system

Abstract

We provide the system. [Solution] A terminal means for receiving user input, A data analysis means for analyzing the user input and identifying the appropriate medical department, Information provision means for generating and presenting the identified medical department information and related institution information to the user, An advice generation method for generating advice to reduce the risk of self-diagnosis, Communication methods to contact actual medical professionals as needed, A system that includes this.

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, which is 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 as a 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] Many people are unable to determine which medical department they should visit for their symptoms, resulting in wasted visits within medical institutions and referrals between medical departments, leading to delays in diagnosis and treatment. Furthermore, the risk of misdiagnosis due to self-diagnosis using the Internet increases, which may instead cause health damage. In response to such a situation, a system that can quickly and appropriately guide patients to the relevant medical department is required, but currently, there is no technology that can fully meet this requirement.

Means for Solving the Problems

[0005] This invention provides a system that identifies the appropriate medical department based on user symptom input and data analysis using a generating AI. The system includes a terminal for receiving user input, data analysis means, information provision means, advice generation means, and communication means, thereby presenting information on medical departments and related institutions in real time according to the user's symptoms, and enabling immediate contact with medical professionals as needed. This simultaneously achieves efficient use of medical resources and reduces the risks of self-diagnosis.

[0006] "User input" refers to information used by users in a system to describe their symptoms or condition in detail.

[0007] "Terminal means" refers to a device used by a user to input information and communicate with the system.

[0008] A "data analysis tool" is an element that has the function of analyzing data in order to identify the appropriate medical department based on the information received.

[0009] An "information provision means" is an element that has the function of providing users with judgment results and information on related hospitals based on the analyzed information.

[0010] An "advice generation means" is an element that has the function of generating advice to reduce the risks of self-diagnosis based on the judgment results derived from the user's input.

[0011] "Communication means" refers to communication functions that allow users to contact medical professionals as needed.

[0012] "System" refers to the overall mechanism through which various means interact with each other to provide medical information to the user. [Brief explanation of the drawing]

[0013] [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]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] 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), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] 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.

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a medical information provision system that allows users to accurately record their symptoms and receive appropriate medical advice quickly based on that information. The system uses advanced generative AI to analyze symptoms, recommend the appropriate medical department, and provide advice to reduce the risks of self-diagnosis. Furthermore, it enables communication with medical professionals as needed.

[0035] Server Processing

[0036] The server receives user symptom data from constantly connected terminals. Based on the received data, it performs analysis using AI generation to determine the most appropriate medical department for the user's symptoms. At the same time, the server refers to its built-in medical database and collects information on medical institutions corresponding to the region and symptoms.

[0037] Furthermore, the server automatically generates advice based on the analysis results, adding information to prevent misdiagnosis and delays in medical treatment. Upon user request, it provides contact information for appropriate medical professionals and offers necessary support in real time.

[0038] Terminal processing

[0039] The terminal provides a mechanism for users to input details of their symptoms via a user interface. Once the user enters their symptoms, the terminal sends this information to a server. Medical department information and advice received from the server are displayed appropriately on the terminal's screen. The terminal also presents the user with options to contact a doctor and activates communication means as needed.

[0040] User behavior

[0041] Users begin by accessing the system using their device and entering their symptoms. At this stage, users are required to provide detailed symptom information. The system analyzes the results, recommends a medical department, and displays it on the screen along with relevant hospital information. If necessary, users can immediately begin communicating with a doctor using their device.

[0042] Specific example

[0043] For example, if a user enters "sudden chest pain and shortness of breath," the server will receive this information, recommend a cardiologist, and provide a list of reputable hospitals in the user's area. It will also provide general advice on heart health and an automatically generated message explaining the importance of immediate medical attention. If the user selects "consult a doctor," the server will establish a connection with available medical professionals and immediately set up an environment where the user can contact them.

[0044] In this way, this system provides rapid and accurate medical support for users' symptoms, minimizing the risks associated with choosing a medical institution or self-diagnosis.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user opens the symptom input interface via their terminal and enters detailed information about their specific symptoms and the circumstances under which they occurred.

[0048] Step 2:

[0049] The terminal retrieves the symptom data entered by the user, formats it, and then sends it to the server.

[0050] Step 3:

[0051] The server launches a generative AI model to analyze the user's symptom data received from the terminal.

[0052] Step 4:

[0053] The server uses an AI model to identify the appropriate medical department based on the entered symptom data. It also references relevant medical databases to supplement this information.

[0054] Step 5:

[0055] The server generates identified medical department information and a list of recommended medical institutions, and applies advice generation methods to generate appropriate advice.

[0056] Step 6:

[0057] The server sends the generated medical department information, hospital list, and advice to the terminal.

[0058] Step 7:

[0059] The terminal uses the received information to display to the user the results of the medical department recommendation, information on related hospitals, and advice.

[0060] Step 8:

[0061] The user reviews the results and, if necessary, selects an option to communicate with a doctor from their device.

[0062] Step 9:

[0063] The device initiates communication to contact a doctor based on the user's selection and sends the necessary information to the server.

[0064] Step 10:

[0065] The server establishes a connection with the doctor and sends information to enable communication with the user.

[0066] (Example 1)

[0067] Next, we will describe 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."

[0068] In today's healthcare environment, it is crucial for users to accurately communicate their symptoms to healthcare providers and receive appropriate treatment promptly. However, many users find it difficult to assess their symptoms, leading to misdiagnosis and delays in medical care. Furthermore, finding the most suitable healthcare provider in their area quickly can be challenging, potentially negatively impacting users' health.

[0069] 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.

[0070] In this invention, the server includes information gathering means for receiving user input, data processing means for analyzing the user input and identifying the appropriate medical department, and information presentation means for referencing a built-in medical information database, generating appropriate medical department information and related medical facility information, and presenting them to the user. As a result, users can receive recommendations for the appropriate medical department simply by entering their symptoms, quickly identify the best medical institution in their area, and smoothly contact medical professionals as needed.

[0071] "Information gathering means" refers to a mechanism that provides an interface for users to input symptoms and related information, and for receiving that information.

[0072] "Data processing means" refers to algorithms and processes used to analyze received user input information and identify the appropriate medical department.

[0073] A "medical information database" is a collection of information that holds a large amount of data, including medical departments, symptoms, and regional information, and is referenced as needed.

[0074] An "information presentation means" is an output interface that presents information about medical departments and related medical facilities to users in an easy-to-understand manner.

[0075] An "advice generation system" is a system that automatically generates advice to mitigate the risks of self-diagnosis and inform users of the importance of appropriate medical treatment.

[0076] "Communication means" refers to the means that enable connection between users and medical professionals and allow for real-time communication as needed.

[0077] A "recommendation method" is a system that uses processes and algorithms to suggest the most suitable medical institutions to users, taking into account local information and reputation ratings.

[0078] To implement this invention, the server, terminal, and user each play a specific role.

[0079] The server is equipped with a dedicated generative AI model and is responsible for analyzing information received from users. This generative AI model works in conjunction with a large-scale medical information database to identify the appropriate medical department from the user's input information. The server operates on a state-of-the-art hardware environment, enabling high-speed and accurate data processing. Furthermore, it also has an advice generation function that creates advice to prevent errors caused by user self-diagnosis.

[0080] The terminal provides an interface for users to input their symptoms. This allows users to record their symptoms in detail and send them to the server. The terminal also visually displays medical department information and advice received from the server, making it easy for users to understand. Through the communication means on the terminal, users can contact medical professionals directly as needed.

[0081] The user is the central figure who inputs their symptoms using their device and receives the necessary information. For example, if a user inputs symptoms such as "sudden chest pain and shortness of breath," the server receives this information, recommends a cardiology specialist, and generates and provides a list of reputable medical institutions in the area. It also generates and presents general advice for maintaining heart health. If the user selects "Consult a doctor," the server immediately enables communication with a medical professional.

[0082] This process, supported by a generative AI model throughout the entire system, allows users to receive quick and appropriate medical support. An example of a specific prompt is input such as, "My current symptoms are sudden chest pain and shortness of breath. Which department should I go to?"

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users input symptoms and signs in text format using a terminal. This input data is collected through the user interface and prepared for direct transmission to the server. The input data, which includes specific symptoms and circumstances, is important for subsequent data analysis.

[0086] Step 2:

[0087] The terminal sends user input data to the server. This data is transmitted via a secure communication protocol. The server receives this input data and prepares it for analysis by the generating AI model. Data integrity is checked at this stage, and the data is validated as needed.

[0088] Step 3:

[0089] The server runs a generative AI model using the received user symptom data. It references a large medical information database to identify the most appropriate medical department based on the input data. Machine learning algorithms are used for data processing, ensuring efficient analysis. The output is information on the relevant medical department and an initial assessment based on the symptoms.

[0090] Step 4:

[0091] Based on the analysis results, the server generates information on appropriate medical departments and related healthcare facilities. This information is customized to take into account the user's geographical location and is configured to provide the best possible options for the user. Furthermore, advice to mitigate risks through self-diagnosis is automatically generated.

[0092] Step 5:

[0093] The terminal receives medical department information and advice transmitted from the server and presents it visually to the user. Appropriate information is clearly displayed on the user interface, providing a foundation for the user to decide on their next action. At this stage, the user can also select actions such as "consult with a doctor."

[0094] Step 6:

[0095] When a user chooses to communicate with a medical professional, the device establishes a communication method via a server. This process includes preparing for voice or video calls and configuring the system to ensure smooth contact between the user and the professional. This system allows the user to receive necessary medical advice at the appropriate time.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In the modern healthcare system, it is difficult for users to quickly and appropriately select a medical department and access healthcare facilities based on their symptoms. Furthermore, payment procedures after consultations are often time-consuming, which places a burden on patients. Therefore, there is a need for a system that allows users to efficiently receive medical services and make payments quickly.

[0099] 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.

[0100] In this invention, the server includes an information processing device means for receiving user input, a data analysis device means for analyzing the user input and identifying the appropriate medical department, an information providing device means for generating and presenting the identified medical department information and related institution information to the user, an advice generating device means for generating advice to reduce the risk of self-diagnosis, a communication device means for contacting actual medical professionals as needed, and an electronic payment device means for instantly electronically settling medical expenses at the relevant medical institution via the information providing device means. This enables the user to receive appropriate medical services quickly, accurately, and efficiently, and to make payments for them.

[0101] An "information processing device" is a device that receives information from a user as input, appropriately classifies and organizes that information, and has the function of transmitting necessary data to other system components.

[0102] A "data analysis device" is a device that performs analysis based on the user's input information received to identify the appropriate medical department and proposes a suitable medical department to the user.

[0103] "Information provision device means" refers to a device that generates information on medical departments and related medical institutions identified through analysis, and provides that information to the user visually or by other sensory means.

[0104] A "proposal generation device" is a device that generates necessary advice to prevent errors in self-diagnosis and provides that advice to the user in order to reduce health risks.

[0105] "Communication device means" refers to a device that provides communication means and an environment that enables users to contact actual medical professionals as needed and to communicate quickly.

[0106] An "electronic payment device" is a device that has a payment system that enables users to pay medical fees at a relevant medical institution instantly, safely, and efficiently.

[0107] A system for implementing this invention consists of a complex configuration including an information processing device, a data analysis device, an information provision device, an advice generation device, a communication device, and an electronic payment device.

[0108] The server receives symptom data in real time, transmitted from the user via an information processing device. The received data is analyzed within a data analysis device using a generative AI model to identify the appropriate medical department. In doing so, the server refers to a large medical database and collects information on relevant medical institutions.

[0109] The analysis results are transmitted to the user's terminal via an information provision device, and along with suggestions for medical institutions relevant to the user, advice to mitigate self-diagnosis risks is also displayed. The advice generation device automatically generates appropriate advice according to the risk using a generation AI model and notifies the user.

[0110] Furthermore, the communication device provides a means to establish communication with actual medical professionals as needed. The electronic payment device provides users with a means to process medical fees returned from healthcare facilities quickly and securely through the information provision device. This allows users to easily complete the entire process from booking medical services to making payments.

[0111] For example, if a user enters "acute headache and nausea," the information processing device receives this information, identifies neurology as the appropriate medical department, and presents a list of nearby medical facilities. It also provides general advice regarding symptoms, such as encouraging hydration, and offers the option to communicate with a medical professional if necessary. Regarding payment, the system is designed to allow for smooth electronic payment by integrating all information. An example of a prompt to the generating AI model is, "Identify the most relevant medical department for the symptoms the user is experiencing and recommend appropriate nearby medical facilities."

[0112] This invention solves the challenges of modern medicine, namely the need for rapid selection of medical departments and payment procedures, and provides users with an easy-to-use medical experience.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The user enters symptom information through the terminal's user interface. This input is collected as digital data by the information processing unit. The entered data is then sent directly to the server.

[0116] Step 2:

[0117] The server takes the received user's symptom data as input and starts analyzing it using a data analysis device with a generating AI model. This analysis compares the symptom data with a medical database to identify the most appropriate medical department related to the symptoms. As a result, information on the appropriate medical department is obtained.

