system

Abstract

We provide the system. [Solution] A means for users to input changes in their physical condition in natural language, A means for analyzing the input natural language and extracting relevant keywords, A means for searching a database for information on countermeasures, health supplements, and medical institutions based on the extracted keywords, Means for displaying the aforementioned search results to the user, A means for obtaining user feedback and storing it in the database, A means for optimizing search results based on the aforementioned feedback, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, due to busy lives, stress, etc., many people are experiencing various physical changes. However, it is difficult to perform self-diagnosis and find appropriate countermeasures, and there is a need for means that can respond appropriately without visiting a medical institution. In addition, there is a lack of a system that can provide optimal countermeasures according to individual physical conditions and lifestyles. Furthermore, there is an increasing need for a system that not only provides general countermeasures but also utilizes feedback from users to provide personalized responses.

Means for Solving the Problems

[0005] To solve the above-mentioned problems, the present invention provides the following means: a means for the user to input changes in their physical condition in natural language, a means for analyzing the input natural language and extracting relevant keywords; a means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords; a means for displaying the search results to the user and a means for obtaining and storing user feedback in the database; and finally, a means for optimizing the search results based on the feedback, thereby constructing a system that can quickly provide the user with effective and personalized remedies.

[0006] A "user" refers to an individual who uses this system to consult about changes in their physical condition and obtain advice on how to deal with them and related information.

[0007] "Natural language" refers to the language that humans use on a daily basis (e.g., Japanese, English, etc.), and in this system, it is one of the means used when users input changes in their physical condition.

[0008] "Natural language processing" is a technique that processes input natural language and extracts meaning from it, and it is used as a specific processing method in this system.

[0009] "Related keywords" are terms that indicate changes in physical condition or symptoms based on user input, extracted through natural language processing.

[0010] A "database" is an information management system used to store information about treatments, health supplements, and medical institutions, and is used for searching and displaying results within this system.

[0011] "Solutions" refer to specific methods and advice for dealing with changes in the user's physical condition, and are one of the pieces of information that are searched and displayed in the database.

[0012] "Health supplements" refer to foods and supplements consumed with the expectation of having an effect on specific symptoms or physical conditions, and in this system, they are provided to users as recommended information.

[0013] "Medical institutions" refer to facilities that provide medical services, such as hospitals and clinics. This system provides information on relevant medical institutions based on the user's location.

[0014] "Feedback" refers to information that users input into this system, including their evaluations and results of the solutions and information they have provided. This feedback is accumulated and used to optimize the system.

[0015] "Optimization" is the process of improving the way search results and solutions are provided based on user feedback, with the aim of enhancing the effectiveness of the system. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] Shows an emotion map on which a plurality of emotions are mapped. [Figure 10] Shows an emotion map on which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 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 Embodiment 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.

Mode for Carrying Out the Invention

[0017] 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. [[ID=Z7]]

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of 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.

[0020] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. The specific operation of the system is described below.

[0038] 1. User processing

[0039] 1. Enter your health status

[0040] The user opens the application on their device and enters changes in their physical condition in natural language. For example, they might enter, "I've been feeling a bit anemic lately."

[0041] Once the user has finished entering the information, they click the "Submit" button.

[0042] 2. Terminal processing

[0043] 1. Input acquisition and transmission

[0044] The terminal retrieves the user's input and stores it as data.

[0045] The terminal formats the input data and converts it into a format that can be sent to the server.

[0046] Send the formatted data to the server.

[0047] 3. Server processing

[0048] 1. Input Analysis

[0049] The server analyzes the received data. Specifically, it uses a natural language processing (NLP) program to analyze the input "feeling anemic."

[0050] The analysis extracts relevant keywords (e.g., "anemia," "iron deficiency").

[0051] 2. Obtaining related data

[0052] The server searches the database for appropriate solutions based on the extracted keywords. For example, it might find solutions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[0053] The system uses relevant health supplements (e.g., "iron supplements") and the user's location information to retrieve information about nearby medical facilities.

[0054] 3. Generating and sending responses

[0055] The server consolidates the search results into a single response message. Specifically, it includes the following information:

[0056] List of solutions

[0057] Recommended health supplements

[0058] Information on the nearest medical institution

[0059] The server sends the generated response message to the terminal.

[0060] 4. Terminal processing (continued)

[0061] 1. Obtaining and displaying the response

[0062] The terminal receives and analyzes the response from the server.

[0063] Display the analysis results to the user. For example:

[0064] "To combat anemia, try the following: 1) Eat iron-rich foods, 2) Take iron with vitamin C, 3) Get plenty of rest."

[0065] "Recommended health supplement: Iron supplements"

[0066] "Nearest medical institution: ○○ Clinic (address and contact information)"

[0067] 5. User processing (continued)

[0068] 1. Implementation of countermeasures and provision of feedback

[0069] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[0070] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[0071] 6. Terminal Processing (continued)

[0072] 1. Obtaining and sending feedback

[0073] The device collects user feedback and sends it to the server.

[0074] 7. Server processing (continued)

[0075] 1. Accumulation and optimization of feedback

[0076] The server saves the received feedback to the database.

[0077] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[0078] This allows us to adjust the priority of solutions based on user feedback and improve the accuracy of the system.

[0079] Specific example

[0080] For example, if a user enters "I feel a bit anemic" and submits it, the server analyzes the input and extracts the keyword "anemia." Next, it searches its database for possible solutions such as "eating iron-rich foods," "taking vitamin C along with iron," and "getting rest," and recommends these to the user. It also simultaneously provides information on iron supplements and a guide to a medical institution near the user's home (e.g., "○○ Clinic"). The user then implements these solutions based on this information and provides the results as feedback to the system. This feedback is used to optimize the search results for the next time.

[0081] In this way, the system of the present invention supports the user's health management and enables continuous improvement.

[0082] The following describes the processing flow.

[0083] Step 1:

[0084] The user enters a change in their physical condition. The user opens the application on their device, types "I feel a bit anemic" in natural language into the text input field, and clicks the "Send" button.

[0085] Step 2:

[0086] The terminal obtains user input. The terminal retrieves the data "I feel a bit anemic" from the text input field and converts it into an internal data format.

[0087] Step 3:

[0088] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[0089] Step 4:

[0090] The server receives the data. The server receives the data "I feel a bit anemic" sent from the terminal and passes it to the analysis program.

[0091] Step 5:

[0092] The server performs natural language analysis. Using natural language processing (NLP) tools, the server extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I feel a bit anemic."

[0093] Step 6:

[0094] The server searches the database. Based on the extracted keywords, it searches the database for solutions, health supplements, and medical institution information.

[0095] Step 7:

[0096] The server compiles the search results. It combines the suggested solutions obtained from the search results (e.g., "Eat foods rich in iron," "Take vitamin C"), health supplements (e.g., "Iron supplements"), and information on nearby medical facilities into a single response message.

[0097] Step 8:

[0098] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[0099] Step 9:

[0100] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[0101] Step 10:

[0102] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. For example, the displayed content might be: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic."

[0103] Step 11:

[0104] The user implements the suggested course of action. The user follows the course of action provided by the system, either purchasing the recommended supplement or seeking medical attention.

[0105] Step 12:

[0106] Users provide feedback. Users enter feedback on the effectiveness of the implemented solutions and click the "Submit" button.

[0107] Step 13:

[0108] The device retrieves the feedback. The device retrieves the feedback content from the text input field and converts it into a data format.

[0109] Step 14:

[0110] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[0111] Step 15:

[0112] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[0113] Step 16:

[0114] The server optimizes based on the feedback. It analyzes the received feedback and evaluates the effectiveness of the solutions. This information is used in subsequent search processes to help adjust the priority of solutions.

[0115] This series of processes allows users to quickly and effectively obtain ways to deal with changes in their physical condition, and the system is gradually optimized through feedback.

[0116] (Example 1)

[0117] 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."

[0118] In modern society, users need quick and accurate ways to respond to daily changes in their physical condition. However, for the average user, managing their health and finding appropriate treatment methods is difficult. In particular, for users who do not accurately recognize their own symptoms and lack specialized knowledge, it is difficult to determine what actions to take. Against this backdrop, there is a need for a system that can quickly and accurately analyze changes in the user's physical condition, provide optimal treatment methods, and continuously optimize the system itself based on feedback.

[0119] 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.

[0120] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means including a generative AI model for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user, means for obtaining feedback from the user and storing it in the database, and means for continuously optimizing the search results based on the feedback. As a result, the user can quickly obtain appropriate remedies for changes in their physical condition, and the system itself is continuously improved through feedback, enabling more accurate responses.

[0121] A "user" refers to an individual who uses the system to input their health information and receive appropriate treatment.

[0122] A "terminal" is a device used by a user to access a system, and includes mobile devices and computers.

[0123] "Natural language" refers to the language used in everyday conversation that users use to input changes in their physical condition.

[0124] A "generative AI model" refers to artificial intelligence technology that analyzes natural language data input by users and extracts relevant keywords.

[0125] "Analysis" refers to the process of using generative AI models to process natural language data input by users and extract important information.

[0126] "Keywords" are important words or phrases extracted through analysis, and include information related to changes in the user's physical condition.

[0127] "Solutions" refer to specific actions or advice that users should take based on the extracted keywords.

[0128] "Health supplements" refer to nutritional supplements and vitamins recommended to support the user's health.

[0129] "Medical institutions" refer to facilities such as hospitals and clinics that users can visit to receive appropriate medical treatment.

[0130] A "database" refers to a centralized location where information on treatments, health supplements, and medical institutions is stored.

[0131] "Feedback" refers to information that users provide to the system, evaluating the effectiveness of the solutions and advice offered by the system.

[0132] "Optimization" refers to the process of improving and refining the system's search results and suggestions based on feedback.

[0133] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Specific embodiments for carrying out this invention are described in detail below.

[0134] System Configuration

[0135] This system consists of a multi-stage process that includes user input, data processing by the terminal, and analysis and optimization by the server. The following describes how each of these processes is implemented.

[0136] User processing

[0137] The user uses the application on their device to input changes in their physical condition in natural language. For example, they might input, "I've been feeling a bit anemic lately." This input is captured as text on the application. Once the user has finished inputting, they click the "Submit" button to send the data to the next processing step.

[0138] Terminal processing

[0139] The terminal retrieves user input and first stores it as text data. The software used here is the application interface; for example, Kotlin or Swift are often used for mobile apps, while React or Angular are often used for web apps. Next, the retrieved text data is formatted and converted into a format such as JSON that can be sent to the server. Scripting languages ​​such as Python or JavaScript are used for this process. The formatted data is sent to the server using the HTTPS protocol.

[0140] Server Processing

[0141] The server receives data sent from the terminal and first temporarily stores it in a database. Databases such as MySQL® and PostgreSQL are used. Next, the received data is analyzed using a generative AI model. Specifically, NLP models such as BERT (Bidirectional Encoder Representations from Transformers) and GPT-3® (Generative Pre-trained Transformer 3) are used. Through analysis, relevant keywords (e.g., "anemia," "iron deficiency") are extracted from the text. The server then searches the database for appropriate solutions based on the extracted keywords. For example, it might use SQL queries to find suggestions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[0142] Next, the system retrieves information about nearby medical facilities using relevant health supplements (e.g., "iron supplements") and the user's location. This information is then combined into a single response message as search results, and the server sends the generated response message back to the device.

[0143] Terminal response processing

[0144] The terminal receives response messages from the server, parses them, and formats them into a format that can be displayed on the user interface. JavaScript and HTML are often used in the display portion of the application. The analysis results are then displayed to the user. Specifically, the following information is included: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take it with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," "Nearest medical institution: XX Clinic (address and contact information)."

[0145] User feedback

[0146] The user implements the suggested solution and inputs the results as feedback into the application on their device. Once the input is complete, they click the "Submit" button. This feedback is then sent from the device to the server.

[0147] Server feedback processing

[0148] The server stores user feedback in a database. This data is stored in a dedicated table for accumulating user feedback information. Subsequently, statistical analysis is performed based on this feedback data to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches.

[0149] Specific example

[0150] For example, if a user enters "I've been feeling a bit anemic lately" into the device and clicks the "Send" button, the device receives the input, formats it, and sends it to the server. The server analyzes the received data using an NLP model and extracts keywords such as "anemia" and "iron deficiency." Next, it searches the database for solutions such as "consume iron-rich foods," "take vitamin C along with it," and "get rest," and retrieves information on nearby medical facilities along with this information to generate a response. The device receives this response and displays it to the user.

[0151] Users implement solutions and provide feedback on their effectiveness to the system. Based on this feedback, the system is continuously optimized, resulting in more accurate search results in the future.

[0152] Example of a prompt

[0153] "What are some recommended ways to increase iron intake when experiencing symptoms of anemia?"

[0154] In this way, the system of the present invention supports the user's health management, and through continuous system improvement, it enables the provision of more efficient and accurate treatment methods.

[0155] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0156] Step 1: User enters their health status.

[0157] The user opens the application on their device. Next, they input changes in their physical condition or symptoms they are experiencing in natural language. For example, they might input, "I've been feeling a bit anemic lately." Once they have finished inputting, they click the submit button. Thus, the input in this step is the user's natural language text, and the output is the data sent to the device.

