches for and displays appropriate medical institutions based on body parts and symptoms specified by the user, means for reducing the time required to search for medical institutions, and means for managing each user's health history and medication history. As a result, users can quickly find appropriate medical institutions and easily manage and refer to past diagnosis results and prescription history.

[0632] A "user" is an individual who uses the system to search for medical institutions based on their own health status and symptoms, and manages that information.

[0633] "Body part" refers to a specific area of ​​the body where the user experiences symptoms, and is information used as a basis for searching for medical institutions.

[0634] "Symptoms" refer to physical or mental abnormalities or discomforts experienced by the user, and serve as the basis for information used when searching for medical institutions.

[0635] A "medical institution" refers to facilities such as hospitals and clinics that provide medical care to address the user's symptoms.

[0636] "Searching" is the process of finding appropriate medical institutions from a database based on the conditions specified by the user.

[0637] "Health history" refers to information about a user's past diagnoses and treatments, and is data that users use to manage their own health status.

[0638] "Medication history" refers to information about medications a user has been prescribed in the past, and is data that users use to manage their own drug therapy.

[0639] "Management" refers to the process of saving a user's health history and medication history, and making it possible to update and refer to it as needed.

[0640] One embodiment of this invention is to provide a system that allows users to quickly find appropriate medical facilities based on their symptoms and to manage their past health and medication history.

[0641] The server receives information about body parts and symptoms entered by the user through their terminal and searches its database. This database contains information such as the specialty and location of medical institutions, and searches are performed using a database management system such as SQL. The server sends the search results to the user's terminal and displays them in a format that the user can easily understand.

[0642] Users can input information about past diagnoses and prescribed medications through their devices. The server stores this information in a database, making it accessible to users when needed. This allows users to manage their health and stay informed about the information necessary to receive appropriate medical care.

[0643] For example, if a user enters "headache" as a symptom, the server will display information such as "headache specialist clinics" and "neurology hospitals." It will also save information about past visits to "headache specialist clinics," diagnoses of "migraines," and prescriptions for "ibuprofen," allowing the user to refer to this information.

[0644] By utilizing generative AI models, systems can be designed and improved. An example of a prompt message is, "Design a system that searches for information on specialists and hospitals corresponding to the affected area specified by the user, and allows the user to save and refer to past diagnostic results and prescribed medications." The flow of specific processing in Example 3 will be explained using Figure 15.

[0645] Step 1:

[0646] The user inputs symptoms and body parts through the terminal's interface. The entered information is sent from the terminal to the server. For example, if the user inputs "headache," the terminal sends this information to the server in real time.

[0647] Step 2:

[0648] The server searches the database based on the received symptom information. The input is information about "headaches," and the server uses an SQL query to extract information about relevant medical institutions from the database. The output is a list of medical institutions that can treat headaches. Specifically, the server searches for information on "headache specialist clinics" and "neurology hospitals."

[0649] Step 3:

[0650] The server sends the search results to the user's device. The device displays the received information to the user. Specifically, the device displays a list of "headache specialist clinics" and "neurology hospitals" on the screen, allowing the user to select one.

[0651] Step 4:

[0652] The user enters information about past diagnoses and prescribed medications into the terminal. The entered information is sent from the terminal to the server and stored in the database. Specifically, if the user enters information that they were diagnosed with "migraine" and prescribed "ibuprofen," the server saves this information to the database.

[0653] Step 5:

[0654] Users can access their saved health and medication history. The device retrieves information from the server upon user request and displays it on the screen. Specifically, when a user wants to review past diagnostic results, the device retrieves information from the server and displays a history of being diagnosed with "migraine."

[0655] (Application Example 3)

[0656] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0657] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, the procedures for paying medical expenses after consultations and managing past medical history are also cumbersome. There is a need to solve these problems and provide convenient healthcare services for users.

[0658] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0659] In this invention, the server includes means for searching for an appropriate medical institution based on a body part or symptom specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing each user's medical history and prescription history; means for performing electronic payment after the consultation; and means for generating prompt messages to search for relevant medical institutions using a generative AI model. This makes it possible for users to quickly find an appropriate medical institution, easily make payments after the consultation, and easily manage their past medical history.

[0660] A "user" is an individual who uses the system to search for medical institutions and manage their medical history.

[0661] "Body parts and symptoms" refers to information about a user's health condition that they specify when searching for a medical institution.

[0662] "Medical institutions" refer to hospitals and clinics that can treat the user's symptoms.

[0663] "Search methods" refer to functions that allow users to find appropriate medical institutions based on the information they specify.

[0664] "Display means" refers to functions that provide search results to users visually.

[0665] "Time-saving measures" refer to features that streamline the search process for medical institutions, thereby reducing the time it takes for users to obtain results.

[0666] "Medical history / prescription history" refers to records of medical treatments and medications prescribed to the user in the past.

[0667] "Management means" refers to a function for saving and updating a user's medical history and prescription history as needed.

[0668] "Electronic payment methods" refer to functions that allow users to pay medical expenses online after a medical consultation.

[0669] A "generative AI model" is a technology that uses artificial intelligence to generate prompt messages based on user input and search for appropriate medical institutions.

[0670] A "prompt sentence" is an instruction sentence used by a generative AI model when searching for medical institutions.

[0671] The system for implementing this invention allows users to search for medical institutions and manage their medical history using terminals such as smartphones and computers. The system exchanges data between a server and the user terminal and provides appropriate information according to the user's requests.

[0672] The server generates prompt messages using a generative AI model based on the body parts and symptoms specified by the user, searching for relevant medical institutions. Based on these prompt messages, it retrieves information on appropriate medical institutions from the database and displays it on the user's terminal. This allows the user to quickly find the appropriate medical institution.

[0673] The server also provides functionality for electronic payment after consultations. Users can pay for their medical services online, and the payment information is stored on the server. Furthermore, the server manages the user's medical history and prescription history, allowing users to view and update this information.

[0674] For example, when a user enters "headache," the server generates a prompt message saying, "The user is complaining of a headache. Please list medical institutions that can treat headaches." Based on this prompt message, the AI ​​model searches for appropriate medical institutions and displays the results on the user's terminal. The user can then select a medical institution from the displayed list and make an appointment. After the consultation, the user pays the medical fees using the electronic payment function, and the history is automatically updated.

[0675] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0676] Step 1:

[0677] The user uses a device to input information about body parts and symptoms. The entered information is then sent from the device to the server.

[0678] Step 2:

[0679] The server uses a generative AI model to generate a prompt message based on the user's input information received. Specifically, it creates a prompt message in the format of, "The user is reporting symptoms. Please list medical institutions that can treat these symptoms." This prompt message is then sent to the generative AI model.

[0680] Step 3:

[0681] The generative AI model analyzes the prompt text and searches the database for information on appropriate medical institutions. The search results are returned to the server.

[0682] Step 4:

[0683] The server sends the medical institution information received from the generated AI model to the user's terminal. The user's terminal visually displays the received information to the user. The user can then select a medical institution from the displayed list and make an appointment.

[0684] Step 5:

[0685] After the consultation, the user makes an electronic payment using a terminal. The terminal sends the payment information to the server. The server processes the payment information and completes the user's payment.

[0686] Step 6:

[0687] The server updates the user's medical history and prescription history. The updated information is stored in a database for the user to review later. The user can review and update their history as needed.

[0688] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0689] "Example of form 1"

[0690] One embodiment of the present invention involves a system that combines a user's emotions with an emotion engine. This system searches for an appropriate hospital (doctor) based on the affected area or symptoms specified by the user and displays the results. Furthermore, the emotion engine recognizes the user's emotions and adjusts the search results for hospitals (doctors) based on those emotions. For example, if the user is feeling anxious, the emotion engine uses that information to prioritize displaying hospitals (doctors) that can provide the user with a sense of security.

[0691] "Example of form 2"

[0692] Another embodiment of the present invention is a system that adjusts the display method of medical history and prescription history based on the user's emotions. This system manages the medical history and prescription history for each user, allowing users to check their own medical history and prescription history and update it as needed. Furthermore, the emotion engine recognizes the user's emotions and adjusts the display method of the medical history and prescription history based on those emotions. For example, if the user is confused, the emotion engine uses that information to display the medical history and prescription history in a simpler and easier-to-understand format.

[0693] "Example of form 3"

[0694] Another embodiment of the present invention is a system that adjusts the display method of medical history and prescription history based on the user's emotions. This system manages the medical history and prescription history for each user, allowing users to check their own medical history and prescription history and update it as needed. Furthermore, the emotion engine recognizes the user's emotions and adjusts the display method of the medical history and prescription history based on those emotions. For example, if the user is confused, the emotion engine uses that information to display the medical history and prescription history in a simpler and easier-to-understand format.

[0695] The following describes the processing flow for each example of the form.

[0696] "Example of form 1"

[0697] Step 1: The user accesses the system and enters their symptoms and affected areas.

[0698] Step 2: The system searches for a suitable hospital (doctor) based on the entered information.

[0699] Step 3: Simultaneously, the emotion engine recognizes the user's emotions.

[0700] Step 4: The emotion engine adjusts search results based on the emotions it recognizes, prioritizing hospitals (doctors) that can provide the user with a sense of security.

[0701] "Example of form 2"

[0702] Step 1: The user accesses the system and checks their medical and prescription history.

[0703] Step 2: The emotion engine recognizes the user's emotions.

[0704] Step 3: Based on the emotions it recognizes, the emotion engine adjusts how the medical history and prescription history are displayed, presenting them in a simpler and easier-to-understand format if the user is confused.

[0705] (Example 1)

[0706] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0707] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, the inability to select a medical institution that takes the user's emotional state into consideration means that user anxiety cannot be alleviated. Additionally, there is a need to effectively manage and update users' health information as needed.

[0708] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0709] In this invention, the server includes means for searching for appropriate medical institutions based on body parts or symptoms specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the search results based on those emotions; and means for managing each user's health information. As a result, users can quickly find medical institutions suitable for their symptoms, make choices that take their emotions into consideration, and easily manage and update their health information.

[0710] A "user" is an individual who uses the system to input information about their health condition and search for appropriate medical institutions.

[0711] "Body parts and symptoms" refers to specific information about one's own health status that the user inputs into the system.

[0712] A "medical institution" refers to a facility or specialist that provides medical care and treatment tailored to the user's health condition.

[0713] "Search results" refer to a list of appropriate medical institutions presented by the system based on the information entered by the user.

[0714] "Analyzing emotions" is the process of evaluating a user's emotional state based on their input information and past data.

[0715] "Health information" refers to personal information about a user's health, such as their medical history and prescription history.

[0716] "Managing" refers to the process of organizing users' health information and updating or verifying it as needed.

[0717] As an embodiment of this invention, the following system is constructed.

[0718] The server runs a program that searches for appropriate medical facilities based on the body parts and symptoms specified by the user. This program includes a user interface, a database search function, and a sentiment analysis engine. The user interface is implemented as a web browser or mobile application. When the user enters symptoms into the interface, the device sends that information to the server.

[0719] The server searches the database based on the information it receives. This database contains information about medical institutions, and a relational database management system such as MySQL or PostgreSQL is used. The server uses SQL queries to search for medical institutions that are suitable for the user's symptoms.

[0720] Furthermore, the server uses a sentiment analysis engine to recognize the user's emotions. This sentiment analysis engine analyzes the user's emotions using natural language processing techniques. Specifically, it might use Python libraries such as NLTK or Transformers. Once the sentiment engine recognizes the user's emotions, the server adjusts the search results based on those emotions.

[0721] As a concrete example, consider a case where a user enters "headache" and "anxiety." The server searches its database for medical institutions specializing in headaches and then uses an emotion engine to prioritize displaying medical institutions that can alleviate the user's anxiety.

[0722] An example of a prompt message to input into a generative AI model might be, "The user entered a headache and is feeling anxious. Please search for an appropriate medical institution." Based on this prompt message, the generative AI model will generate appropriate search results.