[0118] Step 3:

[0119] The server outputs appropriate medical department information obtained from the data analysis device, and based on this information, the information provision device generates related medical institution information. The generated medical institution information is based on the user's location and is returned to the user's terminal.

[0120] Step 4:

[0121] The user's terminal receives information on medical departments and medical institutions transmitted from the server and displays it on the screen. Simultaneously, advice generated by the advice generation device to mitigate self-diagnosis risks is also displayed.

[0122] Step 5:

[0123] If the user requires it, the device will establish communication with actual medical professionals through communication equipment. This communication includes real-time chat, voice calls, and video calls.

[0124] Step 6:

[0125] When a user wishes to pay for medical services, the terminal activates the electronic payment device and initiates a process to instantly electronically settle the medical fees obtained from the information provider. The inputs are payment information and the medical fees, and the output confirms that the payment is securely completed via the payment network.

[0126] 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.

[0127] This invention is a medical information system that uses an emotion engine to recognize symptoms and emotions input by the user, recommends the most suitable medical department based on that information, and provides related information. The aim of this system is to provide more comprehensive and individualized medical support by analyzing the user's emotional state using the emotion engine and utilizing the results to provide other medical information and advice.

[0128] Server Processing

[0129] The server receives emotional data along with the user's symptom data sent from the terminal. This data is analyzed by the emotion engine. The resulting emotional state provides an indicator of the user's subjective health status, such as the degree of anxiety or stress they are experiencing.

[0130] The server analyzes incoming data using a generative AI model and determines the most suitable medical department, taking emotional data into consideration. Furthermore, when recommending a department, it adjusts the wording of the advice based on the user's emotional state. For example, if the user is showing high levels of anxiety, it will provide advice in a particularly gentle tone and include additional reassuring information.

[0131] Terminal processing

[0132] The device provides an interactive screen through its user interface to answer questions about symptoms and emotions. Once the user enters information, the device organizes it and sends it to a server. The server retrieves information including the medical department and advice, and displays it to the user in a format adjusted according to their emotions.

[0133] User behavior

[0134] Users use a terminal to input detailed information about their symptoms and associated emotions. The system analyzes this input and recommends appropriate medical departments. Users can review the displayed recommendations and choose to access the appropriate medical facility with peace of mind.

[0135] Specific example

[0136] For example, if a user enters "severe headache and intense anxiety," the server receives and analyzes this information and may recommend a neurologist. At the same time, considering the user's intense anxiety, it may add advice such as, "It's understandable to be worried when you have a headache, but a qualified specialist can help. You can also try some stretches and relaxation techniques that you can do right away."

[0137] In this way, the system can comprehensively assess the user's symptoms and emotional state, enabling it to provide more personalized medical support. This improves the medical experience and facilitates smoother access to healthcare facilities.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] The user uses the device's interface to input their symptoms and the emotions they are experiencing at the time. The device provides questions and sliders to help users assess their emotions as an input aid.

[0141] Step 2:

[0142] The terminal acquires symptom and emotion data entered by the user, formats them into a unified format, and then sends them to the server.

[0143] Step 3:

[0144] The server receives symptom and emotion data sent from the terminal and first uses an emotion engine to analyze the user's emotional state. Through emotion analysis, it determines what kind of emotions the user is experiencing, such as anxiety, joy, or anger, and identifies the level of those specific emotions.

[0145] Step 4:

[0146] The server inputs the received symptom data into a generating AI model and begins the analysis. The analysis results identify the most appropriate medical department. Emotional data is also taken into consideration and, if necessary, influences the selection of the medical department.

[0147] Step 5:

[0148] The server generates a list of relevant medical institutions based on the identified medical department information. In addition, it generates advice that reflects the user's emotional state, adjusting its expression and content accordingly.

[0149] Step 6:

[0150] The server then sends the generated medical department information, related medical institutions, and emotionally sensitive advice to the terminal.

[0151] Step 7:

[0152] The terminal uses information received from the server to display recommendations and advice for medical departments to the user. Based on sentiment data, the display method and wording are optimized to ensure that users can receive the information with confidence.

[0153] Step 8:

[0154] Users can review the displayed information and make decisions about the most appropriate medical institution and their next course of action. They also have the option to contact a medical professional if necessary.

[0155] (Example 2)

[0156] Next, we will describe 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".

[0157] In modern healthcare systems, it is difficult for users to quickly select the appropriate medical institution while considering their own symptoms and emotions. Furthermore, there is often insufficient information to alleviate misunderstandings and anxieties caused by self-diagnosis. As a result, users tend to make inappropriate decisions regarding access to medical care.

[0158] 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.

[0159] In this invention, the server includes an input means for receiving user input and acquiring symptom and emotional data, an analysis means for analyzing the symptom and emotional data and determining the emotional state, and a medical department recommendation means for identifying the most suitable medical department from the emotional analysis results and symptom data using generative artificial intelligence. As a result, users can receive accurate recommendations for medical departments based on their symptoms and emotional state, reducing anxiety and allowing them to choose a medical institution with confidence.

[0160] "User input" refers to information about symptoms and emotions that users enter through their devices.

[0161] "Symptom data" refers to information about physical ailments and health conditions reported by users.

[0162] "Emotional data" refers to information about a user's feelings, stress levels, anxiety, and other psychological states.

[0163] "Input means" refers to a device or software that has the function of receiving information from a user and acquiring it as data.

[0164] "Analysis means" refers to devices or algorithms that have the ability to analyze and judge the user's emotional state based on the received data.

[0165] "Generative artificial intelligence" refers to an algorithm or system that has the ability to generate optimal results based on input data.

[0166] "Medical department recommendation method" refers to a function that identifies and suggests the most suitable medical department for the user based on analyzed emotional state and symptom data.

[0167] "Information provision means" refers to means of presenting analysis results and recommended content to users visually or audibly.

[0168] "Advice generation means" refers to a system or component that has the function of creating and providing advice to alleviate anxiety, taking into account the user's emotional state.

[0169] This invention supports rapid and appropriate access to medical institutions by analyzing the user's symptoms and emotions through a medical information system and recommending the appropriate medical department.

[0170] The server receives user input data sent from the terminal. This data includes symptom information entered by the user on the interface, as well as emotional data including anxiety and stress levels specified using sliders, etc. The server analyzes the received data using software called an emotion engine to identify the user's state of mind.

[0171] The generative AI model is the core technology of this system, identifying the most appropriate medical department for the user based on analyzed emotional state and symptom data. The server inputs prompts to the generative AI model to obtain recommendations for medical departments. For example, a prompt such as, "The user entered a severe headache, accompanied by strong anxiety. Based on this, please suggest a medical department and advice," might be used.

[0172] The terminal displays medical department recommendations received from the server, along with advice tailored to the user's emotional state. Users are provided with reassuring language and guidance on the correct way to access medical facilities. The user interface is designed to present information in an intuitive and easy-to-understand format.

[0173] This system allows users to receive medical support tailored to their symptoms and feelings, and to quickly select the appropriate medical institution. The aim of this invention is to improve the overall medical experience by increasing access to healthcare and reducing user anxiety.

[0174] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0175] Step 1:

[0176] Users input symptoms and emotions using the terminal's user interface. The input data includes symptom information entered by the user in free-form text, as well as numerical data indicating anxiety and stress levels. This data is formatted by the terminal and prepared for transmission to the server.

[0177] Step 2:

[0178] The terminal sends data acquired from the user to the server. Symptom descriptions and emotion values ​​are sent as encoded data packets in a format that the server can securely receive. Encryption protocols are used to protect data integrity and privacy.

[0179] Step 3:

[0180] The server temporarily stores the data received from the terminal in a database and passes it to the emotion engine for analysis. The emotion engine utilizes a generative AI model to analyze the user's emotional state from the symptom description. This analysis uses text mining and natural language processing techniques to identify feelings of anxiety and stress. The output generates numerical values ​​and categories that represent the user's emotional state.

[0181] Step 4:

[0182] The server uses a generative AI model to determine the most suitable medical department based on the emotion analysis results and symptom data. It sends a prompt to the generative AI model to identify the medical department best suited to the user's symptoms and emotional state. This step outputs a list of candidate medical departments and their priorities.

[0183] Step 5:

[0184] The server generates advice that takes the user's emotional state into consideration, along with the medical department's recommendation results. The generation AI model creates emotionally sensitive text, outputting advice that includes specific and gentle words, especially to alleviate anxiety.

[0185] Step 6:

[0186] The server sends the generated medical department information and advice to the terminal. The terminal displays the information in a visually easy-to-understand format. This allows the user to select the appropriate medical department with confidence. The terminal screen is designed to include elements such as the name of the medical department, the reason for the recommendation, and emotionally-sensitive advice.

[0187] (Application Example 2)

[0188] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0189] It is not easy for users to choose the appropriate medical institution or health-related product while considering their symptoms and emotions. In particular, emotional instability can impair judgment, potentially leading to misdiagnosis or inappropriate product selection. Therefore, there is a need for more appropriate and individualized recommendations for medical institutions and products that take into account the user's emotional state.

[0190] 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.

[0191] In this invention, the server includes data analysis means for analyzing user input and emotional data to identify an appropriate medical department or product; information provision means for generating and presenting identified medical department information, product information, and related institution information to the user; and advice generation means for generating advice according to the user's emotional state. This enables the user to confidently select an appropriate medical institution and product in a way that takes their emotions into consideration.

[0192] "User input" refers to the provision of information or data input by the user to the device, including information about symptoms and emotions.

[0193] "Emotional data" refers to information about the emotions expressed by users, including data that quantifies or categorizes the degree of anxiety, stress, etc.

[0194] A "medical department" refers to a specific specialty within a medical institution, such as internal medicine, surgery, or neurology.

[0195] "Products" refer to items such as health-related products and supplements that are deemed appropriate according to the user's health condition and emotions.

[0196] "Data analysis means" refers to technical means that have the function of analyzing user input information and emotional data to identify the most suitable medical department or product.

[0197] "Information provision means" refers to technical means that generate, display, or transmit information necessary for the user based on the analysis results.

[0198] An "advice generation means" is a technical means that has the function of creating and providing appropriate advice or messages to the user based on the user's emotional state.

[0199] The system that realizes this invention is configured to run a program equipped with a generative AI model for analyzing user input and emotional data. The software primarily used includes a generative AI model, specifically OpenAI's GPT model and Hugging Face's transformers library. This allows the system to analyze emotions from the information input by the user and recommend appropriate medical departments or products.

[0200] The server receives user symptom and emotional data transmitted from the terminal and analyzes it using a generative AI model. Based on the analysis results, it identifies the appropriate medical department or product and generates related information. When providing information, personalized advice is generated according to the user's emotional state and presented to them. This process is performed in real time and aims to reduce the user's anxiety and stress.

[0201] The terminal supports information input through a user interface, designed to allow users to easily report their symptoms and feelings. The entered data is sent to a server, and the results are returned after processing is complete. Users can review the displayed medical departments, products, and advice, and choose the appropriate course of action.

[0202] An example of a prompt might be, "The user has reported insomnia and anxiety. Please recommend suitable products and create a comforting, reassuring advice message." By feeding this prompt to the AI ​​generation model, the most suitable products and advice for the user will be generated.

[0203] For example, if a user enters "I have a headache and feel anxious," the server can recommend a neurologist's consultation while also suggesting relaxation techniques and supplements that can help alleviate symptoms. In this way, the system comprehensively assesses the user's health condition and emotions and provides personalized options.

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The user inputs information about symptoms and emotions through the terminal's user interface. The entered data is recorded as text for symptom information, and emotional states are selected using a pull-down menu or slider, or recorded as text. The terminal then organizes this data and converts it into a format for transmission to the server.

[0207] Step 2:

[0208] The server analyzes symptom information and emotional data received from the terminal. First, the received data is stored in a database, and then the emotional data is analyzed using a generative AI model. This process includes calculations to categorize the emotional data as part of data processing. As a result of the analysis, the user's emotional state and subjective health indicators are generated.

[0209] Step 3:

[0210] The server uses a generative AI model to identify the most suitable medical department or product based on the analysis results. The model is given a prompt such as, "The user is experiencing discomfort and a certain emotion. Please identify the appropriate medical department or product for this condition," and in response, it generates a list of recommended medical departments or products. The output information includes an optimal action plan for the user's symptoms and emotions.

[0211] Step 4:

[0212] The server generates advice based on the user's emotional state. Using a generative AI model, it formulates gentle messages and recommended actions that take into account the results of the emotion analysis. This process generates text using expressions that convey a sense of security and trustworthiness. The generated advice is output as text.

[0213] Step 5:

[0214] The server is built as a data package for sending the generated medical department information, product information, and results including advice to the user. This data is sent to the user's terminal and displayed on the terminal in a visually easy-to-understand format.

[0215] Step 6:

[0216] Users can review the information presented on their device, select a medical department, and consider purchasing recommended products. They can also take actions to improve their health based on the advice provided.

[0217] 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.

[0218] Data generation model 58 is a 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> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0219] 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.

[0220] [Second Embodiment]

[0221] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0222] 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.