[0158] Step 2: Data acquisition and formatting on the device

[0159] The terminal receives natural language text sent by the user. Next, it processes this input data and converts it into a format that can be sent to the server (e.g., JSON). Scripting languages ​​such as Python or JavaScript are used for this process. The input for this step is the user's natural language text, and the output is formatted JSON data. The formatted data is then sent to the server via the HTTPS protocol.

[0160] Step 3: Receiving and temporarily storing data on the server

[0161] The server receives JSON data sent from the terminal. The received data is temporarily stored in a database. Databases such as MySQL or PostgreSQL are used. The input for this step is formatted JSON data, and the output is the information stored in the database.

[0162] Step 4: Natural Language Processing (NLP)

[0163] The server uses a generative AI model to analyze the stored data. Specifically, NLP models such as BERT and GPT-3 extract relevant keywords from natural language text. The input for this step is temporarily stored data, and the output is the extracted keywords. For example, keywords such as "anemia" and "iron deficiency" are extracted.

[0164] Step 5: Retrieve relevant data from the database

[0165] The server searches the database for information on remedies, health supplements, and medical institutions based on the extracted keywords. Using SQL queries, it finds information such as iron-rich foods, ways to consume vitamin C together, and ways to get enough rest. The input for this step is the extracted keywords, and the output is the retrieved information on remedies and medical institutions.

[0166] Step 6: Response generation and sending

[0167] The server generates a response message based on the retrieved information. This message includes the following information: a list of countermeasures, recommended health supplements, and information on the nearest medical facility. The generated response message is sent to the terminal. The input for this step is the search result data, and the output is the generated response message.

[0168] Step 7: Receiving and analyzing the terminal's response

[0169] The terminal receives and analyzes the response message from the server. It then formats the analysis results into a format that can be displayed on the user interface. The input for this step is the response message from the server, and the output is the information displayed on the user interface. Specific examples of the displayed information include: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take iron with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," and "Nearest medical institution: XX Clinic (address and contact information)."

[0170] Step 8: User implements corrective action and enters feedback.

[0171] The user implements the suggested solutions, such as purchasing supplements or visiting a medical institution. Afterward, they evaluate whether the provided solutions were effective and enter feedback. Once feedback is complete, they click the "Submit" button. The input in this step is the user's feedback, and the output is the submitted feedback data.

[0172] Step 9: Obtain and send feedback from the device.

[0173] The terminal receives user feedback and formats it into a format that can be sent to the server. The input for this step is the user feedback, and the output is the formatted feedback data. The formatted data is then sent to the server.

[0174] Step 10: Server feedback accumulation and optimization

[0175] The server stores the received feedback data in a database. Based on this feedback data, statistical analysis is performed to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches. The input for this step is the feedback data, and the output is the optimized search algorithm. This allows for continuous improvement of the system through feedback.

[0176] (Application Example 1)

[0177] 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."

[0178] Conventional medical support systems made it difficult for users to obtain the information necessary to appropriately address changes in their own health. Furthermore, the lack of means to continuously optimize the system based on feedback made it difficult to provide personalized and appropriate medical information. As a result, users were unable to manage their health quickly and accurately, leading to a decrease in the efficiency of health management.

[0179] 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.

[0180] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user on a visual display device or virtual store, means for obtaining feedback from the user and storing it in the database, means for optimizing the search results based on the feedback, and means for using a generative AI model to suggest remedies and related information corresponding to the changes in physical condition within the virtual store. This allows the user to obtain quick and accurate remedies for changes in their physical condition, and the system is optimized based on the feedback, enabling the provision of personalized and appropriate medical information.

[0181] "User" refers to an individual or legal entity that uses the system.

[0182] "Changes in physical condition" refers to changes or abnormalities in the user's health status.

[0183] "Natural language" refers to the words and sentences that humans use on a daily basis, and does not require any special format or structure for input.

[0184] "Related keywords" refer to words or phrases related to changes in physical condition that the user enters in natural language.

[0185] "Solutions" refer to methods that indicate appropriate responses or improvements to changes in the user's physical condition.

[0186] "Health supplements" refer to substances or products consumed to maintain or promote health.

[0187] A "medical institution" refers to a facility or organization where doctors provide medical care.

[0188] A "database" refers to a system or device for systematically storing and managing large amounts of data.

[0189] A "visual display device" refers to a device such as a monitor or display used to show information to a user.

[0190] A "virtual store" refers to a virtual shop that provides goods and services on the internet.

[0191] "Feedback" refers to the act of users returning feedback on the effectiveness and evaluation of the solutions or information they have provided, as well as the content of that feedback.

[0192] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to generate and analyze information.

[0193] "Optimization" refers to making adjustments and improvements to maximize the performance and efficiency of a system.

[0194] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on that feedback. The system begins with the user inputting changes in their physical condition in natural language.

[0195] System program

[0196] The system is built using the following hardware and software:

[0197] Hardware:

[0198] Mobile devices or information processing devices (smartphones, personal computers, tablets, etc.)

[0199] Visual display devices (monitors, displays, etc.)

[0200] software:

[0201] Natural Language Processing (NLP): Natural Language Toolkit (nltk)

[0202] Server program: Flask

[0203] Machine learning models: scikit-learn

[0204] Database Management System (DBMS)

[0205] Processing procedure

[0206] The server receives information about changes in the user's physical condition in natural language, entered through a mobile device or information processing device. Next, it analyzes the input using natural language processing technology and extracts relevant keywords. Specifically, if the user enters "I've been getting tired easily lately," the server analyzes this input and extracts the keyword "gets tired easily."

[0207] Based on these extracted keywords, the server searches the database for information on appropriate treatments, health supplements, and medical institutions. The search results are then presented to the user as optimal treatments and relevant information using a generative AI model.

[0208] For example, if a user enters "I've been feeling tired lately," the server will search its database for solutions based on the keyword "feeling tired," such as "get enough sleep," "eat a balanced diet," and "reduce stress." It will also simultaneously provide information on health supplements like "iron supplements" and information on nearby medical facilities, such as "○○ Clinic (address and contact information)."

[0209] Users implement the suggested solutions and input their results into the system as feedback. This feedback is collected and stored on the server and used as reference in subsequent search and selection processes. This allows the system's accuracy and efficiency to continuously improve based on user feedback.

[0210] Specific example

[0211] When a user enters "I've been feeling tired lately," the system suggests the most suitable solutions based on that input. For example, it might suggest "getting enough sleep," "eating a balanced diet," or "reducing stress." At the same time, it provides information on nearby medical facilities based on the user's location. Furthermore, it may also display a purchase link for "iron supplements" as a health supplement.

[0212] Example of a prompt

[0213] Please suggest solutions for the user who enters "I've been feeling tired lately." Please also include relevant health supplements and information on the nearest medical facilities.

[0214] In this way, the system of the present invention can continue to support the user's health management and improve the accuracy of providing individualized information.

[0215] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0216] Step 1:

[0217] Users input changes in their physical condition using natural language via a mobile device or information processing device. For example, they might input, "I've been feeling tired lately." After inputting the information, the user clicks the "Submit" button.

[0218] Input: User's natural language description of changes in their physical condition (e.g., "I've been feeling tired lately").

[0219] Output: Natural language input data

[0220] Step 2:

[0221] The terminal acquires the user's natural language input data, formats it, and sends it to the server. The formatted data is often converted to JSON or XML format.

[0222] Input: User's natural language input data (e.g., "I've been feeling tired lately")

[0223] Data processing: Formatting natural language input into JSON or XML.

[0224] Output: Formatted data

[0225] Step 3:

[0226] The server receives formatted data sent from the terminal. The received data is analyzed using a natural language processing (NLP) program, and relevant keywords are extracted. For example, the keyword "easily fatigued" might be extracted.

[0227] Input: Formatted data (e.g., "I've been feeling tired lately")

[0228] Data processing: Keyword extraction using Natural Language Processing (NLP)

[0229] Output: Extracted keywords (e.g., "easily fatigued")

[0230] Step 4:

[0231] The server searches the database for appropriate treatments, health supplements, and medical information based on the extracted keywords. The search results are optimized using a generative AI model for presentation to the user.

[0232] Input: Extracted keywords (e.g., "easily fatigued")

[0233] Data Search: Search for relevant information from the database.

[0234] Data processing: Optimizing information using generative AI models.

[0235] Output: Optimized treatment methods, health supplements, and healthcare information.

[0236] Step 5:

[0237] The server sends optimized information to the terminal. This information includes a list of solutions, recommendations for health supplements, and information on the nearest medical facilities.

[0238] Input: Optimized treatment methods, health supplements, medical institution information

[0239] Data processing: Packaging and transmission of information

[0240] Output: Packaged data

[0241] Step 6:

[0242] The terminal receives data from the server and displays it to the user. The user can view the information through a visual display device. Specifically, this includes lists of countermeasures (e.g., "Get enough sleep," "Eat a balanced diet," "Reduce stress"), recommendations for health supplements (e.g., "Iron supplements"), and information on the nearest medical institution (e.g., "○○ Clinic").

[0243] Input: Packaged data received from the server

[0244] Data processing: Parsing and displaying received data

[0245] Output: Information displayed to the user

[0246] Step 7:

[0247] Users implement the suggested solutions and provide feedback on their effectiveness. They input the effects and evaluations in natural language and click the "Submit" button.

[0248] Input: User feedback (e.g., "I feel less tired")

[0249] Output: Natural language feedback data

[0250] Step 8:

[0251] The device then sends the user's feedback data back to the server. This allows the feedback to be accumulated in the system.

[0252] Input: User's natural language feedback data

[0253] Data processing: Format conversion of natural language feedback

[0254] Output: Formatted feedback data

[0255] Step 9:

[0256] The server receives feedback data and stores it in a database. The stored feedback data is statistically analyzed and used to optimize search results for future searches.

[0257] Input: Formatted feedback data

[0258] Data processing: Accumulation and statistical analysis of feedback data.

[0259] Output: Optimized search algorithm

[0260] Thus, the system of the present invention provides the optimal course of action based on changes in the user's physical condition, and realizes a process in which the system is continuously optimized through that feedback.

[0261] 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.

[0262] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[0263] 1. User processing

[0264] 1. Enter your health status

[0265] Users open the application on their device and input changes in their physical condition using natural language. For example, they might input "I've been feeling a bit anemic lately" and also input any anxiety they feel as a result.

[0266] Once the user has finished entering the information, they click the "Submit" button.

[0267] 2. Terminal processing

[0268] 1. Input acquisition and transmission

[0269] The device acquires user input and stores it as data. This data may include not only text data but also audio data.

[0270] The terminal formats the input data and converts it into a format that can be sent to the server.

[0271] Send the formatted data to the server.

[0272] 3. Server processing

[0273] 1. Input Analysis

[0274] The server analyzes the received data. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the input sentence "I feel a bit anemic."

[0275] If voice data is included, use a voice analysis tool to identify the content and emotion of the speech.

[0276] 2. Recognition by the Emotion Engine

[0277] The server uses an emotion engine to recognize the user's emotional state (e.g., "nervous", "anxious", "relaxed") from the analyzed data.

[0278] 3. Retrieval of Related Data

[0279] Based on the extracted keywords and the recognized emotional state, search the database for appropriate coping methods, health supplements, and medical institution information. For example, measures such as "ingest foods rich in iron", "ingest vitamin C together", and "take a rest" may be found.

[0280] If the user's emotional state is recognized as "nervous", advice to relieve it can also be included.

[0281] 4. Generation and Transmission of Responses

[0282] The server combines the search results into a single response message. Specifically, it includes the following information:

[0283] List of coping methods

[0284] Recommended health supplements

[0285] Information on the nearest medical institutions

[0286] Additional psychological advice (e.g., "take deep breaths to relax")

[0287] The server transmits the generated response message to the terminal.

[0288] 4. Processing by the Terminal (Continued) <​​1. Obtaining and displaying the response

[0290] The terminal receives a response from the server and analyzes its contents.

[0291] The analysis results are displayed in a format that is easy for the user to understand. For example, the displayed content might include: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to help you relax."

[0292] 5. User processing (continued)

[0293] 1. Implementation of countermeasures and provision of feedback

[0294] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[0295] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[0296] 6. Terminal Processing (continued)

[0297] 1. Obtaining and sending feedback

[0298] The device collects user feedback and sends it to the server.

[0299] 7. Server processing (continued)

[0300] 1. Accumulation and optimization of feedback

[0301] The server saves the received feedback to the database.

[0302] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[0303] Based on this, it is possible to adjust the priority of countermeasures and improve the accuracy of the system according to the feedback from the user.

[0304] Specific example

[0305] For example, when the user inputs "I've been feeling anemic lately" and states "I'm very anxious" verbally, the server analyzes the input and extracts the keyword "anemia" and the emotional state of "anxiety". In addition to countermeasures such as "ingesting iron-rich foods", "ingesting with vitamin C", and "taking a rest" retrieved from the database, the server also searches for psychological advice such as "performing deep breathing to relax" and provides it to the user. Based on this information, the user practices the necessary countermeasures and provides feedback on the results to contribute to the optimization of the system.