[0723] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0724] Step 1:

[0725] The user enters information about their body parts and symptoms into the interface. The entered information is sent to the terminal in text format. Specifically, when the user enters "I have a headache," the terminal prepares to send this information to the server.

[0726] Step 2:

[0727] The terminal sends the information entered by the user to the server as an HTTP request. The input data is packaged in JSON format and sent to the server. This allows the server to receive the user's symptom information.

[0728] Step 3:

[0729] The server searches the database based on the received symptom information. Specifically, it generates an SQL query to search for medical institution information within the database. The input is the user's symptom information, and the output is a list of relevant medical institutions.

[0730] Step 4:

[0731] The server analyzes the user's emotions using an emotion analysis engine. The input consists of the user's symptom information and past history, and the emotions are evaluated using natural language processing techniques. The output is the user's emotional state.

[0732] Step 5:

[0733] The server adjusts search results based on the results of sentiment analysis. The input is a list of medical institutions and the user's emotional state, and the output is a list of adjusted medical institutions. Specifically, if the user is feeling anxious, the server prioritizes selecting medical institutions that can provide a sense of security.

[0734] Step 6:

[0735] The server sends the adjusted search results to the terminal. The output is a list of adjusted medical institutions, and the terminal receives this information.

[0736] Step 7:

[0737] The terminal displays search results received from the server to the user. The user can review the displayed information on medical institutions and select an appropriate one. Specifically, by selecting a "relaxing hospital," the user can receive medical services with peace of mind.

[0738] (Application Example 1)

[0739] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0740] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is suitable for their symptoms. Furthermore, there is a lack of services that consider the user's feelings when selecting a medical institution, and integrated services for appointment scheduling and electronic payment. Therefore, there is a need to alleviate user anxiety and improve convenience.

[0741] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0742] This invention includes a server that searches for an appropriate medical institution based on the affected area or symptoms specified by the user and displays the results; a server that recognizes the user's emotions and adjusts the search results for medical institutions based on those emotions; and a server that provides integrated appointment scheduling and electronic payment. This allows the user to quickly find a medical institution suitable for their symptoms, make a reassuring choice based on their emotions, and handle everything from appointment scheduling to payment in a consistent manner.

[0743] A "user" is an individual who uses the system to search for a medical institution suitable for their symptoms, and to make appointments and electronic payments.

[0744] "Affected area or symptoms" refers to the physical ailments or medical conditions that users specify when searching for a medical institution.

[0745] A "medical institution" refers to facilities such as hospitals and clinics that provide appropriate medical care and treatment for a user's symptoms.

[0746] "Search results" refer to a list of medical institutions presented by the system based on the conditions specified by the user.

[0747] "Means of recognizing emotions" refers to technology that analyzes the user's emotional state and adjusts the search results for medical institutions based on that information.

[0748] "Appointment booking" is the process of booking an appointment in advance at a medical institution of the user's choice.

[0749] "Electronic payment" refers to a method of paying for medical consultations and treatments online.

[0750] A description of the embodiment for carrying out the invention will be provided.

[0751] The system that realizes this invention mainly consists of a server and a user terminal. The server searches for an appropriate medical institution based on the affected area and symptoms specified by the user and displays the results on the user terminal. The user terminal is a mobile information terminal such as a smartphone or tablet and provides an interface for the user to input symptoms.

[0752] The server analyzes the user's emotions using an emotion recognition API (e.g., Microsoft Azure's Emotion API). When the user enters symptoms, the server recognizes the user's emotions through this API and adjusts the search results for medical institutions based on those emotions. For example, if the user is feeling anxious, the server will prioritize displaying medical institutions that can provide a sense of security.

[0753] Furthermore, the server provides a service that integrates appointment scheduling and electronic payment. Users can book appointments at their chosen medical institutions and pay for consultations and treatments online. This process improves user convenience and reduces anxiety.

[0754] For example, if a user enters "headache" and is feeling anxious, the server uses an emotion recognition API to analyze that emotion and prioritizes displaying medical facilities that provide a relaxing environment. An example of a prompt to input into the generative AI model would be, "If the user is feeling anxious, what kind of medical facilities should be prioritized?"

[0755] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0756] Step 1:

[0757] The user uses a terminal to input information about their affected area and symptoms on the interface. The entered data is sent to the server. The input data is text information about the user's symptoms.

[0758] Step 2:

[0759] The server searches a database of medical institutions based on the received symptom data. Using a search algorithm, it generates a list of medical institutions suitable for the symptoms. The output is a list of medical institutions as search results.

[0760] Step 3:

[0761] The server analyzes the user's emotions using an emotion recognition API. It estimates the emotional state using user input data and image data acquired from the device's camera. The output is data indicating the user's emotional state.

[0762] Step 4:

[0763] The server adjusts the search results for healthcare facilities based on emotional state data. For example, if an emotional state indicating anxiety is detected, healthcare facilities that can provide a sense of security will be prioritized and placed higher in the list. The output is a list of the adjusted healthcare facilities.

[0764] Step 5:

[0765] The server sends a list of coordinated medical institutions to the user's terminal. The user reviews the list on their terminal and selects the desired medical institution. Information about the selected medical institution is then displayed to the user.

[0766] Step 6:

[0767] After the user selects their preferred medical institution, they make an appointment using their terminal. The server sends the appointment information to the medical institution and confirms the appointment. The output is appointment confirmation information.

[0768] Step 7:

[0769] The user makes an electronic payment using a terminal. The server processes the payment through the payment system and notifies the user of the payment completion. The output is the payment completion confirmation information.

[0770] (Example 2)

[0771] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0772] In modern medical information management systems, it is crucial for users to efficiently manage their health information and quickly find necessary medical facilities. However, conventional systems often fail to consider how to display information in a way that resonates with the user's emotions, making it difficult to understand the information. Furthermore, the cumbersome process of inputting and updating information makes it difficult for users to properly manage their own health information.

[0773] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0774] In this invention, the server includes means for searching for appropriate medical institutions based on body parts or symptoms specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the display format of health information based on those emotions; and means for the user to input health information and transmit it to the server. This allows the user to efficiently manage their own health information, and the display of information according to their emotions makes it easier to understand the information.

[0775] A "user" refers to an individual who uses the system to manage their own health information and search for medical institutions.

[0776] "Body part" refers to the specific part of the body where the user experiences symptoms.

[0777] "Symptoms" refer to specific conditions or signs that a user perceives as abnormal in their health.

[0778] "Medical institutions" refer to facilities such as hospitals and clinics that users visit to receive medical treatment or diagnosis.

[0779] "Searching" refers to the process of finding a suitable medical institution based on the criteria specified by the user.

[0780] "Health information" refers to medical-related information such as the user's medical history, prescription history, and diagnosis results.

[0781] "Emotions" refer to the user's psychological state and are analyzed to adjust the way information is displayed.

[0782] "Display format" refers to the layout and style used when presenting information to the user.

[0783] "Input" refers to the act of a user providing information to a system.

[0784] A "server" refers to a computer system that processes user requests and manages information.

[0785] A "database" refers to an information system used to systematically store and manage users' health information.

[0786] A description of embodiments for carrying out this invention will be given.

[0787] This system aims to allow users to efficiently manage their health information and quickly find necessary medical facilities. Users input their health information using a dedicated application or web browser and send it to the server. The terminal sends the information entered by the user to the server as an HTTP request. In this case, the data is typically sent in JSON format.

[0788] The server analyzes the received information and stores it in a database such as MySQL or PostgreSQL. The data is stored linked to the user ID, making it easy to search later. When a user wants to view their health information, they send a request from their device, and the server retrieves the relevant information from the database.

[0789] Furthermore, the server uses sentiment analysis APIs to analyze the user's emotions. For example, it can utilize Microsoft Azure's sentiment analysis API or Google Cloud's natural language API. Based on the user's emotions, the server adjusts the display format of health information and sends it to the device. This makes the information easier for the user to understand.

[0790] As a concrete example, consider a case where a user is prescribed a new medication. The user opens the application and clicks the "Add New Medication" button. The device sends the name and dosage of the medication entered by the user to the server. The server saves this information to the database and returns a message to the device confirming that the information has been saved. Later, if the user wants to check their prescription history, they click the "View Prescription History" button in the application. The server retrieves the information from the database, organizes it according to the user's mood, and sends it to the device. The device displays the information to the user, allowing them to check their prescription history.

[0791] An example of a prompt to input into a generative AI model is, "How can I display the medical history based on the user's emotions?" This prompt allows the AI ​​model to suggest ways to display information that are appropriate to the user's feelings.

[0792] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0793] Step 1:

[0794] The user enters their health information. The user enters health information, such as medical history and prescription history, using a dedicated application or web browser. The entered data is converted to JSON format by the terminal. Specifically, the user clicks a button labeled "Add New Medication" and enters the name and dosage of the medication.

[0795] Step 2:

[0796] The terminal sends input data to the server. The terminal sends the JSON-formatted data entered by the user to the server as an HTTP request. The input is the user's health information, and the output is the transmission of data to the server. Specifically, the terminal sends data to the server when the send button is pressed.

[0797] Step 3:

[0798] The server saves the data to a database. The server parses the received JSON data and saves it to a database such as MySQL or PostgreSQL. The input is health information received from the terminal, and the output is a message indicating that the data has been successfully saved to the database. Specifically, the server stores the data associated with the user ID.

[0799] Step 4:

[0800] The user sends a request to view their health information. The user sends a request from their device to view their health information through an application or web browser. The input is the user's viewing request, and the output is the request sent to the server. Specifically, the user clicks a button labeled "View Prescription History".

[0801] Step 5:

[0802] The server retrieves information from the database. The server receives a request from the user and retrieves the corresponding health information from the database. The input is the user's request, and the output is the retrieved health information. Specifically, the server executes a database query to retrieve the information.

[0803] Step 6:

[0804] The emotion engine analyzes the user's emotions. The server uses an emotion analysis API to analyze the user's emotions. The input is the user's past behavior data and input data, and the output is the user's emotional state. Specifically, the server sends data to the emotion analysis API and receives the analysis results.

[0805] Step 7:

[0806] The server sends information to the terminal in a format appropriate to the user's emotions. Based on the analysis results of the emotion engine, the server adjusts the display format of the health information and sends it to the terminal. The input is the acquired health information and emotion analysis results, and the output is the adjusted information. Specifically, the server summarizes and sends the information concisely.

[0807] Step 8:

[0808] The terminal displays information to the user. The terminal displays information received from the server to the user. The input is the processed information from the server, and the output is the display of information to the user. Specifically, the terminal displays information on the screen, and the user checks their own health information.

[0809] (Application Example 2)

[0810] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0811] In today's healthcare environment, users are expected to manage their health information appropriately and smoothly select healthcare providers and pay medical expenses. However, it is a difficult challenge for users to properly understand and utilize information in accordance with their emotional state. In particular, referring to past health information and making appropriate decisions when paying medical expenses can be burdensome for users.

[0812] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0813] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing health information for each user; means for recognizing the user's emotions and adjusting the way health information is displayed based on those emotions; and means for referring to past health information when paying medical expenses and assisting with payment. As a result, users can appropriately understand information according to their emotional state and smoothly select a medical institution and pay medical expenses.

[0814] A "user" is an individual who uses the system to manage their own health information, select medical institutions, and pay for medical expenses.

[0815] A "medical institution" refers to facilities such as hospitals and clinics that users visit to improve their health or receive diagnoses.

[0816] "Health information" is a general term for medical-related data such as a user's medical history, prescription history, and diagnosis results.

[0817] "Emotions" refer to the user's psychological state, which the system recognizes and uses to adjust how information is displayed.

[0818] "Payment" refers to a monetary transaction that a user makes for medical services.