[0223] 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).

[0224] 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.

[0225] 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.

[0226] 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).

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0233] This invention is a medical information provision system that allows users to accurately record their symptoms and receive appropriate medical advice quickly based on that information. The system uses advanced generative AI to analyze symptoms, recommend the appropriate medical department, and provide advice to reduce the risks of self-diagnosis. Furthermore, it enables communication with medical professionals as needed.

[0234] Server Processing

[0235] The server receives user symptom data from constantly connected terminals. Based on the received data, it performs analysis using AI generation to determine the most appropriate medical department for the user's symptoms. At the same time, the server refers to its built-in medical database and collects information on medical institutions corresponding to the region and symptoms.

[0236] Furthermore, the server automatically generates advice based on the analysis results, adding information to prevent misdiagnosis and delays in medical treatment. Upon user request, it provides contact information for appropriate medical professionals and offers necessary support in real time.

[0237] Terminal processing

[0238] The terminal provides a mechanism for users to input details of their symptoms via a user interface. Once the user enters their symptoms, the terminal sends this information to a server. Medical department information and advice received from the server are displayed appropriately on the terminal's screen. The terminal also presents the user with options to contact a doctor and activates communication means as needed.

[0239] User behavior

[0240] Users begin by accessing the system using their device and entering their symptoms. At this stage, users are required to provide detailed symptom information. The system analyzes the results, recommends a medical department, and displays it on the screen along with relevant hospital information. If necessary, users can immediately begin communicating with a doctor using their device.

[0241] Specific example

[0242] For example, if a user enters "sudden chest pain and shortness of breath," the server will receive this information, recommend a cardiologist, and provide a list of reputable hospitals in the user's area. It will also provide general advice on heart health and an automatically generated message explaining the importance of immediate medical attention. If the user selects "consult a doctor," the server will establish a connection with available medical professionals and immediately set up an environment where the user can contact them.

[0243] In this way, this system provides rapid and accurate medical support for users' symptoms, minimizing the risks associated with choosing a medical institution or self-diagnosis.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] The user opens the symptom input interface via their terminal and enters detailed information about their specific symptoms and the circumstances under which they occurred.

[0247] Step 2:

[0248] The terminal retrieves the symptom data entered by the user, formats it, and then sends it to the server.

[0249] Step 3:

[0250] The server launches a generative AI model to analyze the user's symptom data received from the terminal.

[0251] Step 4:

[0252] The server uses an AI model to identify the appropriate medical department based on the entered symptom data. It also references relevant medical databases to supplement this information.

[0253] Step 5:

[0254] The server generates identified medical department information and a list of recommended medical institutions, and applies advice generation methods to generate appropriate advice.

[0255] Step 6:

[0256] The server sends the generated medical department information, hospital list, and advice to the terminal.

[0257] Step 7:

[0258] The terminal uses the received information to display to the user the results of the medical department recommendation, information on related hospitals, and advice.

[0259] Step 8:

[0260] The user reviews the results and, if necessary, selects an option to communicate with a doctor from their device.

[0261] Step 9:

[0262] The device initiates communication to contact a doctor based on the user's selection and sends the necessary information to the server.

[0263] Step 10:

[0264] The server establishes a connection with the doctor and sends information to enable communication with the user.

[0265] (Example 1)

[0266] Next, we will describe 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."

[0267] In today's healthcare environment, it is crucial for users to accurately communicate their symptoms to healthcare providers and receive appropriate treatment promptly. However, many users find it difficult to assess their symptoms, leading to misdiagnosis and delays in medical care. Furthermore, finding the most suitable healthcare provider in their area quickly can be challenging, potentially negatively impacting users' health.

[0268] 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.

[0269] In this invention, the server includes information gathering means for receiving user input, data processing means for analyzing the user input and identifying the appropriate medical department, and information presentation means for referencing a built-in medical information database, generating appropriate medical department information and related medical facility information, and presenting them to the user. As a result, users can receive recommendations for the appropriate medical department simply by entering their symptoms, quickly identify the best medical institution in their area, and smoothly contact medical professionals as needed.

[0270] "Information gathering means" refers to a mechanism that provides an interface for users to input symptoms and related information, and for receiving that information.

[0271] "Data processing means" refers to algorithms and processes used to analyze received user input information and identify the appropriate medical department.

[0272] A "medical information database" is a collection of information that holds a large amount of data, including medical departments, symptoms, and regional information, and is referenced as needed.

[0273] An "information presentation means" is an output interface that presents information about medical departments and related medical facilities to users in an easy-to-understand manner.

[0274] An "advice generation system" is a system that automatically generates advice to mitigate the risks of self-diagnosis and inform users of the importance of appropriate medical treatment.

[0275] "Communication means" refers to the means that enable connection between users and medical professionals and allow for real-time communication as needed.

[0276] A "recommendation method" is a system that uses processes and algorithms to suggest the most suitable medical institutions to users, taking into account local information and reputation ratings.

[0277] To implement this invention, the server, terminal, and user each play a specific role.

[0278] The server is equipped with a dedicated generative AI model and is responsible for analyzing information received from users. This generative AI model works in conjunction with a large-scale medical information database to identify the appropriate medical department from the user's input information. The server operates on a state-of-the-art hardware environment, enabling high-speed and accurate data processing. Furthermore, it also has an advice generation function that creates advice to prevent errors caused by user self-diagnosis.

[0279] The terminal provides an interface for users to input their symptoms. This allows users to record their symptoms in detail and send them to the server. The terminal also visually displays medical department information and advice received from the server, making it easy for users to understand. Through the communication means on the terminal, users can contact medical professionals directly as needed.

[0280] The user is the central figure who uses the terminal to input their symptoms and receive the necessary information. For example, when the user inputs symptoms such as "sudden chest pain and shortness of breath", the server receives this, recommends the Department of Cardiology as the medical department, generates and provides a list of reputable medical institutions in the area. It also generates general advice for maintaining heart health and presents it to the user. When the user selects "Consult a doctor", the server immediately enables communication with medical experts.

[0281] Through this process supported by the generative AI model throughout the system, the user can receive medical support quickly and appropriately. As an example of a specific prompt sentence, an input such as "My current symptoms are sudden chest pain and shortness of breath. Which medical department should I go to?" is shown.

[0282] The flow of the specific process in Example 1 will be described using FIG. 11.

[0283] Step 1:

[0284] The user uses the terminal to input symptoms and signs in text form. This input data is collected through the user interface and prepared to be sent to the server as it is. Since the input data includes specific symptoms and situations, it is important for subsequent data analysis.

[0285] Step 2:

[0286] The terminal sends the user's input data to the server. At this time, the data is sent through a secure communication protocol. The server receives this input data and prepares for analysis by the generative AI model. The integrity of the data is confirmed at this stage, and the data is validated if necessary.

[0287] Step 3:

[0288] The server runs a generative AI model using the received user symptom data. It references a large medical information database to identify the most appropriate medical department based on the input data. Machine learning algorithms are used for data processing, ensuring efficient analysis. The output is information on the relevant medical department and an initial assessment based on the symptoms.

[0289] Step 4:

[0290] Based on the analysis results, the server generates information on appropriate medical departments and related medical facilities. This information is customized to take into account the user's geographical location and is configured to provide the best possible options for the user. Furthermore, advice to mitigate risks through self-diagnosis is automatically generated.

[0291] Step 5:

[0292] The terminal receives medical department information and advice transmitted from the server and presents it visually to the user. Appropriate information is clearly displayed on the user interface, providing a foundation for the user to decide on their next action. At this stage, the user can also select actions such as "consult with a doctor."

[0293] Step 6:

[0294] When a user chooses to communicate with a medical professional, the device establishes a communication method via a server. This process includes preparing for voice or video calls and configuring the system to ensure smooth contact between the user and the professional. This system allows the user to receive necessary medical advice at the appropriate time.

[0295] (Application Example 1)

[0296] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0297] In the modern healthcare system, it is difficult for users to quickly and appropriately select a medical department and access healthcare facilities based on their symptoms. Furthermore, payment procedures after consultations are often time-consuming, which places a burden on patients. Therefore, there is a need for a system that allows users to efficiently receive medical services and make payments quickly.

[0298] 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.

[0299] In this invention, the server includes an information processing device means for receiving user input, a data analysis device means for analyzing the user input and identifying the appropriate medical department, an information providing device means for generating and presenting the identified medical department information and related institution information to the user, an advice generating device means for generating advice to reduce the risk of self-diagnosis, a communication device means for contacting actual medical professionals as needed, and an electronic payment device means for instantly electronically settling medical expenses at the relevant medical institution via the information providing device means. This enables the user to receive appropriate medical services quickly, accurately, and efficiently, and to make payments for them.

[0300] An "information processing device" is a device that receives information from a user as input, appropriately classifies and organizes that information, and has the function of transmitting necessary data to other system components.

[0301] A "data analysis device" is a device that performs analysis based on the user's input information received to identify the appropriate medical department and proposes a suitable medical department to the user.

[0302] "Information provision device means" refers to a device that generates information on medical departments and related medical institutions identified through analysis, and provides that information to the user visually or by other sensory means.

[0303] The "Advice Generation Device Means" is a device that generates advice necessary to prevent errors in self-diagnosis and reduces health risks by providing the advice to the user.

[0304] The "Communication Device Means" is a device that provides communication means and an environment for quick communication for the user to contact actual medical experts as needed.

[0305] The "Electronic Payment Device Means" is a device having a payment system that enables the user to pay medical treatment fees at related medical institutions immediately, safely and efficiently.

[0306] The system for implementing this invention consists of a complex configuration including an information processing device, a data analysis device, an information providing device, an advice generation device, a communication device, and an electronic payment device.

[0307] The server receives symptom data transmitted from the user via the information processing device in real time. The received data is analyzed in the data analysis device using a generation AI model to identify the appropriate medical department. At that time, the server refers to a large-scale medical database and collects information on related medical institutions.

[0308] The analysis result is transmitted to the user's terminal through the information providing device, and in addition to the proposal of the medical institution corresponding to the user, advice for reducing the self-diagnosis risk is also displayed. The advice generation device automatically generates appropriate advice according to the risk using the generation AI model and notifies the user.

[0309] Furthermore, the communication device provides means for establishing communication with actual medical experts as needed. The electronic payment device provides the user with payment means for quickly and safely processing medical treatment fees at the medical institution returned through the information providing device. As a result, the user can easily complete the reservation and payment of medical services.

[0310] For example, if a user enters "acute headache and nausea," the information processing device receives this information, identifies neurology as the appropriate medical department, and presents a list of nearby medical facilities. It also provides general advice regarding symptoms, such as encouraging hydration, and offers the option to communicate with a medical professional if necessary. Regarding payment, the system is designed to allow for smooth electronic payment by integrating all information. An example of a prompt to the generating AI model is, "Identify the most relevant medical department for the symptoms the user is experiencing and recommend appropriate nearby medical facilities."

[0311] This invention solves the challenges of modern medicine, namely the need for rapid selection of medical departments and payment procedures, and provides users with an easy-to-use medical experience.

[0312] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0313] Step 1:

[0314] The user enters symptom information through the terminal's user interface. This input is collected as digital data by the information processing unit. The entered data is then sent directly to the server.

[0315] Step 2:

[0316] The server takes the received user's symptom data as input and starts analyzing it using a data analysis device with a generating AI model. This analysis compares the symptom data with a medical database to identify the most appropriate medical department related to the symptoms. As a result, information on the appropriate medical department is obtained.

[0317] Step 3:

[0318] The server outputs appropriate medical department information obtained from the data analysis device, and based on this information, the information provision device generates related medical institution information. The generated medical institution information is based on the user's location and is returned to the user's terminal.

[0319] Step 4:

[0320] The user's terminal receives information on medical departments and medical institutions transmitted from the server and displays it on the screen. Simultaneously, advice generated by the advice generation device to mitigate self-diagnosis risks is also displayed.

[0321] Step 5:

[0322] If the user requires it, the device will establish communication with actual medical professionals through communication equipment. This communication includes real-time chat, voice calls, and video calls.

[0323] Step 6:

[0324] When a user wishes to pay for medical services, the terminal activates the electronic payment device and initiates a process to instantly electronically settle the medical fees obtained from the information provider. Inputs include payment information and the medical fees, and the output confirms that the payment is securely completed via the payment network.

[0325] 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.

[0326] This invention is a medical information system that uses an emotion engine to recognize symptoms and emotions input by the user, recommends the most suitable medical department based on that information, and provides related information. The aim of this system is to provide more comprehensive and individualized medical support by analyzing the user's emotional state using the emotion engine and utilizing the results to provide other medical information and advice.

[0327] Server Processing

[0328] The server receives emotional data along with the user's symptom data sent from the terminal. This data is analyzed by the emotion engine. The resulting emotional state provides an indicator of the user's subjective health status, such as the degree of anxiety or stress they are experiencing.

[0329] The server analyzes incoming data using a generative AI model and determines the most suitable medical department, taking emotional data into consideration. Furthermore, when recommending a department, it adjusts the wording of the advice based on the user's emotional state. For example, if the user is showing high levels of anxiety, it will provide advice in a particularly gentle tone and include additional reassuring information.