[0306] In this way, the system of the present invention can provide quick and effective health management support while considering the psychological state of the user.

[0307] The following describes the processing flow.

[0308] Step 1:

[0309] The user inputs a change in physical condition. The user opens the application on the terminal, inputs "I've been feeling anemic lately" in natural language in the text input field, and also inputs the emotion towards that state (e.g., "I'm very anxious"). Click the "Send" button.

[0310] Step 2:

[0311] The terminal acquires the user's input. The terminal acquires the data of "I've been feeling anemic lately" and "I'm very anxious" from the text input field and converts it into an internal data format.

[0312] Step 3:

[0313] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[0314] Step 4:

[0315] The server receives the data. The server receives the user input data sent from the terminal ("I've been feeling anemic lately" and "I'm very anxious") and passes it to the analysis program.

[0316] Step 5:

[0317] The server performs natural language analysis. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I've been feeling a bit anemic lately."

[0318] Step 6:

[0319] The server performs emotion recognition using an emotion engine. From the input "I am very anxious," the emotion engine recognizes the emotional state as "anxiety."

[0320] Step 7:

[0321] The server searches the database. Based on the extracted keywords "anemia" and emotional state "anxiety," it searches the database for appropriate treatments, health supplements, and medical institution information.

[0322] Step 8:

[0323] The server compiles the search results. It combines the suggested solutions (e.g., "Consume foods rich in iron," "Consume vitamin C together," "Get rest"), health supplements (e.g., "Iron supplements"), information on nearby medical facilities, and psychological advice to alleviate anxiety (e.g., "Take deep breaths to relax") into a single response message.

[0324] Step 9:

[0325] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[0326] Step 10:

[0327] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[0328] Step 11:

[0329] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. The displayed content may include statements such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. We also recommend deep breathing to alleviate anxiety. The nearest clinic is XX Clinic."

[0330] Step 12:

[0331] The user implements coping strategies. The user practices the coping strategies provided by the system, such as purchasing supplements or visiting a medical institution. They may also follow advice to alleviate anxiety, such as practicing deep breathing.

[0332] Step 13:

[0333] The user provides feedback. The user enters feedback on the effectiveness of the implemented countermeasures and clicks the "Submit" button to send it to their device.

[0334] Step 14:

[0335] The device retrieves the feedback. The device retrieves the feedback content (e.g., "The iron supplement worked") from the text input field and converts it into a data format.

[0336] Step 15:

[0337] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[0338] Step 16:

[0339] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[0340] Step 17:

[0341] The server optimizes based on feedback. It analyzes received feedback (e.g., "iron supplements worked") and evaluates the effectiveness of the suggested solutions. This information is used in subsequent search processes to help adjust the priority of suggested solutions.

[0342] This series of processes allows users to acquire coping mechanisms to respond quickly and effectively to changes in their physical condition, and the system is continuously optimized through user feedback. Furthermore, the combination of emotional engines enables detailed responses that also take into account the user's psychological state.

[0343] (Example 2)

[0344] 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".

[0345] Conventional medical support systems have a problem in that they do not adequately suggest the most suitable treatment methods or health supplements in response to changes in the user's physical condition. Furthermore, advice provided without considering the user's psychological state is often ineffective. In addition, there is a lack of mechanisms to continuously optimize the system using user feedback. Therefore, there is a need for a system that can more effectively support users' health management.

[0346] 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.

[0347] In this invention, the server includes means for the user to input changes in their physical condition in natural language and voice data; means for analyzing the input natural language and voice data and extracting relevant keywords and emotional states; means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords and emotional states; means for displaying the search results to the user; means for obtaining feedback from the user and storing it in the database; and means for optimizing the search results based on the feedback. This enables the provision of remedies that take into account the user's changes in physical condition and psychological state, and continuous optimization of the system using feedback.

[0348] A "user" refers to an individual who uses the system to input changes in their physical condition and emotional state.

[0349] "Changes in physical condition" refers to a state in which a user expresses, in natural language, any abnormalities or problems they have experienced regarding their physical condition.

[0350] "Natural language" refers to language used by humans on a daily basis, and is not limited to any specific form of language description.

[0351] "Audio data" refers to data that records the content of what a user has said in digital format.

[0352] "Analysis" refers to the process of mechanically analyzing input natural language or audio data to identify and classify its meaning and emotions.

[0353] "Keywords" refer to important words extracted from analyzed natural language and speech data.

[0354] "Emotional state" refers to the user's psychological state, which the system identifies through analysis of voice data and other information.

[0355] "Solutions" refer to specific examples of actions or measures suggested in response to changes in the user's physical condition.

[0356] "Health supplements" refer to foods and supplements consumed with the purpose of supporting or improving the user's health.

[0357] "Medical institution information" refers to information about medical facilities such as hospitals and clinics where users can receive treatment.

[0358] A "database" refers to a collection of data that stores and allows searching for information such as treatment methods, health supplements, and medical institutions.

[0359] "Searching" refers to the process of extracting data that matches specific criteria from information stored in a database.

[0360] "Feedback" refers to the act of a user sending back information to the system regarding the effectiveness and satisfaction level of the solutions provided.

[0361] "Optimization" refers to the process by which a system improves its search algorithms and methods of providing solutions based on user feedback, thereby increasing the accuracy of search results in subsequent searches.

[0362] This invention is a medical support system that considers the user's physical and psychological changes, provides the optimal course of action accordingly, and continuously optimizes the system based on feedback. The system analyzes the user's natural language and voice input to identify keywords indicating changes in physical condition and emotional states. This enables more effective health management support.

[0363] Hardware and software to be used

[0364] Devices: Smartphones, tablets, PCs, etc.

[0365] Server: An information processing device with high-performance computing capabilities.

[0366] Natural language processing tools: Google® Cloud Natural Language API, IBM Watson® Natural Language Understanding.

[0367] Speech analysis tools: Google Cloud Speech-to-Text, Amazon Transcribe.

[0368] Emotion recognition engine: Microsoft® Azure® Emotion API, Affectiva SDK.

[0369] Database: A database that stores information on treatments, health supplements, and medical institutions.

[0370] System Operation Description

[0371] This system operates using the following steps.

[0372] 1. User's physical condition information and emotional input

[0373] Users open the application on their device and input changes in their physical condition using natural language. For example, they might type, "I've been feeling a bit anemic lately," and then use voice input to say, "I'm very anxious."

[0374] 2. Sending input data

[0375] The terminal formats the acquired text and audio data and sends it to the server.

[0376] 3. Data analysis on the server

[0377] The server analyzes the received data. It uses natural language processing tools to extract relevant keywords such as "anemia" from the text data. It converts the audio data into text using speech analysis tools and identifies emotional states (e.g., "anxiety") using an emotion recognition engine.

[0378] 4. Searching for and generating solutions

[0379] Based on the extracted keywords and emotional state, the server searches the database for appropriate coping strategies, health supplements, and medical information. This may include advice such as "consume iron-rich foods" or "visit a nearby clinic." Furthermore, considering that the emotional state is "anxiety," it may also include additional advice such as "take deep breaths to relax."

[0380] 5. Displaying search results

[0381] The device displays search results received from the server. For example, it might show advice such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax."

[0382] 6. User Feedback

[0383] Users who implement the solution will input feedback regarding its effectiveness and their satisfaction level, and this feedback will also be sent to the server via their device.

[0384] 7. Accumulation and optimization of feedback

[0385] The server stores feedback data in a database and statistically analyzes the effectiveness of the countermeasures. Based on the results of this analysis, the system is optimized to improve the accuracy of subsequent search processes.

[0386] Specific example

[0387] For example, if a user types "I've been feeling a bit anemic lately" and says "I'm very anxious" via voice, the server extracts the keyword "anemia" and the emotional state "anxiety." Based on this, the server searches the database for coping strategies such as "eat iron-rich foods," "take vitamin C along with it," and "get rest," as well as psychological advice such as "take deep breaths to relax," and provides these to the user. The user then uses this information to implement the necessary coping strategies and provides feedback on the results to help optimize the system.

[0388] As a result, the system of the present invention can provide rapid and effective health management support while taking into account the user's physical condition and psychological state.

[0389] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0390] Step 1:

[0391] Users input changes in their physical condition into the device using natural language and voice. For example, they might type "I've been feeling a bit anemic lately" into the text input field and then say "I'm very worried" into the microphone.

[0392] Input: Natural language text and audio data

[0393] Output: Text and audio data temporarily stored on the device.

[0394] Step 2:

[0395] The terminal formats the user's input data. Specifically, it converts text data to JSON format and saves audio data as an audio file. This converts the data into a format that can be transmitted.

[0396] Input: Natural language text and audio data

[0397] Output: Formatted JSON text data and audio files

[0398] Step 3:

[0399] The terminal sends the formatted data to the server. The data is sent using a communication protocol (e.g., HTTP).

[0400] Input: Formatted JSON text data and audio files

[0401] Output: Text and audio data sent to the server

[0402] Step 4:

[0403] The server analyzes the received data. Using natural language processing tools, it extracts keywords related to solutions from the text data. Simultaneously, it converts audio data into text using speech analysis tools and identifies the user's emotional state using an emotion recognition engine.

[0404] Input: Text data and audio data

[0405] Output: Extracted keywords (e.g., "anemia") and emotional states (e.g., "anxiety")

[0406] Step 5:

[0407] The server searches the database for relevant information based on the extracted keywords and emotional state. It retrieves coping strategies, health supplements, and medical information. This includes specific advice such as "consume iron-rich foods" or "visit a nearby clinic."

[0408] Input: Keywords and emotional state

[0409] Output: Search results (solutions, health supplements, medical institution information, etc.)

[0410] Step 6:

[0411] The server generates search results as a response message. It then summarizes specific advice into a single message and sends it to the terminal.

[0412] Input: Search Results

[0413] Output: Response message (Example: "Please increase your iron intake. Here are some recommended supplements.")

[0414] Step 7:

[0415] The terminal analyzes the response message received from the server and displays it to the user. For example, it might be displayed as a message box on the application screen.

[0416] Input: Response message

[0417] Output: Display of the analyzed message

[0418] Step 8:

[0419] The user implements the provided solution. For example, they might purchase and take an iron supplement. Afterwards, they input feedback on the effectiveness and satisfaction level of the solution and send it to their device.

[0420] Input: Feedback on solutions

[0421] Output: Feedback data

[0422] Step 9:

[0423] The device formats the user's feedback data and sends it to the server. This allows the feedback to be reflected in the system.

[0424] Input: Feedback data

[0425] Output: Feedback data sent to the server

[0426] Step 10:

[0427] The server accumulates feedback data and analyzes it statistically. Based on this, it evaluates the effectiveness of the countermeasures and optimizes the search process for subsequent searches.

[0428] Input: Feedback data

[0429] Output: Optimized search algorithms and a list of solutions

[0430] This allows the system to take into account changes in the user's physical and psychological state and continuously provide optimized solutions.

[0431] (Application Example 2)

[0432] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0433] Traditional health management systems can provide basic coping strategies based on changes in a user's physical condition, but they struggle to offer strategies that take into account the user's emotional state. Furthermore, their limited ability to optimize the system based on feedback made it difficult to provide optimal solutions for individual users. This highlights the need for flexible health management support tailored to the user's psychological state.

[0434] 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.

[0435] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on treatment methods, health supplements, and medical institutions based on the extracted keywords and emotional state, means for displaying the search results to the user, means for obtaining user feedback and storing it in the database, means for optimizing the search results based on the feedback, and further means for emotion recognition. This makes it possible to provide the optimal treatment method that simultaneously considers the user's physical condition and emotions.

[0436] A "user" is someone who uses the system to input changes in their physical condition and emotions.

[0437] "Natural language" refers to the language that humans use on a daily basis, and is used by users to input changes in their physical condition and emotions.

[0438] A "natural language input method" refers to a device or program that provides an interface for users to input changes in their physical condition or emotions in natural language.

[0439] "Analysis means" refers to a device or program that has the function of analyzing input natural language and extracting relevant keywords.

[0440] "Keywords" are highly relevant words or phrases extracted from the input natural language using analysis tools.

[0441] "Emotional state" refers to the psychological state of a user, as recognized by analytical methods.

[0442] "Emotion recognition means" refers to a device or program used to determine a user's psychological state from natural language or speech input.

[0443] "Solutions" refer to methods and means of health management provided based on the user's physical and emotional state.

[0444] "Health supplements" refer to foods and supplements recommended to users for the purpose of maintaining or restoring health.

[0445] "Medical institution information" refers to information such as contact details and addresses of clinics, hospitals, and other medical facilities that provide the medical services that users need.

[0446] A "database" is a collection of data that stores and manages information such as treatment methods, health supplements, and medical institutions in a searchable format.

[0447] A "search tool" refers to a device or program that has the function of extracting necessary information from a database.

[0448] "Display means" refers to a device or program that has the function of visualizing and providing search results to the user.

[0449] "Feedback" refers to information provided to the system about the effectiveness and impressions of the solutions implemented by the user.