[0819] A "server" is a computer system that manages users' health information and performs tasks such as searching for medical facilities and recognizing emotions.

[0820] A description of the embodiment for carrying out the invention will be provided.

[0821] The system that realizes this invention consists of a user's smartphone or tablet and a server located in the cloud. The server manages the user's health information and runs programs for searching for medical institutions and performing emotion recognition. Specifically, the server stores the user's health information using a database management system (e.g., Firebase) and analyzes the user's emotions using an emotion recognition engine (e.g., Affectiva SDK).

[0822] When a user searches for a medical facility using their device, the server searches for an appropriate facility based on the affected area or symptoms specified by the user and displays the results on the device. Furthermore, the server analyzes the user's emotions through the camera and microphone using an emotion recognition engine and adjusts how health information is displayed based on those emotions. For example, if the user is feeling anxious, the server displays information concisely and supports the payment process.

[0823] As a concrete example, when a user is paying at a hospital, they launch the app, and the camera reads their facial expression. If the emotion is recognized as "anxiety," the server briefly displays past health information and suggests payment methods. In this case, a generative AI model can be used to display information and suggest payment methods that are appropriate for the user.

[0824] An example of a prompt would be, "Please tell me how to analyze the user's emotions, concisely display past health information, and support payment." Using this prompt, the generative AI model can provide the user with the most relevant information.

[0825] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0826] Step 1:

[0827] The user launches the application on their device and begins searching for a medical institution. As input, the user specifies the affected area and symptoms. The device then sends this information to the server.

[0828] Step 2:

[0829] The server searches its database for appropriate medical institutions based on the received information about the affected area and symptoms. It uses a database management system (e.g., Firebase) to extract information about relevant medical institutions. The server then generates search results as output and sends them to the terminal.

[0830] Step 3:

[0831] The terminal displays the search results for medical institutions received from the server to the user. The user reviews the displayed information and selects a medical institution as needed.

[0832] Step 4:

[0833] After the user selects a medical institution, the device uses its camera and microphone to collect the user's emotions. It acquires the user's facial expressions and voice data as input.

[0834] Step 5:

[0835] The server uses an emotion recognition engine (e.g., Affectiva SDK) to analyze collected facial and voice data and recognize the user's emotions. It then generates and sends the recognized emotion information as output to the terminal.

[0836] Step 6:

[0837] The device adjusts how health information is displayed based on emotional information received from the server. For example, if the user is feeling anxious, the information will be displayed more concisely.

[0838] Step 7:

[0839] When a user pays for medical expenses, the terminal refers to past health information and suggests a payment method. The server uses a generative AI model to generate a payment method suitable for the user. The prompt message used is, "Please tell me how to analyze the user's emotions, concisely display past health information, and support payment."

[0840] Step 8:

[0841] The terminal displays the generated payment method to the user, and the user pays the medical expenses using the suggested method.

[0842] (Example 3)

[0843] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0844] In modern medical information systems, it is difficult for users to quickly and accurately find a medical institution suitable for their symptoms. Furthermore, the display of information is often not tailored to the user's emotional state, making it difficult to understand. Additionally, managing users' medical and prescription histories is cumbersome, and there are challenges in easily accessing past treatment records.

[0845] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0846] In this invention, the server includes means for searching for an appropriate medical institution based on a body part or symptom specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the way information is displayed based on those emotions; and means for saving and making the user's past medical history accessible. As a result, the user can quickly find an appropriate medical institution, understand information more easily through emotion-based display, and easily access their past medical history.

[0847] A "user" refers to an individual who uses the system to search for medical information and manage their medical history.

[0848] "Body part" refers to a specific area of ​​the body where the user experiences symptoms.

[0849] "Symptoms" refer to physical or mental abnormalities experienced by the user.

[0850] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[0851] "Searching" refers to the act of finding relevant information from a database based on conditions specified by the user.

[0852] "Display" refers to the act of making search results and information visually accessible to users.

[0853] "Emotions" refer to the user's psychological state and are the subject of analysis by the system.

[0854] "Medical history" refers to the records of medical services a user has received in the past.

[0855] "Saving" refers to the act of recording information in a database so that it can be referenced later.

[0856] "Referencing" refers to the act of a user checking saved information.

[0857] To implement this invention, the server, terminal, and user must each fulfill their respective roles. The server uses a database management system to search for medical institutions based on the body parts and symptoms specified by the user. Specifically, the server uses a database management system such as MySQL and executes SQL queries to extract relevant information.

[0858] The server analyzes the user's emotions using emotion recognition software. For example, it uses an emotion recognition API to recognize emotions from text or voice input by the user. Based on this information, the server adjusts how the information is displayed and provides it in a format that is easy for the user to understand.

[0859] The terminal provides an interface for users to input information and view search results from the server. Through the terminal, users can input body parts and symptoms and view the search results.

[0860] For example, if a user enters "headache," the server will display a message such as "Looking for a doctor specializing in headaches" and provide a list of relevant doctors and hospitals. It will also display information about medical institutions the user has visited in the past, their diagnoses, and the medications they have been prescribed.

[0861] An example of a prompt to the generative AI model might be, "Please tell me how to search for doctors related to the affected area specified by the user and display the information based on emotion." Using this prompt, the generative AI model can be asked to specify a particular processing method. The flow of the specific processing in Example 3 will be explained using Figure 21.

[0862] Step 1:

[0863] The user uses a terminal to access the system and enter information about body parts and symptoms. The entered information is sent to the server. For example, the user might type "headache" and press the submit button.

[0864] Step 2:

[0865] The server uses a database management system to search for medical institutions based on the user's input information. The server executes an SQL query to extract information about doctors and hospitals related to "headache" from the database. The input is the user's symptom information, and the output is a list of relevant medical institutions.

[0866] Step 3:

[0867] The server sends the search results to the user's device. The device displays the received information to the user. Specifically, the device displays a "list of headache specialists" on the screen. The input is the search results from the server, and the output is information that the user can visually confirm.

[0868] Step 4:

[0869] The server analyzes the user's emotions using emotion recognition software. The emotion recognition API determines the emotion based on the text and voice data entered by the user. The input is the user's emotion data, and the output is the result of the emotion analysis.

[0870] Step 5:

[0871] The server adjusts how information is displayed based on the analyzed emotions. For example, if the server determines that the user is confused, it converts the information into a simpler, easier-to-understand format and sends it to the terminal. The input is the result of the emotion analysis, and the output is the adjusted information display.

[0872] Step 6:

[0873] The server stores the user's past medical history in a database and makes it accessible as needed. Specifically, the server updates the medical history so that the user can review it later. The input is new medical information, and the output is the updated medical history.

[0874] (Application Example 3)

[0875] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0876] In today's healthcare environment, it is difficult for users to quickly find a medical institution that is appropriate for their symptoms. Furthermore, managing medical history, displaying information in a way that responds to emotions, and choosing payment methods for medical expenses all present significant challenges for users. To address these challenges, a flexible system that meets user needs is necessary.

[0877] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0878] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing each user's medical history; means for analyzing the user's emotions and adjusting the display method of the medical history according to those emotions; and means for suggesting a payment method for medical expenses. As a result, the user can quickly and appropriately select a medical institution, receive information displayed according to their emotions, and choose the optimal payment method.

[0879] A "user" refers to an individual who uses the system to search for medical institutions or manage their medical history.

[0880] "Affected area or symptoms" refers to the body part or health condition that a user specifies when searching for a medical institution.

[0881] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[0882] "Search method" refers to a function that finds appropriate medical institutions based on the conditions specified by the user.

[0883] "Medical history" refers to data that includes a user's past medical records and information about prescribed medications.

[0884] "Means of analyzing emotions" refers to functions that recognize the user's emotional state and adjust the system's operation based on that information.

[0885] "Means for adjusting the display method" refers to a function that changes the way information is presented according to the user's emotions.

[0886] "Means of suggesting payment methods" refers to a function that presents users with the most suitable method for paying medical expenses.

[0887] The system for implementing this invention consists of a user's smartphone or tablet and a server in the cloud. The server searches for appropriate medical institutions based on the affected area or symptoms specified by the user and displays the results on the user's device. A database management system (e.g., Firebase) is used for the search to enable rapid information provision.

[0888] The server also manages the user's medical history and analyzes the user's emotions using an emotion analysis engine (e.g., Microsoft Azure's Emotion Analysis API). This allows the display of the medical history to be adjusted according to the user's emotions. For example, if the user is feeling anxious, the information may be displayed simply to provide reassurance.

[0889] Furthermore, the server has a function to suggest payment methods for the user's medical expenses. It takes into account the user's past payment history and current emotional state to suggest the most suitable payment method.

[0890] As a concrete example, when a user opens the app after a consultation, the sentiment analysis engine detects anxiety from the user's facial expressions and voice. It retrieves past medical history from Firebase and suggests a simple payment method (e.g., one-click payment). An example of a prompt to input into the generating AI model is, "If the user is feeling anxious after a consultation, please refer to their past medical history and suggest the most suitable payment method."

[0891] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0892] Step 1:

[0893] The user uses a device to input information about the affected area and symptoms. The device sends this information to the server. The entered information is stored on the server as data indicating the user's current health status.

[0894] Step 2:

[0895] Based on the received information about the affected area and symptoms, the server uses a database management system (e.g., Firebase) to search for appropriate medical institutions. A list of medical institutions is generated as a search result and sent to the device.

[0896] Step 3:

[0897] The terminal displays a list of medical institutions received from the server to the user. The user selects a desired medical institution from this list. The selected information is sent to the server for the next processing step.

[0898] Step 4:

[0899] The server analyzes the user's emotions using an emotion analysis engine (e.g., Microsoft Azure's Emotion Analysis API) based on the user's selection. It uses the user's voice and facial expression data as input and outputs the emotional state as the analysis result.

[0900] Step 5:

[0901] The server adjusts how the user's medical history is displayed based on the results of sentiment analysis. For example, if the user is feeling anxious, the data is processed to display information in a simpler way before being sent to the device.

[0902] Step 6:

[0903] The server considers the user's past payment history and current emotional state to suggest the most suitable payment method for medical expenses. The suggested payment method is sent to the terminal and displayed to the user.

[0904] Step 7:

[0905] The user reviews and selects a payment method displayed on their device. The selected payment method is sent to the server, and the payment process is initiated.

[0906] (Other examples)

[0907] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[0908] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0909] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0910] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[0911] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0912] [Third Embodiment]

[0913] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0914] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0915] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0916] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0917] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0918] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0919] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0920] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0921] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0922] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0923] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0924] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0925] "Example of form 1"

[0926] The system of the present invention has a function to search for an appropriate hospital (doctor) based on the affected area and symptoms specified by the user. Specifically, when the user enters their affected area and symptoms on the interface, the system searches the database for information on hospitals and doctors and displays the results to the user. This function allows the user to efficiently find a hospital or doctor suitable for their symptoms.

[0927] "Example of form 2"

[0928] Furthermore, the system of the present invention has a function to manage each user's medical history and prescription history. Specifically, the system stores information such as hospitals and doctors the user has visited in the past, diagnoses, and prescribed medications in a database, allowing the user to refer to this information at any time. This function allows users to easily manage their own medical history and prescription history.

[0929] "Example of form 3"

[0930] For example, if a user specifies "headache" as the affected area, the system searches its database for hospital and doctor information and displays headache specialists and hospitals that can treat headaches to the user. It also saves information such as hospitals and doctors the user has visited for headaches in the past, diagnoses, and prescribed medications, allowing the user to access this information at any time.

[0931] The following describes the processing flow for each example of the form.

[0932] "Example of form 1"

[0933] Step 1: The user enters their affected area and symptoms on the system interface. Step 2: The system searches its database for hospital and doctor information and extracts hospitals and doctors suitable for the affected area and symptoms entered by the user.

[0934] Step 3: The system displays the extracted hospital and doctor information to the user.