[0330] Terminal processing

[0331] The device provides an interactive screen through its user interface to answer questions about symptoms and emotions. Once the user enters information, the device organizes it and sends it to a server. The server retrieves information including the medical department and advice, and displays it to the user in a format adjusted according to their emotions.

[0332] User behavior

[0333] Users use a terminal to input detailed information about their symptoms and associated emotions. The system analyzes this input and recommends appropriate medical departments. Users can review the displayed recommendations and choose to access the appropriate medical facility with peace of mind.

[0334] Specific example

[0335] For example, if a user enters "severe headache and intense anxiety," the server receives and analyzes this information and may recommend a neurologist. At the same time, considering the user's intense anxiety, it may add advice such as, "It's understandable to be worried when you have a headache, but a qualified specialist can help. You can also try some stretches and relaxation techniques that you can do right away."

[0336] In this way, the system can comprehensively assess the user's symptoms and emotional state, enabling it to provide more personalized medical support. This improves the medical experience and facilitates smoother access to healthcare facilities.

[0337] The following describes the processing flow.

[0338] Step 1:

[0339] The user uses the device's interface to input their symptoms and the emotions they are experiencing at the time. The device provides questions and sliders to help users assess their emotions as an input aid.

[0340] Step 2:

[0341] The terminal acquires symptom and emotion data entered by the user, formats them into a unified format, and then sends them to the server.

[0342] Step 3:

[0343] The server receives symptom and emotion data sent from the terminal and first uses an emotion engine to analyze the user's emotional state. Through emotion analysis, it determines what kind of emotions the user is experiencing, such as anxiety, joy, or anger, and identifies the level of those specific emotions.

[0344] Step 4:

[0345] The server inputs the received symptom data into a generating AI model and begins analysis. The analysis results identify the most appropriate medical department. Emotional data is also taken into consideration and, if necessary, influences the selection of the medical department.

[0346] Step 5:

[0347] The server generates a list of relevant medical institutions based on the identified medical specialty information. In addition, it generates advice that reflects the user's emotional state, adjusting its expression and content accordingly.

[0348] Step 6:

[0349] The server then sends the generated medical department information, related medical institutions, and emotionally sensitive advice to the terminal.

[0350] Step 7:

[0351] The terminal uses information received from the server to display recommendations and advice for medical departments to the user. Based on sentiment data, the display method and wording are optimized to ensure that users can receive the information with confidence.

[0352] Step 8:

[0353] Users can review the displayed information and make decisions about the most appropriate healthcare provider and their next course of action. They also have the option to contact a medical professional if necessary.

[0354] (Example 2)

[0355] Next, we will describe 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".

[0356] In modern healthcare systems, it is difficult for users to quickly select the appropriate medical institution while considering their own symptoms and emotions. Furthermore, there is often insufficient information to alleviate misunderstandings and anxieties caused by self-diagnosis. As a result, users tend to make inappropriate decisions regarding access to medical care.

[0357] 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.

[0358] In this invention, the server includes an input means for receiving user input and acquiring symptom and emotional data, an analysis means for analyzing the symptom and emotional data and determining the emotional state, and a medical department recommendation means for identifying the most suitable medical department from the emotional analysis results and symptom data using generative artificial intelligence. As a result, users can receive accurate recommendations for medical departments based on their symptoms and emotional state, reducing anxiety and allowing them to choose a medical institution with confidence.

[0359] "User input" refers to information about symptoms and emotions that users enter through their devices.

[0360] "Symptom data" refers to information about physical ailments and health conditions reported by users.

[0361] "Emotional data" refers to information about a user's feelings, stress levels, anxiety, and other psychological states.

[0362] "Input means" refers to a device or software that has the function of receiving information from a user and acquiring it as data.

[0363] "Analysis means" refers to devices or algorithms that have the ability to analyze and judge the user's emotional state based on the received data.

[0364] "Generative artificial intelligence" refers to an algorithm or system that has the ability to generate optimal results based on input data.

[0365] "Medical department recommendation method" refers to a function that identifies and suggests the most suitable medical department for the user based on analyzed emotional state and symptom data.

[0366] "Information provision means" refers to means of presenting analysis results and recommended content to users visually or audibly.

[0367] "Advice generation means" refers to a system or component that has the function of creating and providing advice to alleviate anxiety, taking into account the user's emotional state.

[0368] This invention supports rapid and appropriate access to medical institutions by analyzing the user's symptoms and emotions through a medical information system and recommending the appropriate medical department.

[0369] The server receives user input data sent from the terminal. This data includes symptom information entered by the user on the interface, as well as emotional data including anxiety and stress levels specified using sliders, etc. The server analyzes the received data using software called an emotion engine to identify the user's state of mind.

[0370] The generative AI model is the core technology of this system, identifying the most appropriate medical department for the user based on analyzed emotional state and symptom data. The server inputs prompts to the generative AI model to obtain recommendations for medical departments. For example, a prompt such as, "The user entered a severe headache, accompanied by strong anxiety. Based on this, please suggest a medical department and advice," might be used.

[0371] The terminal displays medical department recommendations received from the server, along with advice tailored to the user's emotional state. Users are provided with reassuring language and guidance on the correct way to access medical facilities. The user interface is designed to present information in an intuitive and easy-to-understand format.

[0372] This system allows users to receive medical support tailored to their symptoms and feelings, and to quickly select the appropriate medical institution. The present invention aims to improve the overall medical experience by increasing access to healthcare and reducing user anxiety.

[0373] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0374] Step 1:

[0375] Users input symptoms and emotions using the terminal's user interface. The input data includes symptom information entered by the user in free-form text, as well as numerical data indicating anxiety and stress levels. This data is formatted by the terminal and prepared for transmission to the server.

[0376] Step 2:

[0377] The terminal sends data acquired from the user to the server. Symptom descriptions and emotion values ​​are sent as encoded data packets in a format that the server can securely receive. Encryption protocols are used to protect data integrity and privacy during this process.

[0378] Step 3:

[0379] The server temporarily stores the data received from the terminal in a database and passes it to the emotion engine for analysis. The emotion engine utilizes a generative AI model to analyze the user's emotional state from the symptom description. This analysis uses text mining and natural language processing techniques to identify feelings of anxiety and stress. The output generates numerical values ​​and categories that represent the user's emotional state.

[0380] Step 4:

[0381] The server uses a generative AI model to determine the most suitable medical department based on the emotion analysis results and symptom data. It sends a prompt message to the generative AI model to identify the medical department best suited to the user's symptoms and emotional state. This step outputs a list of candidate medical departments and their priorities.

[0382] Step 5:

[0383] The server generates advice that takes the user's emotional state into consideration, along with the medical department's recommendation results. The generation AI model creates emotionally sensitive text, outputting advice that includes specific and gentle words, especially to alleviate anxiety.

[0384] Step 6:

[0385] The server sends the generated medical department information and advice to the terminal. The terminal displays the information in a visually easy-to-understand format. This allows the user to select the appropriate medical department with confidence. The terminal screen is designed to include elements such as the name of the medical department, the reason for the recommendation, and emotionally-sensitive advice.

[0386] (Application Example 2)

[0387] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0388] It is not easy for users to choose the appropriate medical institution or health-related product while considering their symptoms and emotions. In particular, emotional instability can impair judgment, potentially leading to misdiagnosis or inappropriate product selection. Therefore, there is a need for more appropriate and individualized recommendations for medical institutions and products that take into account the user's emotional state.

[0389] 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.

[0390] In this invention, the server includes data analysis means for analyzing user input and emotional data to identify an appropriate medical department or product; information provision means for generating and presenting identified medical department information, product information, and related institution information to the user; and advice generation means for generating advice according to the user's emotional state. This enables the user to confidently select an appropriate medical institution and product in a way that takes their emotions into consideration.

[0391] "User input" refers to the provision of information or data input by the user to the device, including information about symptoms and emotions.

[0392] "Emotional data" refers to information about the emotions expressed by users, including data that quantifies or categorizes the degree of anxiety, stress, etc.

[0393] A "medical department" refers to a specific specialty within a medical institution, such as internal medicine, surgery, or neurology.

[0394] "Products" refer to items such as health-related products and supplements that are deemed appropriate according to the user's health condition and emotions.

[0395] "Data analysis means" refers to technical means that have the function of analyzing user input information and emotional data to identify the most suitable medical department or product.

[0396] "Information provision means" refers to technical means that generate, display, or transmit information necessary for the user based on the analysis results.

[0397] An "advice generation means" is a technical means that has the function of creating and providing appropriate advice or messages to the user based on the user's emotional state.

[0398] The system that realizes this invention is configured to run a program equipped with a generative AI model for analyzing user input and emotional data. The software primarily used includes a generative AI model, specifically OpenAI's GPT model and Hugging Face's transformers library. This allows the system to analyze emotions from the information input by the user and recommend appropriate medical departments or products.

[0399] The server receives user symptom and emotional data transmitted from the terminal and analyzes it using a generative AI model. Based on the analysis results, it identifies the appropriate medical department or product and generates related information. When providing information, personalized advice is generated according to the user's emotional state and presented to them. This process is performed in real time and aims to reduce the user's anxiety and stress.

[0400] The terminal supports information input through a user interface, designed to allow users to easily report their symptoms and feelings. The entered data is sent to a server, and the results are returned after processing is complete. Users can review the displayed medical departments, products, and advice, and choose the appropriate course of action.

[0401] An example of a prompt might be, "The user has reported insomnia and anxiety. Please recommend suitable products and create a comforting, reassuring advice message." By feeding this prompt to the AI ​​generation model, the most suitable products and advice for the user will be generated.

[0402] For example, if a user enters "I have a headache and feel anxious," the server can recommend a neurologist's consultation while also suggesting relaxation techniques and supplements that can help alleviate symptoms. In this way, the system comprehensively assesses the user's health condition and emotions and provides personalized options.

[0403] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0404] Step 1:

[0405] The user inputs information about symptoms and emotions through the terminal's user interface. The entered data is recorded as text for symptom information, and emotional states are selected using a pull-down menu or slider, or recorded as text. The terminal then organizes this data and converts it into a format for transmission to the server.

[0406] Step 2:

[0407] The server analyzes symptom information and emotional data received from the terminal. First, the received data is stored in a database, and then the emotional data is analyzed using a generative AI model. This process includes calculations to categorize the emotional data as part of data processing. As a result of the analysis, the user's emotional state and subjective health indicators are generated.

[0408] Step 3:

[0409] The server uses a generative AI model to identify the most suitable medical department or product based on the analysis results. The model is given a prompt such as, "The user is experiencing discomfort and a certain emotion. Please identify the appropriate medical department or product for this condition," and in response, it generates a list of recommended medical departments or products. The output information includes an optimal action plan for the user's symptoms and emotions.

[0410] Step 4:

[0411] The server generates advice based on the user's emotional state. Using a generative AI model, it formulates gentle messages and recommended actions that take into account the results of the emotion analysis. This process generates text using expressions that convey a sense of security and trustworthiness. The generated advice is output as text.

[0412] Step 5:

[0413] The server is built as a data package for sending results, including created medical department information, product information, and advice, to the user. This data is sent to the user's terminal and displayed on the terminal in a visually easy-to-understand format.

[0414] Step 6:

[0415] Users can review the information displayed on their device, select a medical department, and consider purchasing recommended products. They can also take actions to improve their health based on the advice provided.

[0416] 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.

[0417] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0418] 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.

[0419] [Third Embodiment]

[0420] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0421] 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.

[0422] 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).

[0423] 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.

[0424] 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.

[0425] 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).

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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.

[0431] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0432] This invention is a medical information provision system that allows users to accurately record their symptoms and receive appropriate medical advice quickly based on that information. The system uses advanced generative AI to analyze symptoms, recommend the appropriate medical department, and provide advice to reduce the risks of self-diagnosis. Furthermore, it enables communication with medical professionals as needed.

[0433] Server Processing

[0434] The server receives user symptom data from constantly connected terminals. Based on the received data, it performs analysis using AI generation to determine the most appropriate medical department for the user's symptoms. At the same time, the server refers to its built-in medical database and collects information on medical institutions corresponding to the region and symptoms.

[0435] Furthermore, the server automatically generates advice based on the analysis results, adding information to prevent misdiagnosis and delays in medical treatment. Upon user request, it provides contact information for appropriate medical professionals and offers necessary support in real time.

[0436] Terminal processing

[0437] The terminal provides a mechanism for users to input details of their symptoms via a user interface. Once the user enters their symptoms, the terminal sends this information to a server. Medical department information and advice received from the server are displayed appropriately on the terminal's screen. The terminal also presents the user with options to contact a doctor and activates communication means as needed.

[0438] User behavior

[0439] Users begin by accessing the system using their device and entering their symptoms. At this stage, users are required to provide detailed symptom information. The system analyzes the results, recommends a medical department, and displays it on the screen along with relevant hospital information. If necessary, users can immediately begin communicating with a doctor using their device.