[0450] An "optimization tool" is a device or program that has the function of improving the system's search results or solutions based on the feedback it receives.

[0451] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[0452] 1. System Configuration

[0453] This system consists of the following main components:

[0454] User device: (e.g., smartphone or computer)

[0455] Natural language input method: An interface for users to input changes in their physical condition or emotions using natural language.

[0456] Display method: An interface for displaying search results and solutions to the user.

[0457] server:

[0458] Analysis method: Software (e.g., Transformers library) for analyzing user-inputted natural language data and extracting relevant keywords and emotional states.

[0459] Emotion recognition means: Software for identifying a user's emotional state.

[0460] Search method: Software for searching databases for relevant treatments, health supplements, and information on medical institutions.

[0461] Optimization method: Software to improve search results based on feedback provided by users.

[0462] 2. Usage of Hardware and Software

[0463] User terminal:

[0464] Install an application that runs on a smartphone or computer. The user uses this application to input changes in their physical condition and emotions in natural language.

[0465] server:

[0466] The server uses generative AI models for natural language processing and emotion recognition. Specifically, it uses Python and the Transformers library. It analyzes user input and recognizes emotional states.

[0467] An API (Application Programming Interface) endpoint will be set up to communicate with the database and search for information on appropriate treatments, health supplements, and medical institutions.

[0468] After receiving feedback from users, the system is optimized based on statistical analysis.

[0469] 3. Specific Examples

[0470] For example, if a user enters "I've been feeling a bit anemic lately," the server analyzes this input and extracts the keyword "anemia." Simultaneously, it uses an emotion recognition engine to determine the user's feelings and recognize that the user is feeling anxious. The server then provides advice from its database as a solution, such as "consume iron-rich foods," "it's recommended to take them with vitamin C," and "take deep breaths to relax." This allows the user to implement the necessary solutions and provide feedback to the system.

[0471] 4. Example of a prompt statement

[0472] The following are examples of prompts that the user will enter:

[0473] "I've been feeling a bit anemic lately. I'm very worried. What can I do?"

[0474] "I've had a persistent headache. Which medicine would you recommend?"

[0475] "I can't shake off this fatigue. Do you have any recommendations for solutions?"

[0476] Based on these inputs, the system can perform appropriate analysis and searches, and propose the optimal course of action.

[0477] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0478] Step 1:

[0479] Users input changes in their physical condition and emotions into the device using natural language. Specifically, they open a smartphone application and enter text such as, "I've been feeling anemic lately. I'm very worried." The input data is text data in natural language format.

[0480] Step 2:

[0481] The terminal retrieves natural language text entered by the user and prepares an API request to send it to the server. The terminal converts the input text data into JSON format and sends it to the server. The input is the user's input text, and the output is the JSON data sent to the server.

[0482] Step 3:

[0483] The server parses the received JSON data and processes the input natural language to extract keywords. Specifically, it uses a generative AI model (e.g., the Transformers library) to extract keywords such as "anemia" and "anxiety." The input is JSON data, and the output is a list of extracted keywords.

[0484] Step 4:

[0485] The server uses an emotion recognition engine to identify the user's emotional state. Specifically, it uses an emotion recognition model to extract emotions (e.g., "anxiety," "restlessness") from text. The input is the user's text data, and the output is the identified emotional state.

[0486] Step 5:

[0487] The server searches its database for relevant coping strategies, health supplements, and healthcare information based on extracted keywords and emotional states. The server generates search queries and retrieves relevant information from a pre-stored database. Inputs are keywords and emotional states, while output is a list of coping strategies and recommended information.

[0488] Step 6:

[0489] The server consolidates the search results into a single response message and sends it to the terminal. Specifically, it generates a response that includes a list of solutions, recommended health supplements, information on the nearest medical facility, and additional psychological advice. The input is the search results, and the output is the response message.

[0490] Step 7:

[0491] The terminal analyzes the received response message and displays it in a user-friendly format. Specifically, it displays messages such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax," on the application screen. The input is the response message, and the output is the content displayed to the user.

[0492] Step 8:

[0493] The user implements the displayed solution and inputs the results as feedback. Specifically, they use the application to input the effectiveness and their impressions of the solution, such as "It was effective" or "My tension eased." The feedback data is then converted back into JSON format and sent from the terminal to the server. The input is the user's feedback text, and the output is the JSON data sent to the server.

[0494] Step 9:

[0495] The server analyzes the received feedback data and stores it in a database. Furthermore, it performs statistical analysis based on the feedback to continuously optimize search results and solutions. This data is then used for future search and selection processes. The input is feedback data, and the output is an updated database and an optimized list of solutions.

[0496] 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.

[0497] 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.

[0498] 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.

[0499] [Second Embodiment]

[0500] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0501] 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.

[0502] 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).

[0503] 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.

[0504] 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.

[0505] 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).

[0506] 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.

[0507] 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.

[0508] 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.

[0509] 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.

[0510] 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.

[0511] 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".

[0512] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. The specific operation of the system is described below.

[0513] 1. User processing

[0514] 1. Enter your health status

[0515] The user opens the application on their device and enters changes in their physical condition in natural language. For example, they might enter, "I've been feeling a bit anemic lately."

[0516] Once the user has finished entering the information, they click the "Submit" button.

[0517] 2. Terminal processing

[0518] 1. Input acquisition and transmission

[0519] The terminal retrieves the user's input and stores it as data.

[0520] The terminal formats the input data and converts it into a format that can be sent to the server.

[0521] Send the formatted data to the server.

[0522] 3. Server processing

[0523] 1. Input Analysis

[0524] The server analyzes the received data. Specifically, it uses a natural language processing (NLP) program to analyze the input "feeling anemic."

[0525] The analysis extracts relevant keywords (e.g., "anemia," "iron deficiency").

[0526] 2. Obtaining related data

[0527] The server searches the database for appropriate solutions based on the extracted keywords. For example, it might find solutions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[0528] The system uses relevant health supplements (e.g., "iron supplements") and the user's location information to retrieve information about nearby medical facilities.

[0529] 3. Generating and sending responses

[0530] The server consolidates the search results into a single response message. Specifically, it includes the following information:

[0531] List of solutions

[0532] Recommended health supplements

[0533] Information on the nearest medical institution

[0534] The server sends the generated response message to the terminal.

[0535] 4. Terminal processing (continued)

[0536] 1. Obtaining and displaying the response

[0537] The terminal receives and analyzes the response from the server.

[0538] Display the analysis results to the user. For example:

[0539] "To combat anemia, try the following: 1) Eat iron-rich foods, 2) Take iron with vitamin C, 3) Get plenty of rest."

[0540] "Recommended health supplement: Iron supplements"

[0541] "Nearest medical institution: ○○ Clinic (address and contact information)"

[0542] 5. User processing (continued)

[0543] 1. Implementation of countermeasures and provision of feedback

[0544] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[0545] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[0546] 6. Terminal Processing (continued)

[0547] 1. Obtaining and sending feedback

[0548] The device collects user feedback and sends it to the server.

[0549] 7. Server processing (continued)

[0550] 1. Accumulation and optimization of feedback

[0551] The server saves the received feedback to the database.

[0552] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[0553] This allows us to adjust the priority of solutions based on user feedback and improve the accuracy of the system.

[0554] Specific example

[0555] For example, if a user enters "I feel a bit anemic" and submits it, the server analyzes the input and extracts the keyword "anemia." Next, it searches its database for possible solutions such as "eating iron-rich foods," "taking vitamin C along with iron," and "getting rest," and recommends these to the user. It also simultaneously provides information on iron supplements and a guide to a medical institution near the user's home (e.g., "○○ Clinic"). The user then implements these solutions based on this information and provides the results as feedback to the system. This feedback is used to optimize the search results for the next time.

[0556] In this way, the system of the present invention supports the user's health management and enables continuous improvement.

[0557] The following describes the processing flow.

[0558] Step 1:

[0559] The user enters a change in their physical condition. The user opens the application on their device, types "I feel a bit anemic" in natural language into the text input field, and clicks the "Send" button.

[0560] Step 2:

[0561] The terminal obtains user input. The terminal retrieves the data "I feel a bit anemic" from the text input field and converts it into an internal data format.

[0562] Step 3:

[0563] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[0564] Step 4:

[0565] The server receives the data. The server receives the data "I feel a bit anemic" sent from the terminal and passes it to the analysis program.

[0566] Step 5:

[0567] The server performs natural language analysis. Using natural language processing (NLP) tools, the server extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I feel a bit anemic."

[0568] Step 6:

[0569] The server searches the database. Based on the extracted keywords, it searches the database for solutions, health supplements, and medical institution information.

[0570] Step 7:

[0571] The server compiles the search results. It combines the suggested solutions obtained from the search results (e.g., "Eat foods rich in iron," "Take vitamin C"), health supplements (e.g., "Iron supplements"), and information on nearby medical facilities into a single response message.

[0572] Step 8:

[0573] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[0574] Step 9:

[0575] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[0576] Step 10:

[0577] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. For example, the displayed content might be: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic."

[0578] Step 11:

[0579] The user implements the suggested course of action. The user follows the course of action provided by the system, either purchasing the recommended supplement or seeking medical attention.

[0580] Step 12:

[0581] Users provide feedback. Users enter feedback on the effectiveness of the implemented solutions and click the "Submit" button.

[0582] Step 13:

[0583] The device retrieves the feedback. The device retrieves the feedback content from the text input field and converts it into a data format.

[0584] Step 14:

[0585] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[0586] Step 15:

[0587] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[0588] Step 16:

[0589] The server optimizes based on the feedback. It analyzes the received feedback and evaluates the effectiveness of the solutions. This information is used in subsequent search processes to help adjust the priority of solutions.

[0590] This series of processes allows users to quickly and effectively obtain ways to deal with changes in their physical condition, and the system is gradually optimized through feedback.

[0591] (Example 1)

[0592] 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".

[0593] In modern society, users need quick and accurate ways to respond to daily changes in their physical condition. However, for the average user, managing their health and finding appropriate treatment methods is difficult. In particular, for users who do not accurately recognize their own symptoms and lack specialized knowledge, it is difficult to determine what actions to take. Against this backdrop, there is a need for a system that can quickly and accurately analyze changes in the user's physical condition, provide optimal treatment methods, and continuously optimize the system itself based on feedback.

[0594] 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.

[0595] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means including a generative AI model for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user, means for obtaining feedback from the user and storing it in the database, and means for continuously optimizing the search results based on the feedback. As a result, the user can quickly obtain appropriate remedies for changes in their physical condition, and the system itself is continuously improved through feedback, enabling more accurate responses.

[0596] A "user" refers to an individual who uses the system to input their health information and receive appropriate treatment.

[0597] A "terminal" is a device used by a user to access a system, and includes mobile devices and computers.

[0598] "Natural language" refers to the language used in everyday conversation that users use to input changes in their physical condition.

[0599] A "generative AI model" refers to artificial intelligence technology that analyzes natural language data input by users and extracts relevant keywords.

[0600] "Analysis" refers to the process of using generative AI models to process natural language data input by users and extract important information.

[0601] "Keywords" are important words or phrases extracted through analysis, and include information related to changes in the user's physical condition.

[0602] "Solutions" refer to specific actions or advice that users should take based on the extracted keywords.

[0603] "Health supplements" refer to nutritional supplements and vitamins recommended to support the user's health.

[0604] "Medical institutions" refer to facilities such as hospitals and clinics that users can visit to receive appropriate medical treatment.

[0605] A "database" refers to a centralized location where information on treatments, health supplements, and medical institutions is stored.

[0606] "Feedback" refers to information that users provide to the system, evaluating the effectiveness of the solutions and advice offered by the system.

[0607] "Optimization" refers to the process of improving and refining the system's search results and suggestions based on feedback.

[0608] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Specific embodiments for carrying out this invention are described in detail below.

[0609] System Configuration

[0610] This system consists of a multi-stage process that includes user input, data processing by the terminal, and analysis and optimization by the server. The following describes how each of these processes is implemented.

[0611] User processing

[0612] The user uses the application on their device to input changes in their physical condition in natural language. For example, they might input, "I've been feeling a bit anemic lately." This input is captured as text on the application. Once the user has finished inputting, they click the "Submit" button to send the data to the next processing step.

[0613] Terminal processing

[0614] The terminal retrieves user input and first stores it as text data. The software used here is the application's interface; for example, Kotlin or Swift are often used for mobile apps, while React or Angular are commonly used for web apps. Next, the retrieved text data is formatted and converted into a format such as JSON that can be sent to the server. Scripting languages ​​such as Python or JavaScript are used for this process. The formatted data is sent to the server using the HTTPS protocol.

[0615] Server Processing

[0616] The server receives data sent from the terminal and first temporarily stores it in a database. Databases such as MySQL and PostgreSQL are used. Next, the received data is analyzed using a generative AI model. Specifically, NLP models such as BERT (Bidirectional Encoder Representations from Transformers) and GPT-3 (Generative Pre-trained Transformer 3) are used. Through analysis, relevant keywords (e.g., "anemia," "iron deficiency") are extracted from the text. The server then searches the database for appropriate solutions based on the extracted keywords. For example, it might use SQL queries to find suggestions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[0617] Next, the system retrieves information about nearby medical facilities using relevant health supplements (e.g., "iron supplements") and the user's location. This information is then combined into a single response message as search results, and the server sends the generated response message back to the device.