[0935] "Example of form 2"

[0936] Step 1: The user enters their medical history and prescription history into the system.

[0937] Step 2: The system saves the medical history and prescription history entered by the user to the database.

[0938] Step 3: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[0939] "Example of form 3"

[0940] Step 1: The user enters "headache" as the affected area into the system.

[0941] Step 2: The system searches the database for hospital and doctor information and extracts headache specialists and hospitals that can treat headaches.

[0942] Step 3: The system displays the extracted hospital and doctor information to the user.

[0943] Step 4: The user enters information into the system, such as the hospitals and doctors they have visited in the past for headaches, their diagnoses, and the medications they have been prescribed.

[0944] Step 5: The system saves the information entered by the user to the database.

[0945] Step 6: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[0946] (Example 1)

[0947] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0948] There is a challenge in that it is difficult for users to quickly and accurately find the appropriate medical institution based on their body part and symptoms. Furthermore, there is a need to efficiently manage and update each user's health information as needed.

[0949] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0950] In this invention, the server includes means for searching for an appropriate medical institution based on the body part or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. As a result, users can quickly find an appropriate medical institution and manage and update their health information efficiently.

[0951] A "user" refers to an individual who uses the system to search for appropriate medical institutions based on their own body parts and symptoms.

[0952] "Body parts and symptoms" refers to information related to a user's health condition that they enter when searching for a medical institution.

[0953] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[0954] "Searching" refers to the process of examining information within a database based on conditions specified by the user and finding appropriate results.

[0955] "Display" refers to outputting search results to the device in a format that is easy for the user to understand.

[0956] "Health information" refers to data related to a user's health status, such as their medical history and prescription history.

[0957] "Management" refers to the process of organizing health information and updating or correcting it as needed.

[0958] A "server" refers to a computer system that receives input from users, searches a database, and returns the results.

[0959] A "terminal" refers to a device that a user uses to access a system through an interface.

[0960] As an embodiment of this invention, the following system is constructed.

[0961] The server generates a program that searches for appropriate medical institutions based on the body parts and symptoms specified by the user. This program consists of multiple components, including a user interface, database access, and a search algorithm. Specifically, the server implements the search algorithm using Python and manages medical institution information using a MySQL database.

[0962] The user uses the terminal's interface to input information about their body parts and symptoms. The terminal sends this input to the server. The server searches its database for information on medical institutions based on the received information. The search results are returned to the terminal and displayed to the user.

[0963] For example, if a user enters "stomach ache," the server searches its database for medical institutions specializing in "gastroenterology." The search results might display "local gastroenterology clinics" or "gastrointestinal hospitals in the city."

[0964] An example of a prompt to input into the generating AI model might be: "Create a program that searches for appropriate medical institutions based on the symptoms entered by the user. Use MySQL as the database and implement the search algorithm in Python."

[0965] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0966] Step 1:

[0967] The user accesses the device's interface and enters information about their body parts and symptoms. This entered data is saved on the device in text format. This data serves as foundational information for identifying the user's health problems.

[0968] Step 2:

[0969] The terminal sends the information entered by the user to the server as an HTTP request. This request contains data about the user's symptoms. The server receives this request and prepares to look up the database.

[0970] Step 3:

[0971] The server parses the received user information and queries a MySQL database. The database contains information such as the medical institution's specialty, location, and operating hours. The server uses a search algorithm implemented in Python to identify the medical institution best suited to the user's symptoms. The input is the user's symptom data, and the output is a list of appropriate medical institutions.

[0972] Step 4:

[0973] The server returns the search results to the terminal in JSON format. This result includes the name, address, and contact information of the medical institution. The server then processes the data to convert it into a format that is easy for the user to understand.

[0974] Step 5:

[0975] The device displays the received search results in a user-friendly format. Users can view detailed information about medical institutions on the screen and contact them as needed. The displayed information helps users make quick decisions when selecting a medical institution.

[0976] (Application Example 1)

[0977] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0978] In modern society, it is crucial for users to quickly and accurately find medical institutions that are appropriate for their symptoms. However, traditional methods present challenges, such as time-consuming information searches and difficulty for users to select the right medical institution. Furthermore, the lack of efficient means to manage and update users' health information as needed can lead to a decline in the quality of medical services.

[0979] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0980] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. This enables users to quickly find an appropriate medical institution and allows for efficient management and updating of health information.

[0981] A "user" is an individual who uses the system to search for medical institutions based on their own symptoms.

[0982] "Affected area or symptoms" refers to the physical ailments or medical conditions that users enter when searching for medical institutions.

[0983] A "medical institution" refers to a facility that provides medical services, such as a hospital or clinic.

[0984] "Searching" is the act of finding appropriate information from a database based on conditions specified by the user.

[0985] "Health information" refers to a user's medical history, prescription history, and other personal information related to medical care.

[0986] A "smart device" refers to a portable electronic device with internet connectivity, such as a smartphone or tablet.

[0987] "Real-time" refers to information being processed and provided to the user immediately.

[0988] "Expert advice" refers to advice provided to users by professionals with medical knowledge.

[0989] The invention will now be described in terms of embodiments for carrying out the invention. This invention is a system in which a user inputs their symptoms using a smart device and searches for an appropriate medical institution. The system consists of a server, a user terminal, and a database.

[0990] The server searches for medical institution information in its database based on the affected area and symptoms specified by the user, and displays the results on the user's terminal. The server is built using Python and Flask, and uses SQLite for its database. The server receives user input and generates search results in real time.

[0991] The user terminal is a smart device such as a smartphone or tablet, and provides an interface for the user to input symptoms. The user terminal displays the search results received from the server and provides the information in a format that the user can easily understand.

[0992] For example, when a user enters "headache," the server searches the database and suggests nearby neurology clinics. This allows the user to quickly find an appropriate medical facility.

[0993] By using generative AI models, it is also possible to provide expert advice based on the user's symptoms. An example of a prompt message would be: "Based on the symptoms entered by the user, please suggest the most suitable medical institution. Example: For headaches, suggest a neurology hospital."

[0994] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0995] Step 1:

[0996] The user launches the application on their smart device and accesses the symptom input screen. The user enters their affected area and symptoms in text format. The entered data is sent from the user's device to the server.

[0997] Step 2:

[0998] The server analyzes the symptom data received from the user. This analysis uses natural language processing techniques to extract keywords from the input text. Based on the extracted keywords, the server searches for medical institution information in the database.

[0999] Step 3:

[1000] The server generates the results of a database search. The search results include a list of medical institutions suitable for the user's symptoms. The server sends the search results to the user's terminal.

[1001] Step 4:

[1002] The user terminal displays the search results received from the server. The display is in a format that is easy for the user to understand. The user can select the appropriate medical institution from the displayed list.

[1003] Step 5:

[1004] The server uses a generative AI model to generate expert advice based on the user's symptoms. Symptom data is input into the AI ​​model using prompts to obtain appropriate advice. The resulting advice is then sent to the user's terminal.

[1005] Step 6:

[1006] The user terminal displays expert advice received from the server. Users can use this advice to decide on a healthcare provider and their next course of action.

[1007] (Example 2)

[1008] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1009] In modern healthcare, it is crucial for users to efficiently manage their health information and quickly find appropriate medical facilities. However, traditional systems have problems such as users not being able to easily access past health information and the time it takes to search for medical facilities. Furthermore, there were challenges in ensuring the security of health information and obtaining appropriate advice based on that information.

[1010] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1011] In this invention, the server includes means for searching for an appropriate medical institution based on symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing each user's health information. This enables users to efficiently manage their own health information and quickly search for an appropriate medical institution.

[1012] A "user" refers to an individual who uses the system to manage their own health information and search for medical institutions.

[1013] "Symptoms" refers to changes in health conditions or physical state that users specify when searching for medical institutions.

[1014] "Medical institutions" refer to facilities such as hospitals and clinics where users can receive medical treatment.

[1015] "Search results" refer to information about medical institutions provided by the system based on the conditions specified by the user.

[1016] "Health information" refers to medical-related data such as a user's medical history, prescription history, and diagnosis results.

[1017] A "database" refers to an information management system used to store and manage users' health information.

[1018] "Encryption" refers to a technology that transforms data to protect users' health information and prevent third parties from easily accessing it.

[1019] A "generative AI model" refers to artificial intelligence technology that provides advice and predictions based on a user's health information.

[1020] "Advice" refers to suggestions and recommendations provided by the generative AI model based on the user's health information.

[1021] This system enables users to efficiently manage their health information and quickly find appropriate medical facilities. The following describes embodiments for carrying out the invention.

[1022] The server stores user-entered health information in a database. The database uses a relational database management system such as MySQL. When users enter their past medical history and prescription history via a dedicated terminal or web application, the server receives this information and stores it in the database. The stored data is encrypted using the AES encryption algorithm to ensure security.

[1023] Users can search for and retrieve their own health information from their devices. The server queries the database based on the user's search criteria and retrieves the relevant information. The retrieved data is displayed on the user's device through an interface using React.js. This allows users to intuitively check the information.

[1024] Furthermore, by utilizing generative AI models, it is possible to provide advice based on the user's health information. Users can receive advice from the AI ​​model by entering prompts. For example, by entering a prompt such as, "Generate important information to tell my doctor at my next appointment," the AI ​​model will analyze the user's health information and generate appropriate advice.

[1025] This system allows users to centrally manage their health information and use it to their advantage when receiving medical treatment at a healthcare facility.

[1026] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1027] Step 1:

[1028] Users enter their past medical and prescription history using a dedicated terminal or web application. This information includes hospital names, doctor names, diagnoses, and the names and dosages of prescribed medications. This information is then transmitted to the server via a form.

[1029] Step 2:

[1030] The server receives health information submitted by users and stores it in a database. MySQL is used for the database, managing each user's information as a separate record. During storage, the data is encrypted using the AES encryption algorithm to ensure security. The input is the user's health information, and the output is the encrypted database record.

[1031] Step 3:

[1032] If a user wants to check their past medical history or prescription history, they enter search criteria on their device. For example, they can specify specific conditions such as "diagnosis results from March 2023."

[1033] Step 4:

[1034] The server queries the database based on the user's search criteria and retrieves the relevant information. The retrieved data is displayed on the user's device through an interface using React.js. The input is the user's search criteria, and the output is health information as search results.

[1035] Step 5:

[1036] Users can receive advice based on their past medical history data using a generative AI model. Users input prompts and receive advice from the AI ​​model. For example, a user might input a prompt such as, "Generate important information I should tell my doctor at my next appointment." The server uses the AI ​​model to analyze the user's health information and generate appropriate advice. The input consists of prompts and health information, while the output is the advice from the AI ​​model.

[1037] (Application Example 2)

[1038] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1039] In modern healthcare systems, users are required to efficiently manage their health information and easily understand how to choose healthcare providers, pay medical expenses, and access insurance coverage. However, traditional systems have the problem that this information is scattered, making it difficult for users to quickly obtain the information they need.

[1040] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1041] This invention includes a server that provides means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, means for managing each user's health information, means for managing the payment history and insurance coverage status of medical expenses based on the user's health information, and means for allowing the user to check past medical expense payments and insurance coverage status. As a result, users can centrally manage their own health information and efficiently select medical institutions and manage their medical expenses.

[1042] A "user" is an individual who uses the system to manage their own health information, select medical institutions, and manage their medical expenses.

[1043] "Health information" refers to data that includes information such as the user's medical history, prescription history, diagnosis results, medical expense payment history, and insurance coverage status.

[1044] A "medical institution" refers to facilities such as hospitals and clinics that are searched based on the affected area or symptoms specified by the user.

[1045] "Medical expenses" refer to the costs that users pay for medical consultations and treatments at medical institutions.

[1046] "Insurance coverage status" refers to information indicating the extent to which the user's insurance covers medical expenses.

[1047] "Search functionality" refers to a feature that finds appropriate medical institutions based on conditions specified by the user and displays the results.