[0440] Specific example

[0441] For example, if a user enters "sudden chest pain and shortness of breath," the server will receive this information, recommend a cardiologist, and provide a list of reputable hospitals in the user's area. It will also provide general advice on heart health and an automatically generated message explaining the importance of immediate medical attention. If the user selects "consult a doctor," the server will establish a connection with available medical professionals and immediately set up an environment where the user can contact them.

[0442] In this way, this system provides rapid and accurate medical support for users' symptoms, minimizing the risks associated with choosing a medical institution or self-diagnosis.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] The user opens the symptom input interface via their terminal and enters detailed information about their specific symptoms and the circumstances under which they occurred.

[0446] Step 2:

[0447] The terminal retrieves the symptom data entered by the user, formats it, and then sends it to the server.

[0448] Step 3:

[0449] The server launches a generative AI model to analyze the user's symptom data received from the terminal.

[0450] Step 4:

[0451] The server uses an AI model to identify the appropriate medical department based on the entered symptom data. It also references relevant medical databases to supplement this information.

[0452] Step 5:

[0453] The server generates identified medical department information and a list of recommended medical institutions, and applies advice generation methods to generate appropriate advice.

[0454] Step 6:

[0455] The server sends the generated medical department information, hospital list, and advice to the terminal.

[0456] Step 7:

[0457] The terminal uses the received information to display to the user the results of the medical department recommendation, information on related hospitals, and advice.

[0458] Step 8:

[0459] The user reviews the results and, if necessary, selects an option to communicate with a doctor from their device.

[0460] Step 9:

[0461] The device initiates communication to contact a doctor based on the user's selection and sends the necessary information to the server.

[0462] Step 10:

[0463] The server establishes a connection with the doctor and sends information to enable communication with the user.

[0464] (Example 1)

[0465] Next, we will describe 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."

[0466] In today's healthcare environment, it is crucial for users to accurately communicate their symptoms to healthcare providers and receive appropriate treatment promptly. However, many users find it difficult to assess their symptoms, leading to misdiagnosis and delays in medical care. Furthermore, finding the most suitable healthcare provider in their area quickly can be challenging, potentially negatively impacting users' health.

[0467] 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.

[0468] In this invention, the server includes information gathering means for receiving user input, data processing means for analyzing the user input and identifying the appropriate medical department, and information presentation means for referencing a built-in medical information database, generating appropriate medical department information and related medical facility information, and presenting them to the user. As a result, users can receive recommendations for the appropriate medical department simply by entering their symptoms, quickly identify the best medical institution in their area, and smoothly contact medical professionals as needed.

[0469] "Information gathering means" refers to a mechanism that provides an interface for users to input symptoms and related information, and for receiving that information.

[0470] "Data processing means" refers to algorithms and processes used to analyze received user input information and identify the appropriate medical department.

[0471] A "medical information database" is a collection of information that holds a large amount of data, including medical departments, symptoms, and regional information, and is referenced as needed.

[0472] An "information presentation means" is an output interface that presents information about medical departments and related medical facilities to users in an easy-to-understand manner.

[0473] An "advice generation system" is a system that automatically generates advice to mitigate the risks of self-diagnosis and inform users of the importance of appropriate medical treatment.

[0474] "Communication means" refers to the means that enable connection between users and medical professionals and allow for real-time communication as needed.

[0475] A "recommendation method" is a system that uses processes and algorithms to suggest the most suitable medical institutions to users, taking into account local information and reputation ratings.

[0476] To implement this invention, the server, terminal, and user each play a specific role.

[0477] The server is equipped with a dedicated generative AI model and is responsible for analyzing information received from users. This generative AI model works in conjunction with a large-scale medical information database to identify the appropriate medical department from the user's input information. The server operates on a state-of-the-art hardware environment, enabling high-speed and accurate data processing. Furthermore, it also has an advice generation function that creates advice to prevent errors caused by user self-diagnosis.

[0478] The terminal provides an interface for users to input their symptoms. This allows users to record their symptoms in detail and send them to the server. The terminal also visually displays medical department information and advice received from the server, making it easy for users to understand. Through the communication means on the terminal, users can contact medical professionals directly as needed.

[0479] The user is the central figure who inputs their symptoms using their device and receives the necessary information. For example, if a user inputs symptoms such as "sudden chest pain and shortness of breath," the server receives this information, recommends a cardiology specialist, and generates and provides a list of reputable medical institutions in the area. It also generates and presents general advice for maintaining heart health. If the user selects "Consult a doctor," the server immediately enables communication with a medical professional.

[0480] This process, supported by a generative AI model throughout the entire system, allows users to receive quick and appropriate medical support. An example of a specific prompt is input such as, "My current symptoms are sudden chest pain and shortness of breath. Which department should I go to?"

[0481] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0482] Step 1:

[0483] Users input symptoms and signs in text format using a terminal. This input data is collected through the user interface and prepared for direct transmission to the server. The input data, which includes specific symptoms and circumstances, is important for subsequent data analysis.

[0484] Step 2:

[0485] The terminal sends user input data to the server. This data is transmitted via a secure communication protocol. The server receives this input data and prepares it for analysis by the generating AI model. Data integrity is checked at this stage, and the data is validated as needed.

[0486] Step 3:

[0487] The server runs a generative AI model using the received user symptom data. It references a large medical information database to identify the most appropriate medical department based on the input data. Machine learning algorithms are used for data processing, ensuring efficient analysis. The output is information on the relevant medical department and an initial assessment based on the symptoms.

[0488] Step 4:

[0489] Based on the analysis results, the server generates information on appropriate medical departments and related medical facilities. This information is customized to take into account the user's geographical location and is configured to provide the best possible options for the user. Furthermore, advice to mitigate risks through self-diagnosis is automatically generated.

[0490] Step 5:

[0491] The terminal receives medical department information and advice transmitted from the server and presents it visually to the user. Appropriate information is clearly displayed on the user interface, providing a foundation for the user to decide on their next action. At this stage, the user can also select actions such as "consult with a doctor."

[0492] Step 6:

[0493] When a user chooses to communicate with a medical professional, the device establishes a communication method via a server. This process includes preparing for voice or video calls and configuring the system to ensure smooth contact between the user and the professional. This system allows the user to receive necessary medical advice at the appropriate time.

[0494] (Application Example 1)

[0495] Next, we will explain Application Example 1. In the following explanation, 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."

[0496] In the modern healthcare system, it is difficult for users to quickly and appropriately select a medical department and access healthcare facilities based on their symptoms. Furthermore, payment procedures after consultations are often time-consuming, which places a burden on patients. Therefore, there is a need for a system that allows users to efficiently receive medical services and make payments quickly.

[0497] 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.

[0498] In this invention, the server includes an information processing device means for receiving user input, a data analysis device means for analyzing the user input and identifying the appropriate medical department, an information providing device means for generating and presenting the identified medical department information and related institution information to the user, an advice generating device means for generating advice to reduce the risk of self-diagnosis, a communication device means for contacting actual medical professionals as needed, and an electronic payment device means for instantly electronically settling medical expenses at the relevant medical institution via the information providing device means. This enables the user to receive appropriate medical services quickly, accurately, and efficiently, and to make payments for them.

[0499] An "information processing device" is a device that receives information from a user as input, appropriately classifies and organizes that information, and has the function of transmitting necessary data to other system components.

[0500] A "data analysis device" is a device that performs analysis based on the user's input information received to identify the appropriate medical department and proposes a suitable medical department to the user.

[0501] "Information provision device means" refers to a device that generates information on medical departments and related medical institutions identified through analysis, and provides that information to the user visually or by other sensory means.

[0502] A "proposal generation device" is a device that generates necessary advice to prevent errors in self-diagnosis and provides that advice to the user in order to reduce health risks.

[0503] "Communication device means" refers to a device that provides communication means and an environment that enables users to contact actual medical professionals as needed and to communicate quickly.

[0504] An "electronic payment device" is a device that has a payment system that enables users to pay medical fees at a relevant medical institution instantly, safely, and efficiently.

[0505] A system for implementing this invention consists of a complex configuration including an information processing device, a data analysis device, an information provision device, an advice generation device, a communication device, and an electronic payment device.

[0506] The server receives symptom data in real time, transmitted from the user via an information processing device. The received data is analyzed within a data analysis device using a generative AI model to identify the appropriate medical department. In doing so, the server refers to a large medical database and collects information on relevant medical institutions.

[0507] The analysis results are transmitted to the user's terminal via an information provision device, and along with suggestions for medical institutions relevant to the user, advice to mitigate self-diagnosis risks is also displayed. The advice generation device automatically generates appropriate advice according to the risk using a generation AI model and notifies the user.

[0508] Furthermore, the communication device provides a means to establish communication with actual medical professionals as needed. The electronic payment device provides users with a means to process medical fees returned from healthcare facilities quickly and securely through the information provision device. This allows users to easily complete the entire process from booking medical services to making payments.

[0509] For example, if a user enters "acute headache and nausea," the information processing device receives this information, identifies neurology as the appropriate medical department, and presents a list of nearby medical facilities. It also provides general advice regarding symptoms, such as encouraging hydration, and offers the option to communicate with a medical professional if necessary. Regarding payment, the system is designed to allow for smooth electronic payment by integrating all information. An example of a prompt to the generating AI model is, "Identify the most relevant medical department for the symptoms the user is experiencing and recommend appropriate nearby medical facilities."

[0510] This invention solves the challenges of modern medicine, namely the need for rapid selection of medical departments and payment procedures, and provides users with an easy-to-use medical experience.

[0511] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0512] Step 1:

[0513] The user enters symptom information through the terminal's user interface. This input is collected as digital data by the information processing unit. The entered data is then sent directly to the server.

[0514] Step 2:

[0515] The server takes the received user's symptom data as input and starts analyzing it using a data analysis device with a generating AI model. This analysis compares the symptom data with a medical database to identify the most appropriate medical department related to the symptoms. As a result, information on the appropriate medical department is obtained.

[0516] Step 3:

[0517] The server outputs appropriate medical department information obtained from the data analysis device, and based on this information, the information provision device generates related medical institution information. The generated medical institution information is based on the user's location and is returned to the user's terminal.

[0518] Step 4:

[0519] The user's terminal receives information on medical departments and medical institutions transmitted from the server and displays it on the screen. Simultaneously, advice generated by the advice generation device to mitigate self-diagnosis risks is also displayed.

[0520] Step 5:

[0521] If the user requires it, the device will establish communication with actual medical professionals through communication equipment. This communication includes real-time chat, voice calls, and video calls.

[0522] Step 6:

[0523] When a user wishes to pay for medical services, the terminal activates the electronic payment device and initiates a process to instantly electronically settle the medical fees obtained from the information provider. Inputs include payment information and the medical fees, and the output confirms that the payment is securely completed via the payment network.

[0524] 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.

[0525] This invention is a medical information system that uses an emotion engine to recognize symptoms and emotions input by the user, recommends the most suitable medical department based on that information, and provides related information. The aim of this system is to provide more comprehensive and individualized medical support by analyzing the user's emotional state using the emotion engine and utilizing the results to provide other medical information and advice.

[0526] Server Processing

[0527] The server receives emotional data along with the user's symptom data sent from the terminal. This data is analyzed by the emotion engine. The resulting emotional state provides an indicator of the user's subjective health status, such as the degree of anxiety or stress they are experiencing.

[0528] The server analyzes incoming data using a generative AI model and determines the most suitable medical department, taking emotional data into consideration. Furthermore, when recommending a department, it adjusts the wording of the advice based on the user's emotional state. For example, if the user is showing high levels of anxiety, it will provide advice in a particularly gentle tone and include additional reassuring information.

[0529] Terminal processing

[0530] The device provides an interactive screen through its user interface to answer questions about symptoms and emotions. Once the user enters information, the device organizes it and sends it to a server. The server retrieves information including the medical department and advice, and displays it to the user in a format adjusted according to their emotions.

[0531] User behavior

[0532] Users use a terminal to input detailed information about their symptoms and associated emotions. The system analyzes this input and recommends appropriate medical departments. Users can review the displayed recommendations and choose to access the appropriate medical facility with peace of mind.

[0533] Specific example

[0534] For example, if a user enters "severe headache and intense anxiety," the server receives and analyzes this information and may recommend a neurologist. At the same time, considering the user's intense anxiety, it may add advice such as, "It's understandable to be worried when you have a headache, but a qualified specialist can help. You can also try some stretches and relaxation techniques that you can do right away."

[0535] In this way, the system can comprehensively assess the user's symptoms and emotional state, enabling it to provide more personalized medical support. This improves the medical experience and facilitates smoother access to healthcare facilities.

[0536] The following describes the processing flow.

[0537] Step 1:

[0538] The user uses the device's interface to input their symptoms and the emotions they are experiencing at the time. The device provides questions and sliders to help users assess their emotions as an input aid.

[0539] Step 2:

[0540] The terminal acquires symptom and emotion data entered by the user, formats them into a unified format, and then sends them to the server.