[0618] Terminal response processing

[0619] The terminal receives response messages from the server, parses them, and formats them into a format that can be displayed on the user interface. JavaScript and HTML are often used in the display portion of the application. The analysis results are then displayed to the user. Specifically, the following information is included: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take it with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," "Nearest medical institution: XX Clinic (address and contact information)."

[0620] User feedback

[0621] The user implements the suggested solution and inputs the results as feedback into the application on their device. Once the input is complete, they click the "Submit" button. This feedback is then sent from the device to the server.

[0622] Server feedback processing

[0623] The server stores user feedback in a database. This data is stored in a dedicated table for accumulating user feedback information. Subsequently, statistical analysis is performed based on this feedback data to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches.

[0624] Specific example

[0625] For example, if a user enters "I've been feeling a bit anemic lately" into the device and clicks the "Send" button, the device receives the input, formats it, and sends it to the server. The server analyzes the received data using an NLP model and extracts keywords such as "anemia" and "iron deficiency." Next, it searches the database for solutions such as "consume iron-rich foods," "take vitamin C along with it," and "get rest," and retrieves information on nearby medical facilities along with this information to generate a response. The device receives this response and displays it to the user.

[0626] Users implement solutions and provide feedback on their effectiveness to the system. Based on this feedback, the system is continuously optimized, resulting in more accurate search results in the future.

[0627] Example of a prompt

[0628] "What are some recommended ways to increase iron intake when experiencing symptoms of anemia?"

[0629] In this way, the system of the present invention supports the user's health management, and through continuous system improvement, it enables the provision of more efficient and accurate treatment methods.

[0630] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0631] Step 1: User enters their health status.

[0632] The user opens the application on their device. Next, they input changes in their physical condition or symptoms they are experiencing in natural language. For example, they might input, "I've been feeling a bit anemic lately." Once they have finished inputting, they click the submit button. Thus, the input in this step is the user's natural language text, and the output is the data sent to the device.

[0633] Step 2: Data acquisition and formatting on the device

[0634] The terminal receives natural language text sent by the user. Next, it processes this input data and converts it into a format that can be sent to the server (e.g., JSON). Scripting languages ​​such as Python or JavaScript are used for this process. The input for this step is the user's natural language text, and the output is formatted JSON data. The formatted data is then sent to the server via the HTTPS protocol.

[0635] Step 3: Receiving and temporarily storing data on the server

[0636] The server receives JSON data sent from the terminal. The received data is temporarily stored in a database. Databases such as MySQL or PostgreSQL are used. The input for this step is formatted JSON data, and the output is the information stored in the database.

[0637] Step 4: Natural Language Processing (NLP)

[0638] The server uses a generative AI model to analyze the stored data. Specifically, NLP models such as BERT and GPT-3 extract relevant keywords from natural language text. The input for this step is temporarily stored data, and the output is the extracted keywords. For example, keywords such as "anemia" and "iron deficiency" are extracted.

[0639] Step 5: Retrieve relevant data from the database

[0640] The server searches the database for information on remedies, health supplements, and medical institutions based on the extracted keywords. Using SQL queries, it finds information such as iron-rich foods, ways to consume vitamin C together, and ways to get enough rest. The input for this step is the extracted keywords, and the output is the retrieved information on remedies and medical institutions.

[0641] Step 6: Response generation and sending

[0642] The server generates a response message based on the retrieved information. This message includes the following information: a list of countermeasures, recommended health supplements, and information on the nearest medical facility. The generated response message is sent to the terminal. The input for this step is the search result data, and the output is the generated response message.

[0643] Step 7: Receiving and analyzing the terminal's response

[0644] The terminal receives and analyzes the response message from the server. It then formats the analysis results into a format that can be displayed on the user interface. The input for this step is the response message from the server, and the output is the information displayed on the user interface. Specific examples of the displayed information include: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take iron with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," and "Nearest medical institution: XX Clinic (address and contact information)."

[0645] Step 8: User implements corrective action and enters feedback.

[0646] The user implements the suggested solutions, such as purchasing supplements or visiting a medical institution. Afterward, they evaluate whether the provided solutions were effective and enter feedback. Once feedback is complete, they click the "Submit" button. The input in this step is the user's feedback, and the output is the submitted feedback data.

[0647] Step 9: Obtain and send feedback from the device.

[0648] The terminal receives user feedback and formats it into a format that can be sent to the server. The input for this step is the user feedback, and the output is the formatted feedback data. The formatted data is then sent to the server.

[0649] Step 10: Server feedback accumulation and optimization

[0650] The server stores the received feedback data in a database. Based on this feedback data, statistical analysis is performed to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches. The input for this step is the feedback data, and the output is the optimized search algorithm. This allows for continuous improvement of the system through feedback.

[0651] (Application Example 1)

[0652] 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."

[0653] Conventional medical support systems made it difficult for users to obtain the information necessary to appropriately address changes in their own health. Furthermore, the lack of means to continuously optimize the system based on feedback made it difficult to provide personalized and appropriate medical information. As a result, users were unable to manage their health quickly and accurately, leading to a decrease in the efficiency of health management.

[0654] 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.

[0655] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user on a visual display device or virtual store, means for obtaining feedback from the user and storing it in the database, means for optimizing the search results based on the feedback, and means for using a generative AI model to suggest remedies and related information corresponding to the changes in physical condition within the virtual store. This allows the user to obtain quick and accurate remedies for changes in their physical condition, and the system is optimized based on the feedback, enabling the provision of personalized and appropriate medical information.

[0656] "User" refers to an individual or legal entity that uses the system.

[0657] "Changes in physical condition" refers to changes or abnormalities in the user's health status.

[0658] "Natural language" refers to the words and sentences that humans use on a daily basis, and does not require any special format or structure for input.

[0659] "Related keywords" refer to words or phrases related to changes in physical condition that the user enters in natural language.

[0660] "Solutions" refer to methods that indicate appropriate responses or improvements to changes in the user's physical condition.

[0661] "Health supplements" refer to substances or products consumed to maintain or promote health.

[0662] A "medical institution" refers to a facility or organization where doctors provide medical care.

[0663] A "database" refers to a system or device for systematically storing and managing large amounts of data.

[0664] A "visual display device" refers to a device such as a monitor or display used to show information to a user.

[0665] A "virtual store" refers to a virtual shop that provides goods and services on the internet.

[0666] "Feedback" refers to the act of users returning feedback on the effectiveness and evaluation of the solutions or information they have provided, as well as the content of that feedback.

[0667] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to generate and analyze information.

[0668] "Optimization" refers to making adjustments and improvements to maximize the performance and efficiency of a system.

[0669] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on that feedback. The system begins with the user inputting changes in their physical condition in natural language.

[0670] System program

[0671] The system is built using the following hardware and software:

[0672] Hardware:

[0673] Mobile devices or information processing devices (smartphones, personal computers, tablets, etc.)

[0674] Visual display devices (monitors, displays, etc.)

[0675] software:

[0676] Natural Language Processing (NLP): Natural Language Toolkit (nltk)

[0677] Server program: Flask

[0678] Machine learning models: scikit-learn

[0679] Database Management System (DBMS)

[0680] Processing procedure

[0681] The server receives information about changes in the user's physical condition in natural language, entered through a mobile device or information processing device. Next, it analyzes the input using natural language processing technology and extracts relevant keywords. Specifically, if the user enters "I've been getting tired easily lately," the server analyzes this input and extracts the keyword "gets tired easily."

[0682] Based on these extracted keywords, the server searches the database for information on appropriate treatments, health supplements, and medical institutions. The search results are then presented to the user as optimal treatments and relevant information using a generative AI model.

[0683] For example, if a user enters "I've been feeling tired lately," the server will search its database for solutions based on the keyword "feeling tired," such as "get enough sleep," "eat a balanced diet," and "reduce stress." It will also simultaneously provide information on health supplements like "iron supplements" and information on nearby medical facilities, such as "○○ Clinic (address and contact information)."

[0684] Users implement the suggested solutions and input their results into the system as feedback. This feedback is collected and stored on the server and used as reference in subsequent search and selection processes. This allows the system's accuracy and efficiency to continuously improve based on user feedback.

[0685] Specific example

[0686] When a user enters "I've been feeling tired lately," the system suggests the most suitable solutions based on that input. For example, it might suggest "getting enough sleep," "eating a balanced diet," or "reducing stress." At the same time, it provides information on nearby medical facilities based on the user's location. Furthermore, it may also display a purchase link for "iron supplements" as a health supplement.

[0687] Example of a prompt

[0688] Please suggest solutions for the user who enters "I've been feeling tired lately." Please also include relevant health supplements and information on the nearest medical facilities.

[0689] In this way, the system of the present invention can continue to support the user's health management and improve the accuracy of providing individualized information.

[0690] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0691] Step 1:

[0692] Users input changes in their physical condition using natural language via a mobile device or information processing device. For example, they might input, "I've been feeling tired lately." After inputting the information, the user clicks the "Submit" button.

[0693] Input: User's natural language description of changes in their physical condition (e.g., "I've been feeling tired lately").

[0694] Output: Natural language input data

[0695] Step 2:

[0696] The terminal acquires the user's natural language input data, formats it, and sends it to the server. The formatted data is often converted to JSON or XML format.

[0697] Input: User's natural language input data (e.g., "I've been feeling tired lately")

[0698] Data processing: Formatting natural language input into JSON or XML.

[0699] Output: Formatted data

[0700] Step 3:

[0701] The server receives formatted data sent from the terminal. The received data is analyzed using a natural language processing (NLP) program, and relevant keywords are extracted. For example, the keyword "easily fatigued" might be extracted.

[0702] Input: Formatted data (e.g., "I've been feeling tired lately")

[0703] Data processing: Keyword extraction using Natural Language Processing (NLP)

[0704] Output: Extracted keywords (e.g., "easily fatigued")

[0705] Step 4:

[0706] The server searches the database for appropriate treatments, health supplements, and medical information based on the extracted keywords. The search results are optimized using a generative AI model for presentation to the user.

[0707] Input: Extracted keywords (e.g., "easily fatigued")

[0708] Data Search: Search for relevant information from the database.

[0709] Data processing: Optimizing information using generative AI models.

[0710] Output: Optimized treatment methods, health supplements, and healthcare information.

[0711] Step 5:

[0712] The server sends optimized information to the terminal. This information includes a list of solutions, recommendations for health supplements, and information on the nearest medical facilities.

[0713] Input: Optimized treatment methods, health supplements, medical institution information

[0714] Data processing: Packaging and transmission of information

[0715] Output: Packaged data

[0716] Step 6:

[0717] The terminal receives data from the server and displays it to the user. The user can view the information through a visual display device. Specifically, this includes lists of countermeasures (e.g., "Get enough sleep," "Eat a balanced diet," "Reduce stress"), recommendations for health supplements (e.g., "Iron supplements"), and information on the nearest medical institution (e.g., "○○ Clinic").

[0718] Input: Packaged data received from the server

[0719] Data processing: Parsing and displaying received data

[0720] Output: Information displayed to the user

[0721] Step 7:

[0722] Users implement the suggested solutions and provide feedback on their effectiveness. They input the effects and evaluations in natural language and click the "Submit" button.

[0723] Input: User feedback (e.g., "I feel less tired")

[0724] Output: Natural language feedback data

[0725] Step 8:

[0726] The device then sends the user's feedback data back to the server. This allows the feedback to be accumulated in the system.

[0727] Input: User's natural language feedback data

[0728] Data processing: Format conversion of natural language feedback

[0729] Output: Formatted feedback data

[0730] Step 9:

[0731] The server receives feedback data and stores it in a database. The stored feedback data is statistically analyzed and used to optimize search results for future searches.

[0732] Input: Formatted feedback data

[0733] Data processing: Accumulation and statistical analysis of feedback data.

[0734] Output: Optimized search algorithm

[0735] Thus, the system of the present invention provides the optimal course of action based on changes in the user's physical condition, and realizes a process in which the system is continuously optimized through that feedback.

[0736] 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.

[0737] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[0738] 1. User processing

[0739] 1. Enter your health status

[0740] Users open the application on their device and input changes in their physical condition using natural language. For example, they might input "I've been feeling a bit anemic lately" and also input any anxiety they feel as a result.

[0741] Once the user has finished entering the information, they click the "Submit" button.

[0742] 2. Terminal processing

[0743] 1. Input acquisition and transmission

[0744] The device acquires user input and stores it as data. This data may include not only text data but also audio data.

[0745] The terminal formats the input data and converts it into a format that can be sent to the server.

[0746] Send the formatted data to the server.

[0747] 3. Server processing

[0748] 1. Input Analysis

[0749] The server analyzes the received data. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the input sentence "I feel a bit anemic."

[0750] If audio data is included, use an audio analysis tool to identify the content and emotion of the statements.

[0751] 2. Recognition by the Emotion Engine

[0752] The server uses an emotion engine to recognize the user's emotional state (e.g., "anxious," "restless," "relaxed") from the analyzed data.