[1048] "Management means" refers to a function that stores users' health information in a database and allows for updates and retrieval as needed.

[1049] As an embodiment of this invention, a system is provided that manages users' health information and efficiently manages the selection of medical institutions and medical expenses. The system consists of an application installed on a terminal such as a smartphone and a server that operates on the cloud.

[1050] The server searches for appropriate medical institutions based on the affected area and symptoms specified by the user and displays the results on the terminal. A database management system (e.g., MySQL) is used for the search to quickly retrieve information on medical institutions. Furthermore, the server manages the user's medical expense payment history and insurance coverage status based on the user's health information. This involves retrieving the user's past medical data and insurance information from the database and performing calculations.

[1051] The device will allow users to check their past medical payment history and insurance coverage through the application. A front-end framework (e.g., React Native) will be used to build the user interface and display the information in a visually clear and easy-to-understand manner.

[1052] For example, when a user opens the app and enters "Show me my medical expense payment history for the past 3 months," the server retrieves the relevant information from the database and displays it on the device. An example of a prompt that uses a generative AI model to analyze user input and provide appropriate information is, "Retrieve the user's medical expense payment history for the past 3 months and display it, including insurance coverage status."

[1053] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1054] Step 1:

[1055] The user launches the application using their device and provides input to retrieve specific information. For example, they might enter a prompt such as, "Show me my medical expense payment history for the past three months." The entered prompt is then analyzed by a generative AI model to identify the type of information needed.

[1056] Step 2:

[1057] The terminal sends a request to the server based on the parsed prompt. The request includes the user ID and the type of information requested (e.g., medical expense payment history). The server parses the received request and uses a database management system (e.g., MySQL) to search for the relevant information in the user's health information database.

[1058] Step 3:

[1059] The server calculates medical expense payment history and insurance coverage status based on information retrieved from the database. Past medical data and insurance information are used for the calculations. The calculation results are formatted in a user-friendly format.

[1060] Step 4:

[1061] The server sends the formatted information to the terminal. The terminal then uses a frontend framework (e.g., React Native) to visually display the received information on the user interface. The user can review the displayed information and decide on the next action as needed.

[1062] (Example 3)

[1063] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1064] In the modern healthcare system, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, it is difficult to manage and easily access past diagnoses and prescription histories when needed. This can lead to users missing opportunities to receive appropriate medical care.

[1065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1066] This invention includes a server that searches for and displays appropriate medical institutions based on body parts and symptoms specified by the user, means for reducing the time required to search for medical institutions, and means for managing each user's health history and medication history. As a result, users can quickly find appropriate medical institutions and easily manage and refer to past diagnosis results and prescription history.

[1067] A "user" is an individual who uses the system to search for medical institutions based on their own health status and symptoms, and manages that information.

[1068] "Body part" refers to a specific area of ​​the body where the user experiences symptoms, and is information used as a basis for searching for medical institutions.

[1069] "Symptoms" refer to physical or mental abnormalities or discomforts experienced by the user, and serve as the basis for information used when searching for medical institutions.

[1070] A "medical institution" refers to facilities such as hospitals and clinics that provide medical care to address the user's symptoms.

[1071] "Searching" is the process of finding appropriate medical institutions from a database based on the conditions specified by the user.

[1072] "Health history" refers to information about a user's past diagnoses and treatments, and is data that users use to manage their own health status.

[1073] "Medication history" refers to information about medications a user has been prescribed in the past, and is data that users use to manage their own drug therapy.

[1074] "Management" refers to the process of saving a user's health history and medication history, and making it possible to update and refer to it as needed.

[1075] One embodiment of this invention is to provide a system that allows users to quickly find appropriate medical facilities based on their symptoms and to manage their past health and medication history.

[1076] The server receives information about body parts and symptoms entered by the user through their terminal and searches its database. This database contains information such as the specialty and location of medical institutions, and searches are performed using a database management system such as SQL. The server sends the search results to the user's terminal and displays them in a format that the user can easily understand.

[1077] Users can input information about past diagnoses and prescribed medications through their devices. The server stores this information in a database, making it accessible to users when needed. This allows users to manage their health and stay informed about the information necessary to receive appropriate medical care.

[1078] For example, if a user enters "headache" as a symptom, the server will display information such as "headache specialist clinics" and "neurology hospitals." It will also save information about past visits to "headache specialist clinics," diagnoses of "migraines," and prescriptions for "ibuprofen," allowing the user to refer to this information.

[1079] By utilizing generative AI models, systems can be designed and improved. An example of a prompt message is, "Design a system that searches for information on specialists and hospitals corresponding to the affected area specified by the user, and allows the user to save and refer to past diagnostic results and prescribed medications." The flow of specific processing in Example 3 will be explained using Figure 15.

[1080] Step 1:

[1081] The user inputs symptoms and body parts through the terminal's interface. The entered information is sent from the terminal to the server. For example, if the user inputs "headache," the terminal sends this information to the server in real time.

[1082] Step 2:

[1083] The server searches the database based on the received symptom information. The input is information about "headaches," and the server uses an SQL query to extract information about relevant medical institutions from the database. The output is a list of medical institutions that can treat headaches. Specifically, the server searches for information on "headache specialist clinics" and "neurology hospitals."

[1084] Step 3:

[1085] The server sends the search results to the user's device. The device displays the received information to the user. Specifically, the device displays a list of "headache specialist clinics" and "neurology hospitals" on the screen, allowing the user to select one.

[1086] Step 4:

[1087] The user enters information about past diagnoses and prescribed medications into the terminal. The entered information is sent from the terminal to the server and stored in the database. Specifically, if the user enters information that they were diagnosed with "migraine" and prescribed "ibuprofen," the server saves this information to the database.

[1088] Step 5:

[1089] Users can access their saved health and medication history. The device retrieves information from the server upon user request and displays it on the screen. Specifically, when a user wants to review past diagnostic results, the device retrieves information from the server and displays a history of being diagnosed with "migraine."

[1090] (Application Example 3)

[1091] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[1092] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, the procedures for paying medical expenses after consultations and managing past medical history are also cumbersome. There is a need to solve these problems and provide convenient healthcare services for users.

[1093] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1094] In this invention, the server includes means for searching for an appropriate medical institution based on a body part or symptom specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing each user's medical history and prescription history; means for performing electronic payment after the consultation; and means for generating prompt messages to search for relevant medical institutions using a generative AI model. This makes it possible for users to quickly find an appropriate medical institution, easily make payments after the consultation, and easily manage their past medical history.

[1095] A "user" is an individual who uses the system to search for medical institutions and manage their medical history.

[1096] "Body parts and symptoms" refers to information about a user's health condition that they specify when searching for a medical institution.

[1097] "Medical institutions" refer to hospitals and clinics that can treat the user's symptoms.

[1098] "Search methods" refer to functions that allow users to find appropriate medical institutions based on the information they specify.

[1099] "Display means" refers to functions that provide search results to users visually.

[1100] "Time-saving measures" refer to features that streamline the search process for medical institutions, thereby reducing the time it takes for users to obtain results.

[1101] "Medical history / prescription history" refers to records of medical treatments and medications prescribed to the user in the past.

[1102] "Management means" refers to a function for saving and updating a user's medical history and prescription history as needed.

[1103] "Electronic payment methods" refer to functions that allow users to pay medical expenses online after a medical consultation.

[1104] A "generative AI model" is a technology that uses artificial intelligence to generate prompt messages based on user input and search for appropriate medical institutions.

[1105] A "prompt sentence" is an instruction sentence used by a generative AI model when searching for medical institutions.

[1106] The system for implementing this invention allows users to search for medical institutions and manage their medical history using terminals such as smartphones and computers. The system exchanges data between a server and the user terminal and provides appropriate information according to the user's requests.

[1107] The server generates prompt messages using a generative AI model based on the body parts and symptoms specified by the user, searching for relevant medical institutions. Based on these prompt messages, it retrieves information on appropriate medical institutions from the database and displays it on the user's terminal. This allows the user to quickly find the appropriate medical institution.

[1108] The server also provides functionality for electronic payment after consultations. Users can pay for their medical services online, and the payment information is stored on the server. Furthermore, the server manages the user's medical history and prescription history, allowing users to view and update this information.

[1109] For example, when a user enters "headache," the server generates a prompt message saying, "The user is complaining of a headache. Please list medical institutions that can treat headaches." Based on this prompt message, the AI ​​model searches for appropriate medical institutions and displays the results on the user's terminal. The user can then select a medical institution from the displayed list and make an appointment. After the consultation, the user pays the medical fees using the electronic payment function, and the history is automatically updated.

[1110] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[1111] Step 1:

[1112] The user uses a device to input information about body parts and symptoms. The entered information is then sent from the device to the server.

[1113] Step 2:

[1114] The server uses a generative AI model to generate a prompt message based on the user's input information received. Specifically, it creates a prompt message in the format of, "The user is reporting symptoms. Please list medical institutions that can treat these symptoms." This prompt message is then sent to the generative AI model.

[1115] Step 3:

[1116] The generative AI model analyzes the prompt text and searches the database for information on appropriate medical institutions. The search results are returned to the server.

[1117] Step 4:

[1118] The server sends the medical institution information received from the generated AI model to the user's terminal. The user's terminal visually displays the received information to the user. The user can then select a medical institution from the displayed list and make an appointment.

[1119] Step 5:

[1120] After the consultation, the user makes an electronic payment using a terminal. The terminal sends the payment information to the server. The server processes the payment information and completes the user's payment.

[1121] Step 6:

[1122] The server updates the user's medical history and prescription history. The updated information is stored in a database for the user to review later. The user can review and update their history as needed.

[1123] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1124] "Example of form 1"

[1125] One embodiment of the present invention involves a system that combines a user's emotions with an emotion engine. This system searches for an appropriate hospital (doctor) based on the affected area or symptoms specified by the user and displays the results. Furthermore, the emotion engine recognizes the user's emotions and adjusts the search results for hospitals (doctors) based on those emotions. For example, if the user is feeling anxious, the emotion engine uses that information to prioritize displaying hospitals (doctors) that can provide the user with a sense of security.

[1126] "Example of form 2"

[1127] Another embodiment of the present invention is a system that adjusts the display method of medical history and prescription history based on the user's emotions. This system manages the medical history and prescription history for each user, allowing users to check their own medical history and prescription history and update it as needed. Furthermore, the emotion engine recognizes the user's emotions and adjusts the display method of the medical history and prescription history based on those emotions. For example, if the user is confused, the emotion engine uses that information to display the medical history and prescription history in a simpler and easier-to-understand format.

[1128] "Example of form 3"

[1129] Another embodiment of the present invention is a system that adjusts the display method of medical history and prescription history based on the user's emotions. This system manages the medical history and prescription history for each user, allowing users to check their own medical history and prescription history and update it as needed. Furthermore, the emotion engine recognizes the user's emotions and adjusts the display method of the medical history and prescription history based on those emotions. For example, if the user is confused, the emotion engine uses that information to display the medical history and prescription history in a simpler and easier-to-understand format.

[1130] The following describes the processing flow for each example of the form.

[1131] "Example of form 1"

[1132] Step 1: The user accesses the system and enters their symptoms and affected areas.

[1133] Step 2: The system searches for a suitable hospital (doctor) based on the entered information.

[1134] Step 3: Simultaneously, the emotion engine recognizes the user's emotions.

[1135] Step 4: The emotion engine adjusts search results based on the emotions it recognizes, prioritizing hospitals (doctors) that can provide the user with a sense of security.

[1136] "Example of form 2"

[1137] Step 1: The user accesses the system and checks their medical and prescription history.

[1138] Step 2: The emotion engine recognizes the user's emotions.

[1139] Step 3: Based on the emotions it recognizes, the emotion engine adjusts how the medical history and prescription history are displayed, presenting them in a simpler and easier-to-understand format if the user is confused.