[0541] Step 3:

[0542] The server receives symptom and emotion data sent from the terminal and first uses an emotion engine to analyze the user's emotional state. Through emotion analysis, it determines what kind of emotions the user is experiencing, such as anxiety, joy, or anger, and identifies the level of those specific emotions.

[0543] Step 4:

[0544] The server inputs the received symptom data into a generating AI model and begins analysis. The analysis results identify the most appropriate medical department. Emotional data is also taken into consideration and, if necessary, influences the selection of the medical department.

[0545] Step 5:

[0546] The server generates a list of relevant medical institutions based on the identified medical specialty information. In addition, it generates advice that reflects the user's emotional state, adjusting its expression and content accordingly.

[0547] Step 6:

[0548] The server then sends the generated medical department information, related medical institutions, and emotionally sensitive advice to the terminal.

[0549] Step 7:

[0550] The terminal uses information received from the server to display recommendations and advice for medical departments to the user. Based on sentiment data, the display method and wording are optimized to ensure that users can receive the information with confidence.

[0551] Step 8:

[0552] Users can review the displayed information and make decisions about the most appropriate healthcare provider and their next course of action. They also have the option to contact a medical professional if necessary.

[0553] (Example 2)

[0554] Next, we will describe 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."

[0555] In modern healthcare systems, it is difficult for users to quickly select the appropriate medical institution while considering their own symptoms and emotions. Furthermore, there is often insufficient information to alleviate misunderstandings and anxieties caused by self-diagnosis. As a result, users tend to make inappropriate decisions regarding access to medical care.

[0556] 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.

[0557] In this invention, the server includes an input means for receiving user input and acquiring symptom and emotional data, an analysis means for analyzing the symptom and emotional data and determining the emotional state, and a medical department recommendation means for identifying the most suitable medical department from the emotional analysis results and symptom data using generative artificial intelligence. As a result, users can receive accurate recommendations for medical departments based on their symptoms and emotional state, reducing anxiety and allowing them to choose a medical institution with confidence.

[0558] "User input" refers to information about symptoms and emotions that users enter through their devices.

[0559] "Symptom data" refers to information about physical ailments and health conditions reported by users.

[0560] "Emotional data" refers to information about a user's feelings, stress levels, anxiety, and other psychological states.

[0561] "Input means" refers to a device or software that has the function of receiving information from a user and acquiring it as data.

[0562] "Analysis means" refers to devices or algorithms that have the ability to analyze and judge the user's emotional state based on the received data.

[0563] "Generative artificial intelligence" refers to an algorithm or system that has the ability to generate optimal results based on input data.

[0564] "Medical department recommendation method" refers to a function that identifies and suggests the most suitable medical department for the user based on analyzed emotional state and symptom data.

[0565] "Information provision means" refers to means of presenting analysis results and recommended content to users visually or audibly.

[0566] "Advice generation means" refers to a system or component that has the function of creating and providing advice to alleviate anxiety, taking into account the user's emotional state.

[0567] This invention supports rapid and appropriate access to medical institutions by analyzing the user's symptoms and emotions through a medical information system and recommending the appropriate medical department.

[0568] The server receives user input data sent from the terminal. This data includes symptom information entered by the user on the interface, as well as emotional data including anxiety and stress levels specified using sliders, etc. The server analyzes the received data using software called an emotion engine to identify the user's state of mind.

[0569] The generative AI model is the core technology of this system, identifying the most appropriate medical department for the user based on analyzed emotional state and symptom data. The server inputs prompts to the generative AI model to obtain recommendations for medical departments. For example, a prompt such as, "The user entered a severe headache, accompanied by strong anxiety. Based on this, please suggest a medical department and advice," might be used.

[0570] The terminal displays medical department recommendations received from the server, along with advice tailored to the user's emotional state. Users are provided with reassuring language and guidance on the correct way to access medical facilities. The user interface is designed to present information in an intuitive and easy-to-understand format.

[0571] This system allows users to receive medical support tailored to their symptoms and feelings, and to quickly select the appropriate medical institution. The present invention aims to improve the overall medical experience by increasing access to healthcare and reducing user anxiety.

[0572] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0573] Step 1:

[0574] Users input symptoms and emotions using the terminal's user interface. The input data includes symptom information entered by the user in free-form text, as well as numerical data indicating anxiety and stress levels. This data is formatted by the terminal and prepared for transmission to the server.

[0575] Step 2:

[0576] The terminal sends data acquired from the user to the server. Symptom descriptions and emotion values ​​are sent as encoded data packets in a format that the server can securely receive. Encryption protocols are used to protect data integrity and privacy during this process.

[0577] Step 3:

[0578] The server temporarily stores the data received from the terminal in a database and passes it to the emotion engine for analysis. The emotion engine utilizes a generative AI model to analyze the user's emotional state from the symptom description. This analysis uses text mining and natural language processing techniques to identify feelings of anxiety and stress. The output generates numerical values ​​and categories that represent the user's emotional state.

[0579] Step 4:

[0580] The server uses a generative AI model to determine the most suitable medical department based on the emotion analysis results and symptom data. It sends a prompt message to the generative AI model to identify the medical department best suited to the user's symptoms and emotional state. This step outputs a list of candidate medical departments and their priorities.

[0581] Step 5:

[0582] The server generates advice that takes the user's emotional state into consideration, along with the medical department's recommendation results. The generation AI model creates emotionally sensitive text, outputting advice that includes specific and gentle words, especially to alleviate anxiety.

[0583] Step 6:

[0584] The server sends the generated medical department information and advice to the terminal. The terminal displays the information in a visually easy-to-understand format. This allows the user to select the appropriate medical department with confidence. The terminal screen is designed to include elements such as the name of the medical department, the reason for the recommendation, and emotionally-sensitive advice.

[0585] (Application Example 2)

[0586] Next, we will explain application example 2. In the following explanation, 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."

[0587] It is not easy for users to choose the appropriate medical institution or health-related product while considering their symptoms and emotions. In particular, emotional instability can impair judgment, potentially leading to misdiagnosis or inappropriate product selection. Therefore, there is a need for more appropriate and individualized recommendations for medical institutions and products that take into account the user's emotional state.

[0588] 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.

[0589] In this invention, the server includes data analysis means for analyzing user input and emotional data to identify an appropriate medical department or product; information provision means for generating and presenting identified medical department information, product information, and related institution information to the user; and advice generation means for generating advice according to the user's emotional state. This enables the user to confidently select an appropriate medical institution and product in a way that takes their emotions into consideration.

[0590] "User input" refers to the provision of information or data input by the user to the device, including information about symptoms and emotions.

[0591] "Emotional data" refers to information about the emotions expressed by users, including data that quantifies or categorizes the degree of anxiety, stress, etc.

[0592] A "medical department" refers to a specific specialty within a medical institution, such as internal medicine, surgery, or neurology.

[0593] "Products" refer to items such as health-related products and supplements that are deemed appropriate according to the user's health condition and emotions.

[0594] "Data analysis means" refers to technical means that have the function of analyzing user input information and emotional data to identify the most suitable medical department or product.

[0595] "Information provision means" refers to technical means that generate, display, or transmit information necessary for the user based on the analysis results.

[0596] An "advice generation means" is a technical means that has the function of creating and providing appropriate advice or messages to the user based on the user's emotional state.

[0597] The system that realizes this invention is configured to run a program equipped with a generative AI model for analyzing user input and emotional data. The software primarily used includes a generative AI model, specifically OpenAI's GPT model and Hugging Face's transformers library. This allows the system to analyze emotions from the information input by the user and recommend appropriate medical departments or products.

[0598] The server receives user symptom and emotional data transmitted from the terminal and analyzes it using a generative AI model. Based on the analysis results, it identifies the appropriate medical department or product and generates related information. When providing information, personalized advice is generated according to the user's emotional state and presented to them. This process is performed in real time and aims to reduce the user's anxiety and stress.

[0599] The terminal supports information input through a user interface, designed to allow users to easily report their symptoms and feelings. The entered data is sent to a server, and the results are returned after processing is complete. Users can review the displayed medical departments, products, and advice, and choose the appropriate course of action.

[0600] An example of a prompt might be, "The user has reported insomnia and anxiety. Please recommend suitable products and create a comforting, reassuring advice message." By feeding this prompt to the AI ​​generation model, the most suitable products and advice for the user will be generated.

[0601] For example, if a user enters "I have a headache and feel anxious," the server can recommend a neurologist's consultation while also suggesting relaxation techniques and supplements that can help alleviate symptoms. In this way, the system comprehensively assesses the user's health condition and emotions and provides personalized options.

[0602] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0603] Step 1:

[0604] The user inputs information about symptoms and emotions through the terminal's user interface. The entered data is recorded as text for symptom information, and emotional states are selected using a pull-down menu or slider, or recorded as text. The terminal then organizes this data and converts it into a format for transmission to the server.

[0605] Step 2:

[0606] The server analyzes symptom information and emotional data received from the terminal. First, the received data is stored in a database, and then the emotional data is analyzed using a generative AI model. This process includes calculations to categorize the emotional data as part of data processing. As a result of the analysis, the user's emotional state and subjective health indicators are generated.

[0607] Step 3:

[0608] The server uses a generative AI model to identify the most suitable medical department or product based on the analysis results. The model is given a prompt such as, "The user is experiencing discomfort and a certain emotion. Please identify the appropriate medical department or product for this condition," and in response, it generates a list of recommended medical departments or products. The output information includes an optimal action plan for the user's symptoms and emotions.

[0609] Step 4:

[0610] The server generates advice based on the user's emotional state. Using a generative AI model, it formulates gentle messages and recommended actions that take into account the results of the emotion analysis. This process generates text using expressions that convey a sense of security and trustworthiness. The generated advice is output as text.

[0611] Step 5:

[0612] The server is built as a data package for sending results, including created medical department information, product information, and advice, to the user. This data is sent to the user's terminal and displayed on the terminal in a visually easy-to-understand format.

[0613] Step 6:

[0614] Users can review the information displayed on their device, select a medical department, and consider purchasing recommended products. They can also take actions to improve their health based on the advice provided.

[0615] 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.

[0616] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0617] 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.

[0618] [Fourth Embodiment]

[0619] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0620] 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.

[0621] 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).

[0622] 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.

[0623] 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.

[0624] 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).

[0625] 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.

[0626] 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 in 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.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0632] This invention is a medical information provision system that allows users to accurately record their symptoms and receive appropriate medical advice quickly based on that information. The system uses advanced generative AI to analyze symptoms, recommend the appropriate medical department, and provide advice to reduce the risks of self-diagnosis. Furthermore, it enables communication with medical professionals as needed.

[0633] Server Processing

[0634] The server receives user symptom data from constantly connected terminals. Based on the received data, it performs analysis using AI generation to determine the most appropriate medical department for the user's symptoms. At the same time, the server refers to its built-in medical database and collects information on medical institutions corresponding to the region and symptoms.

[0635] Furthermore, the server automatically generates advice based on the analysis results, adding information to prevent misdiagnosis and delays in medical treatment. Upon user request, it provides contact information for appropriate medical professionals and offers necessary support in real time.

[0636] Terminal processing

[0637] The terminal provides a mechanism for users to input details of their symptoms via a user interface. Once the user enters their symptoms, the terminal sends this information to a server. Medical department information and advice received from the server are displayed appropriately on the terminal's screen. The terminal also presents the user with options to contact a doctor and activates communication means as needed.

[0638] User behavior

[0639] Users begin by accessing the system using their device and entering their symptoms. At this stage, users are required to provide detailed symptom information. The system analyzes the results, recommends a medical department, and displays it on the screen along with relevant hospital information. If necessary, users can immediately begin communicating with a doctor using their device.

[0640] Specific example

[0641] For example, if a user enters "sudden chest pain and shortness of breath," the server will receive this information, recommend a cardiologist, and provide a list of reputable hospitals in the user's area. It will also provide general advice on heart health and an automatically generated message explaining the importance of immediate medical attention. If the user selects "consult a doctor," the server will establish a connection with available medical professionals and immediately set up an environment where the user can contact them.

[0642] In this way, this system provides rapid and accurate medical support for users' symptoms, minimizing the risks associated with choosing a medical institution or self-diagnosis.

[0643] The following describes the processing flow.

[0644] Step 1:

[0645] The user opens the symptom input interface via their terminal and enters detailed information about their specific symptoms and the circumstances under which they occurred.

[0646] Step 2:

[0647] The terminal retrieves the symptom data entered by the user, formats it, and then sends it to the server.

[0648] Step 3:

[0649] The server launches a generative AI model to analyze the user's symptom data received from the terminal.

[0650] Step 4:

[0651] The server uses an AI model to identify the appropriate medical department based on the entered symptom data. It also references relevant medical databases to supplement this information.

[0652] Step 5:

[0653] The server generates identified medical department information and a list of recommended medical institutions, and applies advice generation methods to generate appropriate advice.

[0654] Step 6:

[0655] The server sends the generated medical department information, hospital list, and advice to the terminal.

[0656] Step 7:

[0657] The terminal uses the received information to display to the user the results of the medical department recommendation, information on related hospitals, and advice.