[0753] 3. Obtaining related data

[0754] Based on the extracted keywords and recognized emotional states, the system searches the database for appropriate coping strategies, health supplements, and medical information. For example, it might find solutions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[0755] If the user's emotional state is identified as "anxiety," advice to alleviate it can also be included.

[0756] 4. Generating and sending responses

[0757] The server consolidates the search results into a single response message. Specifically, it includes the following information:

[0758] List of solutions

[0759] Recommended health supplements

[0760] Information on the nearest medical institution

[0761] Additional psychological advice (e.g., "Take deep breaths to relax")

[0762] The server sends the generated response message to the terminal.

[0763] 4. Terminal processing (continued)

[0764] 1. Obtaining and displaying the response

[0765] The terminal receives a response from the server and analyzes its contents.

[0766] The analysis results are displayed in a format that is easy for the user to understand. For example, the displayed content might include: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to help you relax."

[0767] 5. User processing (continued)

[0768] 1. Implementation of countermeasures and provision of feedback

[0769] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[0770] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[0771] 6. Terminal Processing (continued)

[0772] 1. Obtaining and sending feedback

[0773] The device collects user feedback and sends it to the server.

[0774] 7. Server processing (continued)

[0775] 1. Accumulation and optimization of feedback

[0776] The server saves the received feedback to the database.

[0777] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[0778] This allows us to adjust the priority of solutions based on user feedback and improve the accuracy of the system.

[0779] Specific example

[0780] For example, if a user types "I've been feeling a bit anemic lately" and says "I'm very anxious" in voice, the server analyzes the input and extracts the keyword "anemia" and the emotional state of "anxiety." The server then searches its database for coping strategies such as "eat iron-rich foods," "take iron-rich foods," and "get rest," as well as psychological advice such as "take deep breaths to relax," and provides this information to the user. Based on this information, the user implements the necessary coping strategies and provides feedback on the results to contribute to the optimization of the system.

[0781] In this way, the system of the present invention can provide rapid and effective health management support while also taking into account the user's psychological state.

[0782] The following describes the processing flow.

[0783] Step 1:

[0784] The user enters a change in their physical condition. The user opens the application on their device and enters "I've been feeling anemic lately" in natural language into the text input field, along with their feelings about the condition (e.g., "I'm very anxious"). They then click the "Submit" button.

[0785] Step 2:

[0786] The terminal obtains user input. The terminal retrieves the data "I've been feeling anemic lately" and "I'm very anxious" from the text input field and converts it into an internal data format.

[0787] Step 3:

[0788] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[0789] Step 4:

[0790] The server receives the data. The server receives the user input data sent from the terminal ("I've been feeling anemic lately" and "I'm very anxious") and passes it to the analysis program.

[0791] Step 5:

[0792] The server performs natural language analysis. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I've been feeling a bit anemic lately."

[0793] Step 6:

[0794] The server performs emotion recognition using an emotion engine. From the input "I am very anxious," the emotion engine recognizes the emotional state as "anxiety."

[0795] Step 7:

[0796] The server searches the database. Based on the extracted keywords "anemia" and emotional state "anxiety," it searches the database for appropriate treatments, health supplements, and medical institution information.

[0797] Step 8:

[0798] The server compiles the search results. It combines the suggested solutions (e.g., "Consume foods rich in iron," "Consume vitamin C together," "Get rest"), health supplements (e.g., "Iron supplements"), information on nearby medical facilities, and psychological advice to alleviate anxiety (e.g., "Take deep breaths to relax") into a single response message.

[0799] Step 9:

[0800] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[0801] Step 10:

[0802] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[0803] Step 11:

[0804] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. The displayed content may include statements such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. We also recommend deep breathing to alleviate anxiety. The nearest clinic is XX Clinic."

[0805] Step 12:

[0806] The user implements coping strategies. The user practices the coping strategies provided by the system, such as purchasing supplements or visiting a medical institution. They may also follow advice to alleviate anxiety, such as practicing deep breathing.

[0807] Step 13:

[0808] The user provides feedback. The user enters feedback on the effectiveness of the implemented countermeasures and clicks the "Submit" button to send it to their device.

[0809] Step 14:

[0810] The device retrieves the feedback. The device retrieves the feedback content (e.g., "The iron supplement worked") from the text input field and converts it into a data format.

[0811] Step 15:

[0812] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[0813] Step 16:

[0814] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[0815] Step 17:

[0816] The server optimizes based on feedback. It analyzes received feedback (e.g., "iron supplements worked") and evaluates the effectiveness of the suggested solutions. This information is used in subsequent search processes to help adjust the priority of suggested solutions.

[0817] This series of processes allows users to acquire coping mechanisms to respond quickly and effectively to changes in their physical condition, and the system is continuously optimized through user feedback. Furthermore, the combination of emotional engines enables detailed responses that also take into account the user's psychological state.

[0818] (Example 2)

[0819] 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".

[0820] Conventional medical support systems have a problem in that they do not adequately suggest the most suitable treatment methods or health supplements in response to changes in the user's physical condition. Furthermore, advice provided without considering the user's psychological state is often ineffective. In addition, there is a lack of mechanisms to continuously optimize the system using user feedback. Therefore, there is a need for a system that can more effectively support users' health management.

[0821] 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.

[0822] In this invention, the server includes means for the user to input changes in their physical condition in natural language and voice data; means for analyzing the input natural language and voice data and extracting relevant keywords and emotional states; means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords and emotional states; means for displaying the search results to the user; means for obtaining feedback from the user and storing it in the database; and means for optimizing the search results based on the feedback. This enables the provision of remedies that take into account the user's changes in physical condition and psychological state, and continuous optimization of the system using feedback.

[0823] A "user" refers to an individual who uses the system to input changes in their physical condition and emotional state.

[0824] "Changes in physical condition" refers to a state in which a user expresses, in natural language, any abnormalities or problems they have experienced regarding their physical condition.

[0825] "Natural language" refers to language used by humans on a daily basis, and is not limited to any specific form of language description.

[0826] "Audio data" refers to data that records the content of what a user has said in digital format.

[0827] "Analysis" refers to the process of mechanically analyzing input natural language or audio data to identify and classify its meaning and emotions.

[0828] "Keywords" refer to important words extracted from analyzed natural language and speech data.

[0829] "Emotional state" refers to the user's psychological state, which the system identifies through analysis of voice data and other information.

[0830] "Solutions" refer to specific examples of actions or measures suggested in response to changes in the user's physical condition.

[0831] "Health supplements" refer to foods and supplements consumed with the purpose of supporting or improving the user's health.

[0832] "Medical institution information" refers to information about medical facilities such as hospitals and clinics where users can receive treatment.

[0833] A "database" refers to a collection of data that stores and allows searching for information such as treatment methods, health supplements, and medical institutions.

[0834] "Searching" refers to the process of extracting data that matches specific criteria from information stored in a database.

[0835] "Feedback" refers to the act of a user sending back information to the system regarding the effectiveness and satisfaction level of the solutions provided.

[0836] "Optimization" refers to the process by which a system improves its search algorithms and methods of providing solutions based on user feedback, thereby increasing the accuracy of search results in subsequent searches.

[0837] This invention is a medical support system that considers the user's physical and psychological changes, provides the optimal course of action accordingly, and continuously optimizes the system based on feedback. The system analyzes the user's natural language and voice input to identify keywords indicating changes in physical condition and emotional states. This enables more effective health management support.

[0838] Hardware and software to be used

[0839] Devices: Smartphones, tablets, PCs, etc.

[0840] Server: An information processing device with high-performance computing capabilities.

[0841] Natural language processing tools: Google Cloud Natural Language API, IBM Watson Natural Language Understanding.

[0842] Speech analysis tools: Google Cloud Speech-to-Text, Amazon Transcribe.

[0843] Emotion recognition engine: Microsoft Azure Emotion API, Affectiva SDK.

[0844] Database: A database that stores information on treatments, health supplements, and medical institutions.

[0845] System Operation Description

[0846] This system operates using the following steps.

[0847] 1. User's physical condition information and emotional input

[0848] Users open the application on their device and input changes in their physical condition using natural language. For example, they might type, "I've been feeling a bit anemic lately," and then use voice input to say, "I'm very anxious."

[0849] 2. Sending input data

[0850] The terminal formats the acquired text and audio data and sends it to the server.

[0851] 3. Data analysis on the server

[0852] The server analyzes the received data. It uses natural language processing tools to extract relevant keywords such as "anemia" from the text data. It converts the audio data into text using speech analysis tools and identifies emotional states (e.g., "anxiety") using an emotion recognition engine.

[0853] 4. Searching for and generating solutions

[0854] Based on the extracted keywords and emotional state, the server searches the database for appropriate coping strategies, health supplements, and medical information. This may include advice such as "consume iron-rich foods" or "visit a nearby clinic." Furthermore, considering that the emotional state is "anxiety," it may also include additional advice such as "take deep breaths to relax."

[0855] 5. Displaying search results

[0856] The device displays search results received from the server. For example, it might show advice such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax."

[0857] 6. User Feedback

[0858] Users who implement the solution will input feedback regarding its effectiveness and their satisfaction level, and this feedback will also be sent to the server via their device.

[0859] 7. Accumulation and optimization of feedback

[0860] The server stores feedback data in a database and statistically analyzes the effectiveness of the countermeasures. Based on the results of this analysis, the system is optimized to improve the accuracy of subsequent search processes.

[0861] Specific example

[0862] For example, if a user types "I've been feeling a bit anemic lately" and says "I'm very anxious" via voice, the server extracts the keyword "anemia" and the emotional state "anxiety." Based on this, the server searches the database for coping strategies such as "eat iron-rich foods," "take vitamin C along with it," and "get rest," as well as psychological advice such as "take deep breaths to relax," and provides these to the user. The user then uses this information to implement the necessary coping strategies and provides feedback on the results to help optimize the system.

[0863] As a result, the system of the present invention can provide rapid and effective health management support while taking into account the user's physical condition and psychological state.

[0864] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0865] Step 1:

[0866] Users input changes in their physical condition into the device using natural language and voice. For example, they might type "I've been feeling a bit anemic lately" into the text input field and then say "I'm very worried" into the microphone.

[0867] Input: Natural language text and audio data

[0868] Output: Text and audio data temporarily stored on the device.

[0869] Step 2:

[0870] The terminal formats the user's input data. Specifically, it converts text data to JSON format and saves audio data as an audio file. This converts the data into a format that can be transmitted.

[0871] Input: Natural language text and audio data

[0872] Output: Formatted JSON text data and audio files

[0873] Step 3:

[0874] The terminal sends the formatted data to the server. The data is sent using a communication protocol (e.g., HTTP).

[0875] Input: Formatted JSON text data and audio files

[0876] Output: Text and audio data sent to the server

[0877] Step 4:

[0878] The server analyzes the received data. Using natural language processing tools, it extracts keywords related to solutions from the text data. Simultaneously, it converts audio data into text using speech analysis tools and identifies the user's emotional state using an emotion recognition engine.

[0879] Input: Text data and audio data

[0880] Output: Extracted keywords (e.g., "anemia") and emotional states (e.g., "anxiety")

[0881] Step 5:

[0882] The server searches the database for relevant information based on the extracted keywords and emotional state. It retrieves coping strategies, health supplements, and medical information. This includes specific advice such as "consume iron-rich foods" or "visit a nearby clinic."

[0883] Input: Keywords and emotional state

[0884] Output: Search results (solutions, health supplements, medical institution information, etc.)

[0885] Step 6:

[0886] The server generates search results as a response message. It then summarizes specific advice into a single message and sends it to the terminal.

[0887] Input: Search Results

[0888] Output: Response message (Example: "Please increase your iron intake. Here are some recommended supplements.")

[0889] Step 7:

[0890] The terminal analyzes the response message received from the server and displays it to the user. For example, it might be displayed as a message box on the application screen.

[0891] Input: Response message

[0892] Output: Display of the analyzed message

[0893] Step 8:

[0894] The user implements the provided solution. For example, they might purchase and take an iron supplement. Afterwards, they input feedback on the effectiveness and satisfaction level of the solution and send it to their device.

[0895] Input: Feedback on solutions

[0896] Output: Feedback data

[0897] Step 9:

[0898] The device formats the user's feedback data and sends it to the server. This allows the feedback to be reflected in the system.

[0899] Input: Feedback data

[0900] Output: Feedback data sent to the server

[0901] Step 10:

[0902] The server accumulates feedback data and analyzes it statistically. Based on this, it evaluates the effectiveness of the countermeasures and optimizes the search process for subsequent searches.

[0903] Input: Feedback data

[0904] Output: Optimized search algorithms and a list of solutions

[0905] This allows the system to take into account changes in the user's physical and psychological state and continuously provide optimized solutions.

[0906] (Application Example 2)

[0907] 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."

[0908] Traditional health management systems can provide basic coping strategies based on changes in a user's physical condition, but they struggle to offer strategies that take into account the user's emotional state. Furthermore, their limited ability to optimize the system based on feedback made it difficult to provide optimal solutions for individual users. This highlights the need for flexible health management support tailored to the user's psychological state.