[1140] (Example 1)

[1141] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1142] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is appropriate for their symptoms. Furthermore, the inability to select a medical institution that takes the user's emotional state into consideration means that user anxiety cannot be alleviated. Additionally, there is a need to effectively manage and update users' health information as needed.

[1143] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1144] In this invention, the server includes means for searching for appropriate medical institutions based on body parts or symptoms specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the search results based on those emotions; and means for managing each user's health information. As a result, users can quickly find medical institutions suitable for their symptoms, make choices that take their emotions into consideration, and easily manage and update their health information.

[1145] A "user" is an individual who uses the system to input information about their health condition and search for appropriate medical institutions.

[1146] "Body parts and symptoms" refers to specific information about one's own health status that the user inputs into the system.

[1147] A "medical institution" refers to a facility or specialist that provides medical care and treatment tailored to the user's health condition.

[1148] "Search results" refer to a list of appropriate medical institutions presented by the system based on the information entered by the user.

[1149] "Analyzing emotions" is the process of evaluating a user's emotional state based on their input information and past data.

[1150] "Health information" refers to personal information about a user's health, such as their medical history and prescription history.

[1151] "Managing" refers to the process of organizing users' health information and updating or verifying it as needed.

[1152] As an embodiment of this invention, the following system is constructed.

[1153] The server runs a program that searches for appropriate medical facilities based on the body parts and symptoms specified by the user. This program includes a user interface, a database search function, and a sentiment analysis engine. The user interface is implemented as a web browser or mobile application. When the user enters symptoms into the interface, the device sends that information to the server.

[1154] The server searches the database based on the information it receives. This database contains information about medical institutions, and a relational database management system such as MySQL or PostgreSQL is used. The server uses SQL queries to search for medical institutions that are suitable for the user's symptoms.

[1155] Furthermore, the server uses a sentiment analysis engine to recognize the user's emotions. This sentiment analysis engine analyzes the user's emotions using natural language processing techniques. Specifically, it might use Python libraries such as NLTK or Transformers. Once the sentiment engine recognizes the user's emotions, the server adjusts the search results based on those emotions.

[1156] As a concrete example, consider a case where a user enters "headache" and "anxiety." The server searches its database for medical institutions specializing in headaches and then uses an emotion engine to prioritize displaying medical institutions that can alleviate the user's anxiety.

[1157] An example of a prompt message to input into a generative AI model might be, "The user entered a headache and is feeling anxious. Please search for an appropriate medical institution." Based on this prompt message, the generative AI model will generate appropriate search results.

[1158] The flow of the specific processing in Example 1 will be explained using Figure 17.

[1159] Step 1:

[1160] The user enters information about their body parts and symptoms into the interface. The entered information is sent to the terminal in text format. Specifically, when the user enters "I have a headache," the terminal prepares to send this information to the server.

[1161] Step 2:

[1162] The terminal sends the information entered by the user to the server as an HTTP request. The input data is packaged in JSON format and sent to the server. This allows the server to receive the user's symptom information.

[1163] Step 3:

[1164] The server searches the database based on the received symptom information. Specifically, it generates an SQL query to search for medical institution information within the database. The input is the user's symptom information, and the output is a list of relevant medical institutions.

[1165] Step 4:

[1166] The server analyzes the user's emotions using an emotion analysis engine. The input consists of the user's symptom information and past history, and the emotions are evaluated using natural language processing techniques. The output is the user's emotional state.

[1167] Step 5:

[1168] The server adjusts search results based on the results of sentiment analysis. The input is a list of medical institutions and the user's emotional state, and the output is a list of adjusted medical institutions. Specifically, if the user is feeling anxious, the server prioritizes selecting medical institutions that can provide a sense of security.

[1169] Step 6:

[1170] The server sends the adjusted search results to the terminal. The output is a list of adjusted medical institutions, and the terminal receives this information.

[1171] Step 7:

[1172] The terminal displays search results received from the server to the user. The user can review the displayed information on medical institutions and select an appropriate one. Specifically, by selecting a "relaxing hospital," the user can receive medical services with peace of mind.

[1173] (Application Example 1)

[1174] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1175] In today's healthcare environment, it is difficult for users to quickly and accurately find a medical institution that is suitable for their symptoms. Furthermore, there is a lack of services that consider the user's feelings when selecting a medical institution, and integrated services for appointment scheduling and electronic payment. Therefore, there is a need to alleviate user anxiety and improve convenience.

[1176] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1177] This invention includes a server that searches for an appropriate medical institution based on the affected area or symptoms specified by the user and displays the results; a server that recognizes the user's emotions and adjusts the search results for medical institutions based on those emotions; and a server that provides integrated appointment scheduling and electronic payment. This allows the user to quickly find a medical institution suitable for their symptoms, make a reassuring choice based on their emotions, and handle everything from appointment scheduling to payment in a consistent manner.

[1178] A "user" is an individual who uses the system to search for a medical institution suitable for their symptoms, and to make appointments and electronic payments.

[1179] "Affected area or symptoms" refers to the physical ailments or medical conditions that users specify when searching for a medical institution.

[1180] A "medical institution" refers to facilities such as hospitals and clinics that provide appropriate medical care and treatment for a user's symptoms.

[1181] "Search results" refer to a list of medical institutions presented by the system based on the conditions specified by the user.

[1182] "Means of recognizing emotions" refers to technology that analyzes the user's emotional state and adjusts the search results for medical institutions based on that information.

[1183] "Appointment booking" is the process of booking an appointment in advance at a medical institution of the user's choice.

[1184] "Electronic payment" refers to a method of paying for medical consultations and treatments online.

[1185] A description of the embodiment for carrying out the invention will be provided.

[1186] The system that realizes this invention mainly consists of a server and a user terminal. The server searches for an appropriate medical institution based on the affected area and symptoms specified by the user and displays the results on the user terminal. The user terminal is a mobile information terminal such as a smartphone or tablet and provides an interface for the user to input symptoms.

[1187] The server analyzes the user's emotions using an emotion recognition API (e.g., Microsoft Azure's Emotion API). When the user enters symptoms, the server recognizes the user's emotions through this API and adjusts the search results for medical institutions based on those emotions. For example, if the user is feeling anxious, the server will prioritize displaying medical institutions that can provide a sense of security.

[1188] Furthermore, the server provides a service that integrates appointment scheduling and electronic payment. Users can book appointments at their chosen medical institutions and pay for consultations and treatments online. This process improves user convenience and reduces anxiety.

[1189] For example, if a user enters "headache" and is feeling anxious, the server uses an emotion recognition API to analyze that emotion and prioritizes displaying medical facilities that provide a relaxing environment. An example of a prompt to input into the generative AI model would be, "If the user is feeling anxious, what kind of medical facilities should be prioritized?"

[1190] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[1191] Step 1:

[1192] The user uses a terminal to input information about their affected area and symptoms on the interface. The entered data is sent to the server. The input data is text information about the user's symptoms.

[1193] Step 2:

[1194] The server searches a database of medical institutions based on the received symptom data. Using a search algorithm, it generates a list of medical institutions suitable for the symptoms. The output is a list of medical institutions as search results.

[1195] Step 3:

[1196] The server analyzes the user's emotions using an emotion recognition API. It estimates the emotional state using user input data and image data acquired from the device's camera. The output is data indicating the user's emotional state.

[1197] Step 4:

[1198] The server adjusts the search results for healthcare facilities based on emotional state data. For example, if an emotional state indicating anxiety is detected, healthcare facilities that can provide a sense of security will be prioritized and placed higher in the list. The output is a list of the adjusted healthcare facilities.

[1199] Step 5:

[1200] The server sends a list of coordinated medical institutions to the user's terminal. The user reviews the list on their terminal and selects the desired medical institution. Information about the selected medical institution is then displayed to the user.

[1201] Step 6:

[1202] After the user selects their preferred medical institution, they make an appointment using their terminal. The server sends the appointment information to the medical institution and confirms the appointment. The output is appointment confirmation information.

[1203] Step 7:

[1204] The user makes an electronic payment using a terminal. The server processes the payment through the payment system and notifies the user of the payment completion. The output is the payment completion confirmation information.

[1205] (Example 2)

[1206] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1207] In modern medical information management systems, it is crucial for users to efficiently manage their health information and quickly find necessary medical facilities. However, conventional systems often fail to consider how to display information in a way that resonates with the user's emotions, making it difficult to understand the information. Furthermore, the cumbersome process of inputting and updating information makes it difficult for users to properly manage their own health information.

[1208] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1209] In this invention, the server includes means for searching for appropriate medical institutions based on body parts or symptoms specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the display format of health information based on those emotions; and means for the user to input health information and transmit it to the server. This allows the user to efficiently manage their own health information, and the display of information according to their emotions makes it easier to understand the information.

[1210] A "user" refers to an individual who uses the system to manage their own health information and search for medical institutions.

[1211] "Body part" refers to the specific part of the body where the user experiences symptoms.

[1212] "Symptoms" refer to specific conditions or signs that a user perceives as abnormal in their health.

[1213] "Medical institutions" refer to facilities such as hospitals and clinics that users visit to receive medical treatment or diagnosis.

[1214] "Searching" refers to the process of finding a suitable medical institution based on the criteria specified by the user.

[1215] "Health information" refers to medical-related information such as the user's medical history, prescription history, and diagnosis results.

[1216] "Emotions" refer to the user's psychological state and are analyzed to adjust the way information is displayed.

[1217] "Display format" refers to the layout and style used when presenting information to the user.

[1218] "Input" refers to the act of a user providing information to a system.

[1219] A "server" refers to a computer system that processes user requests and manages information.

[1220] A "database" refers to an information system used to systematically store and manage users' health information.

[1221] A description of embodiments for carrying out this invention will be given.

[1222] This system aims to allow users to efficiently manage their health information and quickly find necessary medical facilities. Users input their health information using a dedicated application or web browser and send it to the server. The terminal sends the information entered by the user to the server as an HTTP request. In this case, the data is typically sent in JSON format.

[1223] The server analyzes the received information and stores it in a database such as MySQL or PostgreSQL. The data is stored linked to the user ID, making it easy to search later. When a user wants to view their health information, they send a request from their device, and the server retrieves the relevant information from the database.

[1224] Furthermore, the server uses sentiment analysis APIs to analyze the user's emotions. For example, it can utilize Microsoft Azure's sentiment analysis API or Google Cloud's natural language API. Based on the user's emotions, the server adjusts the display format of health information and sends it to the device. This makes the information easier for the user to understand.

[1225] As a concrete example, consider a case where a user is prescribed a new medication. The user opens the application and clicks the "Add New Medication" button. The device sends the name and dosage of the medication entered by the user to the server. The server saves this information to the database and returns a message to the device confirming that the information has been saved. Later, if the user wants to check their prescription history, they click the "View Prescription History" button in the application. The server retrieves the information from the database, organizes it according to the user's mood, and sends it to the device. The device displays the information to the user, allowing them to check their prescription history.

[1226] An example of a prompt to input into a generative AI model is, "How can I display the medical history based on the user's emotions?" This prompt allows the AI ​​model to suggest ways to display information that are appropriate to the user's feelings.

[1227] The flow of the specific processing in Example 2 will be explained using Figure 19.

[1228] Step 1:

[1229] The user enters their health information. The user enters health information, such as medical history and prescription history, using a dedicated application or web browser. The entered data is converted to JSON format by the terminal. Specifically, the user clicks a button labeled "Add New Medication" and enters the name and dosage of the medication.

[1230] Step 2:

[1231] The terminal sends input data to the server. The terminal sends the JSON-formatted data entered by the user to the server as an HTTP request. The input is the user's health information, and the output is the transmission of data to the server. Specifically, the terminal sends data to the server when the send button is pressed.