[0658] Step 8:

[0659] The user reviews the results and, if necessary, selects an option to communicate with a doctor from their device.

[0660] Step 9:

[0661] The device initiates communication to contact a doctor based on the user's selection and sends the necessary information to the server.

[0662] Step 10:

[0663] The server establishes a connection with the doctor and sends information to enable communication with the user.

[0664] (Example 1)

[0665] Next, we will describe 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".

[0666] In today's healthcare environment, it is crucial for users to accurately communicate their symptoms to healthcare providers and receive appropriate treatment promptly. However, many users find it difficult to assess their symptoms, leading to misdiagnosis and delays in medical care. Furthermore, finding the most suitable healthcare provider in their area quickly can be challenging, potentially negatively impacting users' health.

[0667] 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.

[0668] In this invention, the server includes information gathering means for receiving user input, data processing means for analyzing the user input and identifying the appropriate medical department, and information presentation means for referencing a built-in medical information database, generating appropriate medical department information and related medical facility information, and presenting them to the user. As a result, users can receive recommendations for the appropriate medical department simply by entering their symptoms, quickly identify the best medical institution in their area, and smoothly contact medical professionals as needed.

[0669] "Information gathering means" refers to a mechanism that provides an interface for users to input symptoms and related information, and for receiving that information.

[0670] "Data processing means" refers to algorithms and processes used to analyze received user input information and identify the appropriate medical department.

[0671] A "medical information database" is a collection of information that holds a large amount of data, including medical departments, symptoms, and regional information, and is referenced as needed.

[0672] An "information presentation means" is an output interface that presents information about medical departments and related medical facilities to users in an easy-to-understand manner.

[0673] An "advice generation system" is a system that automatically generates advice to mitigate the risks of self-diagnosis and inform users of the importance of appropriate medical treatment.

[0674] "Communication means" refers to the means that enable connection between users and medical professionals and allow for real-time communication as needed.

[0675] A "recommendation method" is a system that uses processes and algorithms to suggest the most suitable medical institutions to users, taking into account local information and reputation ratings.

[0676] To implement this invention, the server, terminal, and user each play a specific role.

[0677] The server is equipped with a dedicated generative AI model and is responsible for analyzing information received from users. This generative AI model works in conjunction with a large-scale medical information database to identify the appropriate medical department from the user's input information. The server operates on a state-of-the-art hardware environment, enabling high-speed and accurate data processing. Furthermore, it also has an advice generation function that creates advice to prevent errors caused by user self-diagnosis.

[0678] The terminal provides an interface for users to input their symptoms. This allows users to record their symptoms in detail and send them to the server. The terminal also visually displays medical department information and advice received from the server, making it easy for users to understand. Through the communication means on the terminal, users can contact medical professionals directly as needed.

[0679] The user is the central figure who inputs their symptoms using their device and receives the necessary information. For example, if a user inputs symptoms such as "sudden chest pain and shortness of breath," the server receives this information, recommends a cardiology specialist, and generates and provides a list of reputable medical institutions in the area. It also generates and presents general advice for maintaining heart health. If the user selects "Consult a doctor," the server immediately enables communication with a medical professional.

[0680] This process, supported by a generative AI model throughout the entire system, allows users to receive quick and appropriate medical support. An example of a specific prompt is input such as, "My current symptoms are sudden chest pain and shortness of breath. Which department should I go to?"

[0681] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0682] Step 1:

[0683] Users input symptoms and signs in text format using a terminal. This input data is collected through the user interface and prepared for direct transmission to the server. The input data, which includes specific symptoms and circumstances, is important for subsequent data analysis.

[0684] Step 2:

[0685] The terminal sends user input data to the server. This data is transmitted via a secure communication protocol. The server receives this input data and prepares it for analysis by the generating AI model. Data integrity is checked at this stage, and the data is validated as needed.

[0686] Step 3:

[0687] The server runs a generative AI model using the received user symptom data. It references a large medical information database to identify the most appropriate medical department based on the input data. Machine learning algorithms are used for data processing, ensuring efficient analysis. The output is information on the relevant medical department and an initial assessment based on the symptoms.

[0688] Step 4:

[0689] Based on the analysis results, the server generates information on appropriate medical departments and related medical facilities. This information is customized to take into account the user's geographical location and is configured to provide the best possible options for the user. Furthermore, advice to mitigate risks through self-diagnosis is automatically generated.

[0690] Step 5:

[0691] The terminal receives medical department information and advice transmitted from the server and presents it visually to the user. Appropriate information is clearly displayed on the user interface, providing a foundation for the user to decide on their next action. At this stage, the user can also select actions such as "consult with a doctor."

[0692] Step 6:

[0693] When a user chooses to communicate with a medical professional, the device establishes a communication method via a server. This process includes preparing for voice or video calls and configuring the system to ensure smooth contact between the user and the professional. This system allows the user to receive necessary medical advice at the appropriate time.

[0694] (Application Example 1)

[0695] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0696] In the modern healthcare system, it is difficult for users to quickly and appropriately select a medical department and access healthcare facilities based on their symptoms. Furthermore, payment procedures after consultations are often time-consuming, which places a burden on patients. Therefore, there is a need for a system that allows users to efficiently receive medical services and make payments quickly.

[0697] 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.

[0698] In this invention, the server includes an information processing device means for receiving user input, a data analysis device means for analyzing the user input and identifying the appropriate medical department, an information providing device means for generating and presenting the identified medical department information and related institution information to the user, an advice generating device means for generating advice to reduce the risk of self-diagnosis, a communication device means for contacting actual medical professionals as needed, and an electronic payment device means for instantly electronically settling medical expenses at the relevant medical institution via the information providing device means. This enables the user to receive appropriate medical services quickly, accurately, and efficiently, and to make payments for them.

[0699] An "information processing device" is a device that receives information from a user as input, appropriately classifies and organizes that information, and has the function of transmitting necessary data to other system components.

[0700] A "data analysis device" is a device that performs analysis based on the user's input information received to identify the appropriate medical department and proposes a suitable medical department to the user.

[0701] "Information provision device means" refers to a device that generates information on medical departments and related medical institutions identified through analysis, and provides that information to the user visually or by other sensory means.

[0702] A "proposal generation device" is a device that generates necessary advice to prevent errors in self-diagnosis and provides that advice to the user in order to reduce health risks.

[0703] "Communication device means" refers to a device that provides communication means and an environment that enables users to contact actual medical professionals as needed and to communicate quickly.

[0704] An "electronic payment device" is a device that has a payment system that enables users to pay medical fees at a relevant medical institution instantly, safely, and efficiently.

[0705] A system for implementing this invention consists of a complex configuration including an information processing device, a data analysis device, an information provision device, an advice generation device, a communication device, and an electronic payment device.

[0706] The server receives symptom data in real time, transmitted from the user via an information processing device. The received data is analyzed within a data analysis device using a generative AI model to identify the appropriate medical department. In doing so, the server refers to a large medical database and collects information on relevant medical institutions.

[0707] The analysis results are transmitted to the user's terminal via an information provision device, and along with suggestions for medical institutions relevant to the user, advice to mitigate self-diagnosis risks is also displayed. The advice generation device automatically generates appropriate advice according to the risk using a generation AI model and notifies the user.

[0708] Furthermore, the communication device provides a means to establish communication with actual medical professionals as needed. The electronic payment device provides users with a means to process medical fees returned from healthcare facilities quickly and securely through the information provision device. This allows users to easily complete the entire process from booking medical services to making payments.

[0709] For example, if a user enters "acute headache and nausea," the information processing device receives this information, identifies neurology as the appropriate medical department, and presents a list of nearby medical facilities. It also provides general advice regarding symptoms, such as encouraging hydration, and offers the option to communicate with a medical professional if necessary. Regarding payment, the system is designed to allow for smooth electronic payment by integrating all information. An example of a prompt to the generating AI model is, "Identify the most relevant medical department for the symptoms the user is experiencing and recommend appropriate nearby medical facilities."

[0710] This invention solves the challenges of modern medicine, namely the need for rapid selection of medical departments and payment procedures, and provides users with an easy-to-use medical experience.

[0711] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0712] Step 1:

[0713] The user enters symptom information through the terminal's user interface. This input is collected as digital data by the information processing unit. The entered data is then sent directly to the server.

[0714] Step 2:

[0715] The server takes the received user's symptom data as input and starts analyzing it using a data analysis device with a generating AI model. This analysis compares the symptom data with a medical database to identify the most appropriate medical department related to the symptoms. As a result, information on the appropriate medical department is obtained.

[0716] Step 3:

[0717] The server outputs appropriate medical department information obtained from the data analysis device, and based on this information, the information provision device generates related medical institution information. The generated medical institution information is based on the user's location and is returned to the user's terminal.

[0718] Step 4:

[0719] The user's terminal receives information on medical departments and medical institutions transmitted from the server and displays it on the screen. Simultaneously, advice generated by the advice generation device to mitigate self-diagnosis risks is also displayed.

[0720] Step 5:

[0721] If the user requires it, the device will establish communication with actual medical professionals through communication equipment. This communication includes real-time chat, voice calls, and video calls.

[0722] Step 6:

[0723] When a user wishes to pay for medical services, the terminal activates the electronic payment device and initiates a process to instantly electronically settle the medical fees obtained from the information provider. Inputs include payment information and the medical fees, and the output confirms that the payment is securely completed via the payment network.

[0724] 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.

[0725] This invention is a medical information system that uses an emotion engine to recognize symptoms and emotions input by the user, recommends the most suitable medical department based on that information, and provides related information. The aim of this system is to provide more comprehensive and individualized medical support by analyzing the user's emotional state using the emotion engine and utilizing the results to provide other medical information and advice.

[0726] Server Processing

[0727] The server receives emotional data along with the user's symptom data sent from the terminal. This data is analyzed by the emotion engine. The resulting emotional state provides an indicator of the user's subjective health status, such as the degree of anxiety or stress they are experiencing.

[0728] The server analyzes incoming data using a generative AI model and determines the most suitable medical department, taking emotional data into consideration. Furthermore, when recommending a department, it adjusts the wording of the advice based on the user's emotional state. For example, if the user is showing high levels of anxiety, it will provide advice in a particularly gentle tone and include additional reassuring information.

[0729] Terminal processing

[0730] The device provides an interactive screen through its user interface to answer questions about symptoms and emotions. Once the user enters information, the device organizes it and sends it to a server. The server retrieves information including the medical department and advice, and displays it to the user in a format adjusted according to their emotions.

[0731] User behavior

[0732] Users use a terminal to input detailed information about their symptoms and associated emotions. The system analyzes this input and recommends appropriate medical departments. Users can review the displayed recommendations and choose to access the appropriate medical facility with peace of mind.

[0733] Specific example

[0734] For example, if a user enters "severe headache and intense anxiety," the server receives and analyzes this information and may recommend a neurologist. At the same time, considering the user's intense anxiety, it may add advice such as, "It's understandable to be worried when you have a headache, but a qualified specialist can help. You can also try some stretches and relaxation techniques that you can do right away."

[0735] In this way, the system can comprehensively assess the user's symptoms and emotional state, enabling it to provide more personalized medical support. This improves the medical experience and facilitates smoother access to healthcare facilities.

[0736] The following describes the processing flow.

[0737] Step 1:

[0738] The user uses the device's interface to input their symptoms and the emotions they are experiencing at the time. The device provides questions and sliders to help users assess their emotions as an input aid.

[0739] Step 2:

[0740] The terminal acquires symptom and emotion data entered by the user, formats them into a unified format, and then sends them to the server.

[0741] Step 3:

[0742] The server receives symptom and emotion data sent from the terminal and first uses an emotion engine to analyze the user's emotional state. Through emotion analysis, it determines what kind of emotions the user is experiencing, such as anxiety, joy, or anger, and identifies the level of those specific emotions.

[0743] Step 4:

[0744] The server inputs the received symptom data into a generating AI model and begins analysis. The analysis results identify the most appropriate medical department. Emotional data is also taken into consideration and, if necessary, influences the selection of the medical department.

[0745] Step 5:

[0746] The server generates a list of relevant medical institutions based on the identified medical specialty information. In addition, it generates advice that reflects the user's emotional state, adjusting its expression and content accordingly.

[0747] Step 6:

[0748] The server then sends the generated medical department information, related medical institutions, and emotionally sensitive advice to the terminal.

[0749] Step 7:

[0750] The terminal uses information received from the server to display recommendations and advice for medical departments to the user. Based on sentiment data, the display method and wording are optimized to ensure that users can receive the information with confidence.

[0751] Step 8:

[0752] Users can review the displayed information and make decisions about the most appropriate healthcare provider and their next course of action. They also have the option to contact a medical professional if necessary.

[0753] (Example 2)

[0754] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0755] In modern healthcare systems, it is difficult for users to quickly select the appropriate medical institution while considering their own symptoms and emotions. Furthermore, there is often insufficient information to alleviate misunderstandings and anxieties caused by self-diagnosis. As a result, users tend to make inappropriate decisions regarding access to medical care.

[0756] 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.