[0909] 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.

[0910] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on treatment methods, health supplements, and medical institutions based on the extracted keywords and emotional state, means for displaying the search results to the user, means for obtaining user feedback and storing it in the database, means for optimizing the search results based on the feedback, and further means for emotion recognition. This makes it possible to provide the optimal treatment method that simultaneously considers the user's physical condition and emotions.

[0911] A "user" is someone who uses the system to input changes in their physical condition and emotions.

[0912] "Natural language" refers to the language that humans use on a daily basis, and is used by users to input changes in their physical condition and emotions.

[0913] A "natural language input method" refers to a device or program that provides an interface for users to input changes in their physical condition or emotions in natural language.

[0914] "Analysis means" refers to a device or program that has the function of analyzing input natural language and extracting relevant keywords.

[0915] "Keywords" are highly relevant words or phrases extracted from the input natural language using analysis tools.

[0916] "Emotional state" refers to the psychological state of a user, as recognized by analytical methods.

[0917] "Emotion recognition means" refers to a device or program used to determine a user's psychological state from natural language or speech input.

[0918] "Solutions" refer to methods and means of health management provided based on the user's physical and emotional state.

[0919] "Health supplements" refer to foods and supplements recommended to users for the purpose of maintaining or restoring health.

[0920] "Medical institution information" refers to information such as contact details and addresses of clinics, hospitals, and other medical facilities that provide the medical services that users need.

[0921] A "database" is a collection of data that stores and manages information such as treatment methods, health supplements, and medical institutions in a searchable format.

[0922] A "search tool" refers to a device or program that has the function of extracting necessary information from a database.

[0923] "Display means" refers to a device or program that has the function of visualizing and providing search results to the user.

[0924] "Feedback" refers to information provided to the system about the effectiveness and impressions of the solutions implemented by the user.

[0925] An "optimization tool" is a device or program that has the function of improving the system's search results or solutions based on the feedback it receives.

[0926] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[0927] 1. System Configuration

[0928] This system consists of the following main components:

[0929] User device: (e.g., smartphone or computer)

[0930] Natural language input method: An interface for users to input changes in their physical condition or emotions using natural language.

[0931] Display method: An interface for displaying search results and solutions to the user.

[0932] server:

[0933] Analysis method: Software (e.g., Transformers library) for analyzing user-inputted natural language data and extracting relevant keywords and emotional states.

[0934] Emotion recognition means: Software for identifying a user's emotional state.

[0935] Search method: Software for searching databases for relevant treatments, health supplements, and information on medical institutions.

[0936] Optimization method: Software to improve search results based on feedback provided by users.

[0937] 2. Usage of Hardware and Software

[0938] User terminal:

[0939] Install an application that runs on a smartphone or computer. The user uses this application to input changes in their physical condition and emotions in natural language.

[0940] server:

[0941] The server uses generative AI models for natural language processing and emotion recognition. Specifically, it uses Python and the Transformers library. It analyzes user input and recognizes emotional states.

[0942] An API (Application Programming Interface) endpoint will be set up to communicate with the database and search for information on appropriate treatments, health supplements, and medical institutions.

[0943] After receiving feedback from users, the system is optimized based on statistical analysis.

[0944] 3. Specific Examples

[0945] For example, if a user enters "I've been feeling a bit anemic lately," the server analyzes this input and extracts the keyword "anemia." Simultaneously, it uses an emotion recognition engine to determine the user's feelings and recognize that the user is feeling anxious. The server then provides advice from its database as a solution, such as "consume iron-rich foods," "it's recommended to take them with vitamin C," and "take deep breaths to relax." This allows the user to implement the necessary solutions and provide feedback to the system.

[0946] 4. Example of a prompt statement

[0947] The following are examples of prompts that the user will enter:

[0948] "I've been feeling a bit anemic lately. I'm very worried. What can I do?"

[0949] "I've had a persistent headache. Which medicine would you recommend?"

[0950] "I can't shake off this fatigue. Do you have any recommendations for solutions?"

[0951] Based on these inputs, the system can perform appropriate analysis and searches, and propose the optimal course of action.

[0952] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0953] Step 1:

[0954] Users input changes in their physical condition and emotions into the device using natural language. Specifically, they open a smartphone application and enter text such as, "I've been feeling anemic lately. I'm very worried." The input data is text data in natural language format.

[0955] Step 2:

[0956] The terminal retrieves natural language text entered by the user and prepares an API request to send it to the server. The terminal converts the input text data into JSON format and sends it to the server. The input is the user's input text, and the output is the JSON data sent to the server.

[0957] Step 3:

[0958] The server parses the received JSON data and processes the input natural language to extract keywords. Specifically, it uses a generative AI model (e.g., the Transformers library) to extract keywords such as "anemia" and "anxiety." The input is JSON data, and the output is a list of extracted keywords.

[0959] Step 4:

[0960] The server uses an emotion recognition engine to identify the user's emotional state. Specifically, it uses an emotion recognition model to extract emotions (e.g., "anxiety," "restlessness") from text. The input is the user's text data, and the output is the identified emotional state.

[0961] Step 5:

[0962] The server searches its database for relevant coping strategies, health supplements, and healthcare information based on extracted keywords and emotional states. The server generates search queries and retrieves relevant information from a pre-stored database. Inputs are keywords and emotional states, while output is a list of coping strategies and recommended information.

[0963] Step 6:

[0964] The server consolidates the search results into a single response message and sends it to the terminal. Specifically, it generates a response that includes a list of solutions, recommended health supplements, information on the nearest medical facility, and additional psychological advice. The input is the search results, and the output is the response message.

[0965] Step 7:

[0966] The terminal analyzes the received response message and displays it in a user-friendly format. Specifically, it displays messages such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax," on the application screen. The input is the response message, and the output is the content displayed to the user.

[0967] Step 8:

[0968] The user implements the displayed solution and inputs the results as feedback. Specifically, they use the application to input the effectiveness and their impressions of the solution, such as "It was effective" or "My tension eased." The feedback data is then converted back into JSON format and sent from the terminal to the server. The input is the user's feedback text, and the output is the JSON data sent to the server.

[0969] Step 9:

[0970] The server analyzes the received feedback data and stores it in a database. Furthermore, it performs statistical analysis based on the feedback to continuously optimize search results and solutions. This data is then used for future search and selection processes. The input is feedback data, and the output is an updated database and an optimized list of solutions.

[0971] 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.

[0972] 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.

[0973] 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.

[0974] [Third Embodiment]

[0975] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0976] 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.

[0977] 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).

[0978] 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.

[0979] 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.

[0980] 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).

[0981] 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.

[0982] 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.

[0983] 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.

[0984] 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.

[0985] 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.

[0986] 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".

[0987] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. The specific operation of the system is described below.

[0988] 1. User processing

[0989] 1. Enter your health status

[0990] The user opens the application on their device and enters changes in their physical condition in natural language. For example, they might enter, "I've been feeling a bit anemic lately."

[0991] Once the user has finished entering the information, they click the "Submit" button.

[0992] 2. Terminal processing

[0993] 1. Input acquisition and transmission

[0994] The terminal retrieves the user's input and stores it as data.

[0995] The terminal formats the input data and converts it into a format that can be sent to the server.

[0996] Send the formatted data to the server.

[0997] 3. Server processing

[0998] 1. Input Analysis

[0999] The server analyzes the received data. Specifically, it uses a natural language processing (NLP) program to analyze the input "feeling anemic."

[1000] The analysis extracts relevant keywords (e.g., "anemia," "iron deficiency").

[1001] 2. Obtaining related data

[1002] The server searches the database for appropriate solutions based on the extracted keywords. For example, it might find solutions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[1003] The system uses relevant health supplements (e.g., "iron supplements") and the user's location information to retrieve information about nearby medical facilities.

[1004] 3. Generating and sending responses

[1005] The server consolidates the search results into a single response message. Specifically, it includes the following information:

[1006] List of solutions

[1007] Recommended health supplements

[1008] Information on the nearest medical institution

[1009] The server sends the generated response message to the terminal.

[1010] 4. Terminal processing (continued)

[1011] 1. Obtaining and displaying the response

[1012] The terminal receives and analyzes the response from the server.

[1013] Display the analysis results to the user. For example:

[1014] "To combat anemia, try the following: 1) Eat iron-rich foods, 2) Take iron with vitamin C, 3) Get plenty of rest."

[1015] "Recommended health supplement: Iron supplements"

[1016] "Nearest medical institution: ○○ Clinic (address and contact information)"

[1017] 5. User processing (continued)

[1018] 1. Implementation of countermeasures and provision of feedback

[1019] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[1020] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[1021] 6. Terminal Processing (continued)

[1022] 1. Obtaining and sending feedback

[1023] The device collects user feedback and sends it to the server.

[1024] 7. Server processing (continued)

[1025] 1. Accumulation and optimization of feedback

[1026] The server saves the received feedback to the database.

[1027] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[1028] This allows us to adjust the priority of solutions based on user feedback and improve the accuracy of the system.

[1029] Specific example

[1030] For example, if a user enters "I feel a bit anemic" and submits it, the server analyzes the input and extracts the keyword "anemia." Next, it searches its database for possible solutions such as "eating iron-rich foods," "taking vitamin C along with iron," and "getting rest," and recommends these to the user. It also simultaneously provides information on iron supplements and a guide to a medical institution near the user's home (e.g., "○○ Clinic"). The user then implements these solutions based on this information and provides the results as feedback to the system. This feedback is used to optimize the search results for the next time.

[1031] In this way, the system of the present invention supports the user's health management and enables continuous improvement.

[1032] The following describes the processing flow.

[1033] Step 1:

[1034] The user enters a change in their physical condition. The user opens the application on their device, types "I feel a bit anemic" in natural language into the text input field, and clicks the "Send" button.

[1035] Step 2:

[1036] The terminal obtains user input. The terminal retrieves the data "I feel a bit anemic" from the text input field and converts it into an internal data format.

[1037] Step 3:

[1038] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[1039] Step 4:

[1040] The server receives the data. The server receives the data "I feel a bit anemic" sent from the terminal and passes it to the analysis program.

[1041] Step 5:

[1042] The server performs natural language analysis. Using natural language processing (NLP) tools, the server extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I feel a bit anemic."

[1043] Step 6:

[1044] The server searches the database. Based on the extracted keywords, it searches the database for solutions, health supplements, and medical institution information.

[1045] Step 7:

[1046] The server compiles the search results. It combines the suggested solutions obtained from the search results (e.g., "Eat foods rich in iron," "Take vitamin C"), health supplements (e.g., "Iron supplements"), and information on nearby medical facilities into a single response message.

[1047] Step 8:

[1048] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[1049] Step 9:

[1050] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[1051] Step 10:

[1052] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. For example, the displayed content might be: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic."

[1053] Step 11:

[1054] The user implements the suggested course of action. The user follows the course of action provided by the system, either purchasing the recommended supplement or seeking medical attention.

[1055] Step 12:

[1056] Users provide feedback. Users enter feedback on the effectiveness of the implemented solutions and click the "Submit" button.

[1057] Step 13:

[1058] The device retrieves the feedback. The device retrieves the feedback content from the text input field and converts it into a data format.

[1059] Step 14:

[1060] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[1061] Step 15:

[1062] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[1063] Step 16:

[1064] The server optimizes based on the feedback. It analyzes the received feedback and evaluates the effectiveness of the solutions. This information is used in subsequent search processes to help adjust the priority of solutions.

[1065] This series of processes allows users to quickly and effectively obtain ways to deal with changes in their physical condition, and the system is gradually optimized through feedback.

[1066] (Example 1)

[1067] 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."

[1068] In modern society, users need quick and accurate ways to respond to daily changes in their physical condition. However, for the average user, managing their health and finding appropriate treatment methods is difficult. In particular, for users who do not accurately recognize their own symptoms and lack specialized knowledge, it is difficult to determine what actions to take. Against this backdrop, there is a need for a system that can quickly and accurately analyze changes in the user's physical condition, provide optimal treatment methods, and continuously optimize the system itself based on feedback.

[1069] 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.

[1070] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means including a generative AI model for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user, means for obtaining feedback from the user and storing it in the database, and means for continuously optimizing the search results based on the feedback. As a result, the user can quickly obtain appropriate remedies for changes in their physical condition, and the system itself is continuously improved through feedback, enabling more accurate responses.

[1071] A "user" refers to an individual who uses the system to input their health information and receive appropriate treatment.

[1072] A "terminal" is a device used by a user to access a system, and includes mobile devices and computers.

[1073] "Natural language" refers to the language used in everyday conversation that users use to input changes in their physical condition.

[1074] A "generative AI model" refers to artificial intelligence technology that analyzes natural language data input by users and extracts relevant keywords.

[1075] "Analysis" refers to the process of using generative AI models to process natural language data input by users and extract important information.

[1076] "Keywords" are important words or phrases extracted through analysis, and include information related to changes in the user's physical condition.

[1077] "Solutions" refer to specific actions or advice that users should take based on the extracted keywords.

[1078] "Health supplements" refer to nutritional supplements and vitamins recommended to support the user's health.