[1232] Step 3:

[1233] The server saves the data to a database. The server parses the received JSON data and saves it to a database such as MySQL or PostgreSQL. The input is health information received from the terminal, and the output is a message indicating that the data has been successfully saved to the database. Specifically, the server stores the data associated with the user ID.

[1234] Step 4:

[1235] The user sends a request to view their health information. The user sends a request from their device to view their health information through an application or web browser. The input is the user's viewing request, and the output is the request sent to the server. Specifically, the user clicks a button labeled "View Prescription History".

[1236] Step 5:

[1237] The server retrieves information from the database. The server receives a request from the user and retrieves the corresponding health information from the database. The input is the user's request, and the output is the retrieved health information. Specifically, the server executes a database query to retrieve the information.

[1238] Step 6:

[1239] The emotion engine analyzes the user's emotions. The server uses an emotion analysis API to analyze the user's emotions. The input is the user's past behavior data and input data, and the output is the user's emotional state. Specifically, the server sends data to the emotion analysis API and receives the analysis results.

[1240] Step 7:

[1241] The server sends information to the terminal in a format appropriate to the user's emotions. Based on the analysis results of the emotion engine, the server adjusts the display format of the health information and sends it to the terminal. The input is the acquired health information and emotion analysis results, and the output is the adjusted information. Specifically, the server summarizes and sends the information concisely.

[1242] Step 8:

[1243] The terminal displays information to the user. The terminal displays information received from the server to the user. The input is the processed information from the server, and the output is the display of information to the user. Specifically, the terminal displays information on the screen, and the user checks their own health information.

[1244] (Application Example 2)

[1245] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1246] In today's healthcare environment, users are expected to manage their health information appropriately and smoothly select healthcare providers and pay medical expenses. However, it is a difficult challenge for users to properly understand and utilize information in accordance with their emotional state. In particular, referring to past health information and making appropriate decisions when paying medical expenses can be burdensome for users.

[1247] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1248] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing health information for each user; means for recognizing the user's emotions and adjusting the way health information is displayed based on those emotions; and means for referring to past health information when paying medical expenses and assisting with payment. As a result, users can appropriately understand information according to their emotional state and smoothly select a medical institution and pay medical expenses.

[1249] A "user" is an individual who uses the system to manage their own health information, select medical institutions, and pay for medical expenses.

[1250] A "medical institution" refers to facilities such as hospitals and clinics that users visit to improve their health or receive diagnoses.

[1251] "Health information" is a general term for medical-related data such as a user's medical history, prescription history, and diagnosis results.

[1252] "Emotions" refer to the user's psychological state, which the system recognizes and uses to adjust how information is displayed.

[1253] "Payment" refers to a monetary transaction that a user makes for medical services.

[1254] A "server" is a computer system that manages users' health information and performs tasks such as searching for medical facilities and recognizing emotions.

[1255] A description of the embodiment for carrying out the invention will be provided.

[1256] The system that realizes this invention consists of a user's smartphone or tablet and a server located in the cloud. The server manages the user's health information and runs programs for searching for medical institutions and performing emotion recognition. Specifically, the server stores the user's health information using a database management system (e.g., Firebase) and analyzes the user's emotions using an emotion recognition engine (e.g., Affectiva SDK).

[1257] When a user searches for a medical facility using their device, the server searches for an appropriate facility based on the affected area or symptoms specified by the user and displays the results on the device. Furthermore, the server analyzes the user's emotions through the camera and microphone using an emotion recognition engine and adjusts how health information is displayed based on those emotions. For example, if the user is feeling anxious, the server displays information concisely and supports the payment process.

[1258] As a concrete example, when a user is paying at a hospital, they launch the app, and the camera reads their facial expression. If the emotion is recognized as "anxiety," the server briefly displays past health information and suggests payment methods. In this case, a generative AI model can be used to display information and suggest payment methods that are appropriate for the user.

[1259] An example of a prompt would be, "Please tell me how to analyze the user's emotions, concisely display past health information, and support payment." Using this prompt, the generative AI model can provide the user with the most relevant information.

[1260] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[1261] Step 1:

[1262] The user launches the application on their device and begins searching for a medical institution. As input, the user specifies the affected area and symptoms. The device then sends this information to the server.

[1263] Step 2:

[1264] The server searches its database for appropriate medical institutions based on the received information about the affected area and symptoms. It uses a database management system (e.g., Firebase) to extract information about relevant medical institutions. The server then generates search results as output and sends them to the terminal.

[1265] Step 3:

[1266] The terminal displays the search results for medical institutions received from the server to the user. The user reviews the displayed information and selects a medical institution as needed.

[1267] Step 4:

[1268] After the user selects a medical institution, the device uses its camera and microphone to collect the user's emotions. It acquires the user's facial expressions and voice data as input.

[1269] Step 5:

[1270] The server uses an emotion recognition engine (e.g., Affectiva SDK) to analyze collected facial and voice data and recognize the user's emotions. It then generates and sends the recognized emotion information as output to the terminal.

[1271] Step 6:

[1272] The device adjusts how health information is displayed based on emotional information received from the server. For example, if the user is feeling anxious, the information will be displayed more concisely.

[1273] Step 7:

[1274] When a user pays for medical expenses, the terminal refers to past health information and suggests a payment method. The server uses a generative AI model to generate a payment method suitable for the user. The prompt message used is, "Please tell me how to analyze the user's emotions, concisely display past health information, and support payment."

[1275] Step 8:

[1276] The terminal displays the generated payment method to the user, and the user pays the medical expenses using the suggested method.

[1277] (Example 3)

[1278] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1279] In modern medical information systems, it is difficult for users to quickly and accurately find a medical institution suitable for their symptoms. Furthermore, the display of information is often not tailored to the user's emotional state, making it difficult to understand. Additionally, managing users' medical and prescription histories is cumbersome, and there are challenges in easily accessing past treatment records.

[1280] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1281] In this invention, the server includes means for searching for an appropriate medical institution based on a body part or symptom specified by the user and displaying the results; means for analyzing the user's emotions and adjusting the way information is displayed based on those emotions; and means for saving and making the user's past medical history accessible. As a result, the user can quickly find an appropriate medical institution, understand information more easily through emotion-based display, and easily access their past medical history.

[1282] A "user" refers to an individual who uses the system to search for medical information and manage their medical history.

[1283] "Body part" refers to a specific area of ​​the body where the user experiences symptoms.

[1284] "Symptoms" refer to physical or mental abnormalities experienced by the user.

[1285] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[1286] "Searching" refers to the act of finding relevant information from a database based on conditions specified by the user.

[1287] "Display" refers to the act of making search results and information visually accessible to users.

[1288] "Emotions" refer to the user's psychological state and are the subject of analysis by the system.

[1289] "Medical history" refers to the records of medical services a user has received in the past.

[1290] "Saving" refers to the act of recording information in a database so that it can be referenced later.

[1291] "Referencing" refers to the act of a user checking saved information.

[1292] To implement this invention, the server, terminal, and user must each fulfill their respective roles. The server uses a database management system to search for medical institutions based on the body parts and symptoms specified by the user. Specifically, the server uses a database management system such as MySQL and executes SQL queries to extract relevant information.

[1293] The server analyzes the user's emotions using emotion recognition software. For example, it uses an emotion recognition API to recognize emotions from text or voice input by the user. Based on this information, the server adjusts how the information is displayed and provides it in a format that is easy for the user to understand.

[1294] The terminal provides an interface for users to input information and view search results from the server. Through the terminal, users can input body parts and symptoms and view the search results.

[1295] For example, if a user enters "headache," the server will display a message such as "Looking for a doctor specializing in headaches" and provide a list of relevant doctors and hospitals. It will also display information about medical institutions the user has visited in the past, their diagnoses, and the medications they have been prescribed.

[1296] An example of a prompt to the generative AI model might be, "Please tell me how to search for doctors related to the affected area specified by the user and display the information based on emotion." Using this prompt, the generative AI model can be asked to specify a particular processing method. The flow of the specific processing in Example 3 will be explained using Figure 21.

[1297] Step 1:

[1298] The user uses a terminal to access the system and enter information about body parts and symptoms. The entered information is sent to the server. For example, the user might type "headache" and press the submit button.

[1299] Step 2:

[1300] The server uses a database management system to search for medical institutions based on the user's input information. The server executes an SQL query to extract information about doctors and hospitals related to "headache" from the database. The input is the user's symptom information, and the output is a list of relevant medical institutions.

[1301] Step 3:

[1302] The server sends the search results to the user's device. The device displays the received information to the user. Specifically, the device displays a "list of headache specialists" on the screen. The input is the search results from the server, and the output is information that the user can visually confirm.

[1303] Step 4:

[1304] The server analyzes the user's emotions using emotion recognition software. The emotion recognition API determines the emotion based on the text and voice data entered by the user. The input is the user's emotion data, and the output is the result of the emotion analysis.

[1305] Step 5:

[1306] The server adjusts how information is displayed based on the analyzed emotions. For example, if the server determines that the user is confused, it converts the information into a simpler, easier-to-understand format and sends it to the terminal. The input is the result of the emotion analysis, and the output is the adjusted information display.

[1307] Step 6:

[1308] The server stores the user's past medical history in a database and makes it accessible as needed. Specifically, the server updates the medical history so that the user can review it later. The input is new medical information, and the output is the updated medical history.

[1309] (Application Example 3)

[1310] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[1311] In today's healthcare environment, it is difficult for users to quickly find a medical institution that is appropriate for their symptoms. Furthermore, managing medical history, displaying information in a way that responds to emotions, and choosing payment methods for medical expenses all present significant challenges for users. To address these challenges, a flexible system that meets user needs is necessary.

[1312] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1313] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results; means for reducing the time required to search for a medical institution; means for managing each user's medical history; means for analyzing the user's emotions and adjusting the display method of the medical history according to those emotions; and means for suggesting a payment method for medical expenses. As a result, the user can quickly and appropriately select a medical institution, receive information displayed according to their emotions, and choose the optimal payment method.

[1314] A "user" refers to an individual who uses the system to search for medical institutions or manage their medical history.

[1315] "Affected area or symptoms" refers to the body part or health condition that a user specifies when searching for a medical institution.

[1316] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[1317] "Search method" refers to a function that finds appropriate medical institutions based on the conditions specified by the user.

[1318] "Medical history" refers to data that includes a user's past medical records and information about prescribed medications.

[1319] "Means of analyzing emotions" refers to functions that recognize the user's emotional state and adjust the system's operation based on that information.

[1320] "Means for adjusting the display method" refers to a function that changes the way information is presented according to the user's emotions.

[1321] "Means of suggesting payment methods" refers to a function that presents users with the most suitable method for paying medical expenses.

[1322] The system for implementing this invention consists of a user's smartphone or tablet and a server in the cloud. The server searches for appropriate medical institutions based on the affected area or symptoms specified by the user and displays the results on the user's device. A database management system (e.g., Firebase) is used for the search to enable rapid information provision.

[1323] The server also manages the user's medical history and analyzes the user's emotions using an emotion analysis engine (e.g., Microsoft Azure's Emotion Analysis API). This allows the display of the medical history to be adjusted according to the user's emotions. For example, if the user is feeling anxious, the information may be displayed simply to provide reassurance.

[1324] Furthermore, the server has a function to suggest payment methods for the user's medical expenses. It takes into account the user's past payment history and current emotional state to suggest the most suitable payment method.

[1325] As a concrete example, when a user opens the app after a consultation, the sentiment analysis engine detects anxiety from the user's facial expressions and voice. It retrieves past medical history from Firebase and suggests a simple payment method (e.g., one-click payment). An example of a prompt to input into the generating AI model is, "If the user is feeling anxious after a consultation, please refer to their past medical history and suggest the most suitable payment method."

[1326] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[1327] Step 1:

[1328] The user uses a device to input information about the affected area and symptoms. The device sends this information to the server. The entered information is stored on the server as data indicating the user's current health status.