[0757] In this invention, the server includes an input means for receiving user input and acquiring symptom and emotional data, an analysis means for analyzing the symptom and emotional data and determining the emotional state, and a medical department recommendation means for identifying the most suitable medical department from the emotional analysis results and symptom data using generative artificial intelligence. As a result, users can receive accurate recommendations for medical departments based on their symptoms and emotional state, reducing anxiety and allowing them to choose a medical institution with confidence.

[0758] "User input" refers to information about symptoms and emotions that users enter through their devices.

[0759] "Symptom data" refers to information about physical ailments and health conditions reported by users.

[0760] "Emotional data" refers to information about a user's feelings, stress levels, anxiety, and other psychological states.

[0761] "Input means" refers to a device or software that has the function of receiving information from a user and acquiring it as data.

[0762] "Analysis means" refers to devices or algorithms that have the ability to analyze and judge the user's emotional state based on the received data.

[0763] "Generative artificial intelligence" refers to an algorithm or system that has the ability to generate optimal results based on input data.

[0764] "Medical department recommendation method" refers to a function that identifies and suggests the most suitable medical department for the user based on analyzed emotional state and symptom data.

[0765] "Information provision means" refers to means of presenting analysis results and recommended content to users visually or audibly.

[0766] "Advice generation means" refers to a system or component that has the function of creating and providing advice to alleviate anxiety, taking into account the user's emotional state.

[0767] This invention supports rapid and appropriate access to medical institutions by analyzing the user's symptoms and emotions through a medical information system and recommending the appropriate medical department.

[0768] The server receives user input data sent from the terminal. This data includes symptom information entered by the user on the interface, as well as emotional data including anxiety and stress levels specified using sliders, etc. The server analyzes the received data using software called an emotion engine to identify the user's state of mind.

[0769] The generative AI model is the core technology of this system, identifying the most appropriate medical department for the user based on analyzed emotional state and symptom data. The server inputs prompts to the generative AI model to obtain recommendations for medical departments. For example, a prompt such as, "The user entered a severe headache, accompanied by strong anxiety. Based on this, please suggest a medical department and advice," might be used.

[0770] The terminal displays medical department recommendations received from the server, along with advice tailored to the user's emotional state. Users are provided with reassuring language and guidance on the correct way to access medical facilities. The user interface is designed to present information in an intuitive and easy-to-understand format.

[0771] This system allows users to receive medical support tailored to their symptoms and feelings, and to quickly select the appropriate medical institution. The present invention aims to improve the overall medical experience by increasing access to healthcare and reducing user anxiety.

[0772] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0773] Step 1:

[0774] Users input symptoms and emotions using the terminal's user interface. The input data includes symptom information entered by the user in free-form text, as well as numerical data indicating anxiety and stress levels. This data is formatted by the terminal and prepared for transmission to the server.

[0775] Step 2:

[0776] The terminal sends data acquired from the user to the server. Symptom descriptions and emotion values ​​are sent as encoded data packets in a format that the server can securely receive. Encryption protocols are used to protect data integrity and privacy during this process.

[0777] Step 3:

[0778] The server temporarily stores the data received from the terminal in a database and passes it to the emotion engine for analysis. The emotion engine utilizes a generative AI model to analyze the user's emotional state from the symptom description. This analysis uses text mining and natural language processing techniques to identify feelings of anxiety and stress. The output generates numerical values ​​and categories that represent the user's emotional state.

[0779] Step 4:

[0780] The server uses a generative AI model to determine the most suitable medical department based on the emotion analysis results and symptom data. It sends a prompt message to the generative AI model to identify the medical department best suited to the user's symptoms and emotional state. This step outputs a list of candidate medical departments and their priorities.

[0781] Step 5:

[0782] The server generates advice that takes the user's emotional state into consideration, along with the medical department's recommendation results. The generation AI model creates emotionally sensitive text, outputting advice that includes specific and gentle words, especially to alleviate anxiety.

[0783] Step 6:

[0784] The server sends the generated medical department information and advice to the terminal. The terminal displays the information in a visually easy-to-understand format. This allows the user to select the appropriate medical department with confidence. The terminal screen is designed to include elements such as the name of the medical department, the reason for the recommendation, and emotionally-sensitive advice.

[0785] (Application Example 2)

[0786] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0787] It is not easy for users to choose the appropriate medical institution or health-related product while considering their symptoms and emotions. In particular, emotional instability can impair judgment, potentially leading to misdiagnosis or inappropriate product selection. Therefore, there is a need for more appropriate and individualized recommendations for medical institutions and products that take into account the user's emotional state.

[0788] 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.

[0789] In this invention, the server includes data analysis means for analyzing user input and emotional data to identify an appropriate medical department or product; information provision means for generating and presenting identified medical department information, product information, and related institution information to the user; and advice generation means for generating advice according to the user's emotional state. This enables the user to confidently select an appropriate medical institution and product in a way that takes their emotions into consideration.

[0790] "User input" refers to the provision of information or data input by the user to the device, including information about symptoms and emotions.

[0791] "Emotional data" refers to information about the emotions expressed by users, including data that quantifies or categorizes the degree of anxiety, stress, etc.

[0792] A "medical department" refers to a specific specialty within a medical institution, such as internal medicine, surgery, or neurology.

[0793] "Products" refer to items such as health-related products and supplements that are deemed appropriate according to the user's health condition and emotions.

[0794] "Data analysis means" refers to technical means that have the function of analyzing user input information and emotional data to identify the most suitable medical department or product.

[0795] "Information provision means" refers to technical means that generate, display, or transmit information necessary for the user based on the analysis results.

[0796] An "advice generation means" is a technical means that has the function of creating and providing appropriate advice or messages to the user based on the user's emotional state.

[0797] The system that realizes this invention is configured to run a program equipped with a generative AI model for analyzing user input and emotional data. The software primarily used includes a generative AI model, specifically OpenAI's GPT model and Hugging Face's transformers library. This allows the system to analyze emotions from the information input by the user and recommend appropriate medical departments or products.

[0798] The server receives user symptom and emotional data transmitted from the terminal and analyzes it using a generative AI model. Based on the analysis results, it identifies the appropriate medical department or product and generates related information. When providing information, personalized advice is generated according to the user's emotional state and presented to them. This process is performed in real time and aims to reduce the user's anxiety and stress.

[0799] The terminal supports information input through a user interface, designed to allow users to easily report their symptoms and feelings. The entered data is sent to a server, and the results are returned after processing is complete. Users can review the displayed medical departments, products, and advice, and choose the appropriate course of action.

[0800] An example of a prompt might be, "The user has reported insomnia and anxiety. Please recommend suitable products and create a comforting, reassuring advice message." By feeding this prompt to the AI ​​generation model, the most suitable products and advice for the user will be generated.

[0801] For example, if a user enters "I have a headache and feel anxious," the server can recommend a neurologist's consultation while also suggesting relaxation techniques and supplements that can help alleviate symptoms. In this way, the system comprehensively assesses the user's health condition and emotions and provides personalized options.

[0802] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0803] Step 1:

[0804] The user inputs information about symptoms and emotions through the terminal's user interface. The entered data is recorded as text for symptom information, and emotional states are selected using a pull-down menu or slider, or recorded as text. The terminal then organizes this data and converts it into a format for transmission to the server.

[0805] Step 2:

[0806] The server analyzes symptom information and emotional data received from the terminal. First, the received data is stored in a database, and then the emotional data is analyzed using a generative AI model. This process includes calculations to categorize the emotional data as part of data processing. As a result of the analysis, the user's emotional state and subjective health indicators are generated.

[0807] Step 3:

[0808] The server uses a generative AI model to identify the most suitable medical department or product based on the analysis results. The model is given a prompt such as, "The user is experiencing discomfort and a certain emotion. Please identify the appropriate medical department or product for this condition," and in response, it generates a list of recommended medical departments or products. The output information includes an optimal action plan for the user's symptoms and emotions.

[0809] Step 4:

[0810] The server generates advice based on the user's emotional state. Using a generative AI model, it formulates gentle messages and recommended actions that take into account the results of the emotion analysis. This process generates text using expressions that convey a sense of security and trustworthiness. The generated advice is output as text.

[0811] Step 5:

[0812] The server is built as a data package for sending results, including created medical department information, product information, and advice, to the user. This data is sent to the user's terminal and displayed on the terminal in a visually easy-to-understand format.

[0813] Step 6:

[0814] Users can review the information displayed on their device, select a medical department, and consider purchasing recommended products. They can also take actions to improve their health based on the advice provided.

[0815] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 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.

[0816] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0817] In the above embodiment, an example was given in which the 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 robot 414.

[0818] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0819] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0820] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0821] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0822] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0823] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0824] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0825] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0826] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0827] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0828] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0829] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0830] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0831] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0832] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0833] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0834] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0835] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0836] The following is further disclosed regarding the embodiments described above.

[0837] (Claim 1)

[0838] A terminal means for receiving user input,

[0839] A data analysis means for analyzing the user input and identifying the appropriate medical department,

[0840] Information provision means for generating and presenting the identified medical department information and related institution information to the user,

[0841] An advice generation method for generating advice to reduce the risk of self-diagnosis,

[0842] Communication methods to contact actual medical professionals as needed,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] The system according to claim 1, further comprising processing means for processing user input in real time.

[0846] (Claim 3)

[0847] The system according to claim 1, further comprising a recommendation means for recommending the most suitable medical institution based on the medical department information proposed by the system.

[0848] "Example 1"

[0849] (Claim 1)

[0850] Information collection means for receiving user input,

[0851] A data processing means for analyzing the user input and identifying the appropriate medical department,

[0852] An information presentation means that refers to a built-in medical information database, generates appropriate medical department information and related medical facility information, and presents it to the user.

[0853] An advisory generation method that reduces the risk of self-diagnosis and generates advice that informs users of the importance of medical intervention,

[0854] A means of communication to contact appropriate medical professionals in response to user requests,

[0855] A system that includes this.

[0856] (Claim 2)

[0857] The system according to claim 1, comprising a display means that processes the input in real time when a user inputs symptoms and displays the generated medical department information and medical facility information.

[0858] (Claim 3)

[0859] The system according to claim 1, comprising a recommendation means that recommends the most suitable medical facility based on medical treatment department information proposed by the system and evaluates its reputation according to the user's region.

[0860] "Application Example 1"

[0861] (Claim 1)

[0862] Information processing device means for receiving user input,

[0863] A data analysis device means that analyzes the user input and identifies the appropriate medical department,

[0864] Information provision device means that generates the identified medical department information and related institution information and presents it to the user,

[0865] An advice generation device means for generating advice to reduce the risk of self-diagnosis,

[0866] Communication equipment and means for contacting actual medical professionals as needed,

[0867] An electronic payment device means that instantly electronically settles medical expenses at a related medical institution via the information provision device means,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, comprising a processing device that processes user input in real time and enables electronic payment.

[0871] (Claim 3)

[0872] The system according to claim 1, further comprising a recommendation device means that recommends the most suitable medical facility based on medical department information proposed by the system and processes the medical fees immediately.

[0873] "Example 2 of combining an emotion engine"

[0874] (Claim 1)

[0875] An input means for receiving user input and acquiring symptom and emotion data,

[0876] An analytical means for analyzing the symptom and emotional data and determining the emotional state,

[0877] A medical department recommendation method that uses generative artificial intelligence to identify the most suitable medical department from emotion analysis results and symptom data,

[0878] Information provision means for generating advice tailored based on the identified medical department information and emotional state,

[0879] An advice generation means that presents the advice to the user and provides information to alleviate anxiety,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, comprising a processing means that, when a user inputs symptoms and emotions, processes the input in real time and recommends a medical department using generative artificial intelligence.

[0883] (Claim 3)

[0884] The system according to claim 1, comprising means for reducing user anxiety and guiding them to confidently choose a medical institution by providing advice based on medical department information and emotional state proposed by the system.

[0885] "Application example 2 when combining with an emotional engine"

[0886] (Claim 1)

[0887] A terminal means for receiving user input,

[0888] A data analysis means that analyzes the user input and emotional data to identify the appropriate medical department or product,

[0889] Information provision means for generating and presenting the identified medical department information, product information, and related institution information to the user,

[0890] An advice generation method that generates advice according to emotional state,

[0891] Communication methods to contact actual medical professionals and product providers as needed,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, comprising a processing means that processes the input in real time when a user inputs symptoms and emotions, and provides emotion-based product recommendations.

[0895] (Claim 3)

[0896] The system according to claim 1, further comprising a recommendation means for recommending the most suitable medical institution and purchasing method based on the medical department information and product information proposed by the system. [Explanation of Symbols]

[0897] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A terminal means for receiving user input, A data analysis means for analyzing the user input and identifying the appropriate medical department, Information provision means for generating and presenting the identified medical department information and related institution information to the user, An advice generation method for generating advice to reduce the risk of self-diagnosis, Communication methods to contact actual medical professionals as needed, A system that includes this.

2. The system according to claim 1, further comprising processing means for processing user input in real time.

3. The system according to claim 1, further comprising a recommendation means for recommending the most suitable medical institution based on the medical department information proposed by the system.

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