[1329] Step 2:

[1330] Based on the received information about the affected area and symptoms, the server uses a database management system (e.g., Firebase) to search for appropriate medical institutions. A list of medical institutions is generated as a search result and sent to the device.

[1331] Step 3:

[1332] The terminal displays a list of medical institutions received from the server to the user. The user selects a desired medical institution from this list. The selected information is sent to the server for the next processing step.

[1333] Step 4:

[1334] The server analyzes the user's emotions using an emotion analysis engine (e.g., Microsoft Azure's Emotion Analysis API) based on the user's selection. It uses the user's voice and facial expression data as input and outputs the emotional state as the analysis result.

[1335] Step 5:

[1336] The server adjusts how the user's medical history is displayed based on the results of sentiment analysis. For example, if the user is feeling anxious, the data is processed to display information in a simpler way before being sent to the device.

[1337] Step 6:

[1338] The server considers the user's past payment history and current emotional state to suggest the most suitable payment method for medical expenses. The suggested payment method is sent to the terminal and displayed to the user.

[1339] Step 7:

[1340] The user reviews and selects a payment method displayed on their device. The selected payment method is sent to the server, and the payment process is initiated.

[1341] (Other examples)

[1342] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[1343] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1344] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1345] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[1346] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1347] [Fourth Embodiment]

[1348] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1349] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1350] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1351] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1352] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1353] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1354] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1355] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1356] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1357] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1358] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1359] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1360] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[1361] "Example of form 1"

[1362] The system of the present invention has a function to search for an appropriate hospital (doctor) based on the affected area and symptoms specified by the user. Specifically, when the user enters their affected area and symptoms on the interface, the system searches the database for information on hospitals and doctors and displays the results to the user. This function allows the user to efficiently find a hospital or doctor suitable for their symptoms.

[1363] "Example of form 2"

[1364] Furthermore, the system of the present invention has a function to manage each user's medical history and prescription history. Specifically, the system stores information such as hospitals and doctors the user has visited in the past, diagnoses, and prescribed medications in a database, allowing the user to refer to this information at any time. This function allows users to easily manage their own medical history and prescription history.

[1365] "Example of form 3"

[1366] For example, if a user specifies "headache" as the affected area, the system searches its database for hospital and doctor information and displays headache specialists and hospitals that can treat headaches to the user. It also saves information such as hospitals and doctors the user has visited for headaches in the past, diagnoses, and prescribed medications, allowing the user to access this information at any time.

[1367] The following describes the processing flow for each example of the form.

[1368] "Example of form 1"

[1369] Step 1: The user enters their affected area and symptoms on the system interface. Step 2: The system searches its database for hospital and doctor information and extracts hospitals and doctors suitable for the affected area and symptoms entered by the user.

[1370] Step 3: The system displays the extracted hospital and doctor information to the user.

[1371] "Example of form 2"

[1372] Step 1: The user enters their medical history and prescription history into the system.

[1373] Step 2: The system saves the medical history and prescription history entered by the user to the database.

[1374] Step 3: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[1375] "Example of form 3"

[1376] Step 1: The user enters "headache" as the affected area into the system.

[1377] Step 2: The system searches the database for hospital and doctor information and extracts headache specialists and hospitals that can treat headaches.

[1378] Step 3: The system displays the extracted hospital and doctor information to the user.

[1379] Step 4: The user enters information into the system, such as the hospitals and doctors they have visited in the past for headaches, their diagnoses, and the medications they have been prescribed.

[1380] Step 5: The system saves the information entered by the user to the database.

[1381] Step 6: When a user refers to their medical history or prescription history, the system retrieves the relevant information from the database and displays it to the user.

[1382] (Example 1)

[1383] Next, we will describe Embodiment 1 of Example Form 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1384] There is a challenge in that it is difficult for users to quickly and accurately find the appropriate medical institution based on their body part and symptoms. Furthermore, there is a need to efficiently manage and update each user's health information as needed.

[1385] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1386] In this invention, the server includes means for searching for an appropriate medical institution based on the body part or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. As a result, users can quickly find an appropriate medical institution and manage and update their health information efficiently.

[1387] A "user" refers to an individual who uses the system to search for appropriate medical institutions based on their own body parts and symptoms.

[1388] "Body parts and symptoms" refers to information related to a user's health condition that they enter when searching for a medical institution.

[1389] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics.

[1390] "Searching" refers to the process of examining information within a database based on conditions specified by the user and finding appropriate results.

[1391] "Display" refers to outputting search results to the device in a format that is easy for the user to understand.

[1392] "Health information" refers to data related to a user's health status, such as their medical history and prescription history.

[1393] "Management" refers to the process of organizing health information and updating or correcting it as needed.

[1394] A "server" refers to a computer system that receives input from users, searches a database, and returns the results.

[1395] A "terminal" refers to a device that a user uses to access a system through an interface.

[1396] As an embodiment of this invention, the following system is constructed.

[1397] The server generates a program that searches for appropriate medical institutions based on the body parts and symptoms specified by the user. This program consists of multiple components, including a user interface, database access, and a search algorithm. Specifically, the server implements the search algorithm using Python and manages medical institution information using a MySQL database.

[1398] The user uses the terminal's interface to input information about their body parts and symptoms. The terminal sends this input to the server. The server searches its database for information on medical institutions based on the received information. The search results are returned to the terminal and displayed to the user.

[1399] For example, if a user enters "stomach ache," the server searches its database for medical institutions specializing in "gastroenterology." The search results might display "local gastroenterology clinics" or "gastrointestinal hospitals in the city."

[1400] An example of a prompt to input into the generating AI model might be: "Create a program that searches for appropriate medical institutions based on the symptoms entered by the user. Use MySQL as the database and implement the search algorithm in Python."

[1401] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1402] Step 1:

[1403] The user accesses the device's interface and enters information about their body parts and symptoms. This entered data is saved on the device in text format. This data serves as foundational information for identifying the user's health problems.

[1404] Step 2:

[1405] The terminal sends the information entered by the user to the server as an HTTP request. This request contains data about the user's symptoms. The server receives this request and prepares to look up the database.

[1406] Step 3:

[1407] The server parses the received user information and queries a MySQL database. The database contains information such as the medical institution's specialty, location, and operating hours. The server uses a search algorithm implemented in Python to identify the medical institution best suited to the user's symptoms. The input is the user's symptom data, and the output is a list of appropriate medical institutions.

[1408] Step 4:

[1409] The server returns the search results to the terminal in JSON format. This result includes the name, address, and contact information of the medical institution. The server then processes the data to convert it into a format that is easy for the user to understand.

[1410] Step 5:

[1411] The device displays the received search results in a user-friendly format. Users can view detailed information about medical institutions on the screen and contact them as needed. The displayed information helps users make quick decisions when selecting a medical institution.

[1412] (Application Example 1)

[1413] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1414] In modern society, it is crucial for users to quickly and accurately find medical institutions that are appropriate for their symptoms. However, traditional methods present challenges, such as time-consuming information searches and difficulty for users to select the right medical institution. Furthermore, the lack of efficient means to manage and update users' health information as needed can lead to a decline in the quality of medical services.

[1415] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1416] In this invention, the server includes means for searching for an appropriate medical institution based on the affected area or symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing health information for each user. This enables users to quickly find an appropriate medical institution and allows for efficient management and updating of health information.

[1417] A "user" is an individual who uses the system to search for medical institutions based on their own symptoms.

[1418] "Affected area or symptoms" refers to the physical ailments or medical conditions that users enter when searching for medical institutions.

[1419] A "medical institution" refers to a facility that provides medical services, such as a hospital or clinic.

[1420] "Searching" is the act of finding appropriate information from a database based on conditions specified by the user.

[1421] "Health information" refers to a user's medical history, prescription history, and other personal information related to medical care.

[1422] A "smart device" refers to a portable electronic device with internet connectivity, such as a smartphone or tablet.

[1423] "Real-time" refers to information being processed and provided to the user immediately.

[1424] "Expert advice" refers to advice provided to users by professionals with medical knowledge.

[1425] The invention will now be described in terms of embodiments for carrying out the invention. This invention is a system in which a user inputs their symptoms using a smart device and searches for an appropriate medical institution. The system consists of a server, a user terminal, and a database.

[1426] The server searches for medical institution information in its database based on the affected area and symptoms specified by the user, and displays the results on the user's terminal. The server is built using Python and Flask, and uses SQLite for its database. The server receives user input and generates search results in real time.

[1427] The user terminal is a smart device such as a smartphone or tablet, and provides an interface for the user to input symptoms. The user terminal displays the search results received from the server and provides the information in a format that the user can easily understand.

[1428] For example, when a user enters "headache," the server searches the database and suggests nearby neurology clinics. This allows the user to quickly find an appropriate medical facility.

[1429] By using generative AI models, it is also possible to provide expert advice based on the user's symptoms. An example of a prompt message would be: "Based on the symptoms entered by the user, please suggest the most suitable medical institution. Example: For headaches, suggest a neurology hospital."

[1430] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1431] Step 1:

[1432] The user launches the application on their smart device and accesses the symptom input screen. The user enters their affected area and symptoms in text format. The entered data is sent from the user's device to the server.

[1433] Step 2:

[1434] The server analyzes the symptom data received from the user. This analysis uses natural language processing techniques to extract keywords from the input text. Based on the extracted keywords, the server searches for medical institution information in the database.

[1435] Step 3:

[1436] The server generates the results of a database search. The search results include a list of medical institutions suitable for the user's symptoms. The server sends the search results to the user's terminal.

[1437] Step 4:

[1438] The user terminal displays the search results received from the server. The display is in a format that is easy for the user to understand. The user can select the appropriate medical institution from the displayed list.

[1439] Step 5:

[1440] The server uses a generative AI model to generate expert advice based on the user's symptoms. Symptom data is input into the AI ​​model using prompts to obtain appropriate advice. The resulting advice is then sent to the user's terminal.

[1441] Step 6:

[1442] The user terminal displays expert advice received from the server. Users can use this advice to decide on a healthcare provider and their next course of action.

[1443] (Example 2)

[1444] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1445] In modern healthcare, it is crucial for users to efficiently manage their health information and quickly find appropriate medical facilities. However, traditional systems have problems such as users not being able to easily access past health information and the time it takes to search for medical facilities. Furthermore, there were challenges in ensuring the security of health information and obtaining appropriate advice based on that information.

[1446] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1447] In this invention, the server includes means for searching for an appropriate medical institution based on symptoms specified by the user and displaying the results, means for reducing the time required to search for a medical institution, and means for managing each user's health information. This enables users to efficiently manage their own health information and quickly search for an appropriate medical institution.

[1448] A "user" refers to an individual who uses the system to manage their own health information and search for medical institutions.

[1449] "Symptoms" refers to changes in health conditions or physical state that users specify when searching for medical institutions.

[1450] "Medical institutions" refer to facilities such as hospitals and clinics where users can receive medical treatment.

[1451] "Search results" refer to information about medical institutions provided by the system based on the conditions specified by the user.

[1452] "Health information" refers to medical-related data such as a user'...

Claims

[Claim 1] Equipped with a processor, The aforementioned processor, It provides an interface for the user to input a specified body part and / or symptom. Based on the entered body part and / or symptoms, a prompt is generated to instruct the system to search for a medical institution using a generated AI model. The generated prompt is used to search for medical institutions, the search results for medical institutions are formatted, and displayed on the user's terminal. It provides an interface for users to select a medical institution from the displayed list of medical institutions. We provide reservation and electronic payment functions for selected medical institutions. When medical expenses are paid using the aforementioned electronic payment function, the payment history of the medical expenses to be managed is stored in the database. It provides an interface for users to input their medical history and prescription history. The entered medical history and prescription history are stored in the database. The user terminal is made to accept user input to obtain specific information from the aforementioned database. The system retrieves information corresponding to the specific information from the database and displays it on the user terminal. system.

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