[1079] "Medical institutions" refer to facilities such as hospitals and clinics that users can visit to receive appropriate medical treatment.

[1080] A "database" refers to a centralized location where information on treatments, health supplements, and medical institutions is stored.

[1081] "Feedback" refers to information that users provide to the system, evaluating the effectiveness of the solutions and advice offered by the system.

[1082] "Optimization" refers to the process of improving and refining the system's search results and suggestions based on feedback.

[1083] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Specific embodiments for carrying out this invention are described in detail below.

[1084] System Configuration

[1085] This system consists of a multi-stage process that includes user input, data processing by the terminal, and analysis and optimization by the server. The following describes how each of these processes is implemented.

[1086] User processing

[1087] The user uses the application on their device to input changes in their physical condition in natural language. For example, they might input, "I've been feeling a bit anemic lately." This input is captured as text on the application. Once the user has finished inputting, they click the "Submit" button to send the data to the next processing step.

[1088] Terminal processing

[1089] The terminal retrieves user input and first stores it as text data. The software used here is the application's interface; for example, Kotlin or Swift are often used for mobile apps, while React or Angular are commonly used for web apps. Next, the retrieved text data is formatted and converted into a format such as JSON that can be sent to the server. Scripting languages ​​such as Python or JavaScript are used for this process. The formatted data is sent to the server using the HTTPS protocol.

[1090] Server Processing

[1091] The server receives data sent from the terminal and first temporarily stores it in a database. Databases such as MySQL and PostgreSQL are used. Next, the received data is analyzed using a generative AI model. Specifically, NLP models such as BERT (Bidirectional Encoder Representations from Transformers) and GPT-3 (Generative Pre-trained Transformer 3) are used. Through analysis, relevant keywords (e.g., "anemia," "iron deficiency") are extracted from the text. The server then searches the database for appropriate solutions based on the extracted keywords. For example, it might use SQL queries to find suggestions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[1092] Next, the system retrieves information about nearby medical facilities using relevant health supplements (e.g., "iron supplements") and the user's location. This information is then combined into a single response message as search results, and the server sends the generated response message back to the device.

[1093] Terminal response processing

[1094] The terminal receives response messages from the server, parses them, and formats them into a format that can be displayed on the user interface. JavaScript and HTML are often used in the display portion of the application. The analysis results are then displayed to the user. Specifically, the following information is included: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take it with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," "Nearest medical institution: XX Clinic (address and contact information)."

[1095] User feedback

[1096] The user implements the suggested solution and inputs the results as feedback into the application on their device. Once the input is complete, they click the "Submit" button. This feedback is then sent from the device to the server.

[1097] Server feedback processing

[1098] The server stores user feedback in a database. This data is stored in a dedicated table for accumulating user feedback information. Subsequently, statistical analysis is performed based on this feedback data to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches.

[1099] Specific example

[1100] For example, if a user enters "I've been feeling a bit anemic lately" into the device and clicks the "Send" button, the device receives the input, formats it, and sends it to the server. The server analyzes the received data using an NLP model and extracts keywords such as "anemia" and "iron deficiency." Next, it searches the database for solutions such as "consume iron-rich foods," "take vitamin C along with it," and "get rest," and retrieves information on nearby medical facilities along with this information to generate a response. The device receives this response and displays it to the user.

[1101] Users implement solutions and provide feedback on their effectiveness to the system. Based on this feedback, the system is continuously optimized, resulting in more accurate search results in the future.

[1102] Example of a prompt

[1103] "What are some recommended ways to increase iron intake when experiencing symptoms of anemia?"

[1104] In this way, the system of the present invention supports the user's health management, and through continuous system improvement, it enables the provision of more efficient and accurate treatment methods.

[1105] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1106] Step 1: User enters their health status.

[1107] The user opens the application on their device. Next, they input changes in their physical condition or symptoms they are experiencing in natural language. For example, they might input, "I've been feeling a bit anemic lately." Once they have finished inputting, they click the submit button. Thus, the input in this step is the user's natural language text, and the output is the data sent to the device.

[1108] Step 2: Data acquisition and formatting on the device

[1109] The terminal receives natural language text sent by the user. Next, it processes this input data and converts it into a format that can be sent to the server (e.g., JSON). Scripting languages ​​such as Python or JavaScript are used for this process. The input for this step is the user's natural language text, and the output is formatted JSON data. The formatted data is then sent to the server via the HTTPS protocol.

[1110] Step 3: Receiving and temporarily storing data on the server

[1111] The server receives JSON data sent from the terminal. The received data is temporarily stored in a database. Databases such as MySQL or PostgreSQL are used. The input for this step is formatted JSON data, and the output is the information stored in the database.

[1112] Step 4: Natural Language Processing (NLP)

[1113] The server uses a generative AI model to analyze the stored data. Specifically, NLP models such as BERT and GPT-3 extract relevant keywords from natural language text. The input for this step is temporarily stored data, and the output is the extracted keywords. For example, keywords such as "anemia" and "iron deficiency" are extracted.

[1114] Step 5: Retrieve relevant data from the database

[1115] The server searches the database for information on remedies, health supplements, and medical institutions based on the extracted keywords. Using SQL queries, it finds information such as iron-rich foods, ways to consume vitamin C together, and ways to get enough rest. The input for this step is the extracted keywords, and the output is the retrieved information on remedies and medical institutions.

[1116] Step 6: Response generation and sending

[1117] The server generates a response message based on the retrieved information. This message includes the following information: a list of countermeasures, recommended health supplements, and information on the nearest medical facility. The generated response message is sent to the terminal. The input for this step is the search result data, and the output is the generated response message.

[1118] Step 7: Receiving and analyzing the terminal's response

[1119] The terminal receives and analyzes the response message from the server. It then formats the analysis results into a format that can be displayed on the user interface. The input for this step is the response message from the server, and the output is the information displayed on the user interface. Specific examples of the displayed information include: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take iron with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," and "Nearest medical institution: XX Clinic (address and contact information)."

[1120] Step 8: User implements corrective action and enters feedback.

[1121] The user implements the suggested solutions, such as purchasing supplements or visiting a medical institution. Afterward, they evaluate whether the provided solutions were effective and enter feedback. Once feedback is complete, they click the "Submit" button. The input in this step is the user's feedback, and the output is the submitted feedback data.

[1122] Step 9: Obtain and send feedback from the device.

[1123] The terminal receives user feedback and formats it into a format that can be sent to the server. The input for this step is the user feedback, and the output is the formatted feedback data. The formatted data is then sent to the server.

[1124] Step 10: Server feedback accumulation and optimization

[1125] The server stores the received feedback data in a database. Based on this feedback data, statistical analysis is performed to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches. The input for this step is the feedback data, and the output is the optimized search algorithm. This allows for continuous improvement of the system through feedback.

[1126] (Application Example 1)

[1127] 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."

[1128] Conventional medical support systems made it difficult for users to obtain the information necessary to appropriately address changes in their own health. Furthermore, the lack of means to continuously optimize the system based on feedback made it difficult to provide personalized and appropriate medical information. As a result, users were unable to manage their health quickly and accurately, leading to a decrease in the efficiency of health management.

[1129] 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.

[1130] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user on a visual display device or virtual store, means for obtaining feedback from the user and storing it in the database, means for optimizing the search results based on the feedback, and means for using a generative AI model to suggest remedies and related information corresponding to the changes in physical condition within the virtual store. This allows the user to obtain quick and accurate remedies for changes in their physical condition, and the system is optimized based on the feedback, enabling the provision of personalized and appropriate medical information.

[1131] "User" refers to an individual or legal entity that uses the system.

[1132] "Changes in physical condition" refers to changes or abnormalities in the user's health status.

[1133] "Natural language" refers to the words and sentences that humans use on a daily basis, and does not require any special format or structure for input.

[1134] "Related keywords" refer to words or phrases related to changes in physical condition that the user enters in natural language.

[1135] "Solutions" refer to methods that indicate appropriate responses or improvements to changes in the user's physical condition.

[1136] "Health supplements" refer to substances or products consumed to maintain or promote health.

[1137] A "medical institution" refers to a facility or organization where doctors provide medical care.

[1138] A "database" refers to a system or device for systematically storing and managing large amounts of data.

[1139] A "visual display device" refers to a device such as a monitor or display used to show information to a user.

[1140] A "virtual store" refers to a virtual shop that provides goods and services on the internet.

[1141] "Feedback" refers to the act of users returning feedback on the effectiveness and evaluation of the solutions or information they have provided, as well as the content of that feedback.

[1142] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to generate and analyze information.

[1143] "Optimization" refers to making adjustments and improvements to maximize the performance and efficiency of a system.

[1144] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on that feedback. The system begins with the user inputting changes in their physical condition in natural language.

[1145] System program

[1146] The system is built using the following hardware and software:

[1147] Hardware:

[1148] Mobile devices or information processing devices (smartphones, personal computers, tablets, etc.)

[1149] Visual display devices (monitors, displays, etc.)

[1150] software:

[1151] Natural Language Processing (NLP): Natural Language Toolkit (nltk)

[1152] Server program: Flask

[1153] Machine learning models: scikit-learn

[1154] Database Management System (DBMS)

[1155] Processing procedure

[1156] The server receives information about changes in the user's physical condition in natural language, entered through a mobile device or information processing device. Next, it analyzes the input using natural language processing technology and extracts relevant keywords. Specifically, if the user enters "I've been getting tired easily lately," the server analyzes this input and extracts the keyword "gets tired easily."

[1157] Based on these extracted keywords, the server searches the database for information on appropriate treatments, health supplements, and medical institutions. The search results are then presented to the user as optimal treatments and relevant information using a generative AI model.

[1158] For example, if a user enters "I've been feeling tired lately," the server will search its database for solutions based on the keyword "feeling tired," such as "get enough sleep," "eat a balanced diet," and "reduce stress." It will also simultaneously provide information on health supplements like "iron supplements" and information on nearby medical facilities, such as "○○ Clinic (address and contact information)."

[1159] Users implement the suggested solutions and input their results into the system as feedback. This feedback is collected and stored on the server and used as reference in subsequent search and selection processes. This allows the system's accuracy and efficiency to continuously improve based on user feedback.

[1160] Specific example

[1161] When a user enters "I've been feeling tired lately," the system suggests the most suitable solutions based on that input. For example, it might suggest "getting enough sleep," "eating a balanced diet," or "reducing stress." At the same time, it provides information on nearby medical facilities based on the user's location. Furthermore, it may also display a purchase link for "iron supplements" as a health supplement.

[1162] Example of a prompt

[1163] Please suggest solutions for the user who enters "I've been feeling tired lately." Please also include relevant health supplements and information on the nearest medical facilities.

[1164] In this way, the system of the present invention can continue to support the user's health management and improve the accuracy of providing individualized information.

[1165] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1166] Step 1:

[1167] Users input changes in their physical condition using natural language via a mobile device or information processing device. For example, they might input, "I've been feeling tired lately." After inputting the information, the user clicks the "Submit" button.

[1168] Input: User's natural language description of changes in their physical condition (e.g., "I've been feeling tired lately").

[1169] Output: Natural language input data

[1170] Step 2:

[1171] The terminal acquires the user's natural language input data, formats it, and sends it to the server. The formatted data is often converted to JSON or XML format.

[1172] Input: User's natural language input data (e.g., "I've been feeling tired lately")

[1173] Data processing: Formatting natural language input into JSON or XML.

[1174] Output: Formatted data

[1175] Step 3:

[1176] The server receives formatted data sent from the terminal. The received data is analyzed using a natural language processing (NLP) program, and relevant keywords are extracted. For example, the keyword "easily fatigued" might be extracted.

[1177] Input: Formatted data (e.g., "I've been feeling tired lately")

[1178] Data processing: Keyword extraction using Natural Language Processing (NLP)

[1179] Output: Extracted keywords (e.g., "easily fatigued")

[1180] Step 4:

[1181] The server searches the database for appropriate treatments, health supplements, and medical information based on the extracted keywords. The search results are optimized using a generative AI model for presentation to the user.

[1182] Input: Extracted keywords (e.g., "easily fatigued")

[1183] Data Search: Search for relevant information from the database.

[1184] Data processing: Optimizing information using generative AI models.

[1185] Output: Optimized treatment methods, health supplements, and healthcare information.

[1186] Step 5:

[1187] The server sends optimized information to the terminal. This information includes a list of solutions, recommendations for health supplements, and information on the nearest medical facilities.

[1188] Input: Optimized treatment methods, health supplements, medical institution information

[1189] Data processing: Packaging and transmission of information

[1190] Output: Packaged data

[1191] Step 6:

[1192] The terminal receives data from the server and displays it to the user. The user can view the information through a visual display device. Specifically, this includes lists of countermeasures (e.g., "Get enough sleep," "Eat a balanced diet," "Reduce stress"), recommendations for health supplements (e.g., "Iron supplements"), and information on the nearest medical institution (e.g., "○○ Clinic").

[1193] Input: Packaged data received from the server

[1194] Data processing: Parsing and displaying received data

[1195] Output: Information displayed to the user

[1196] Step 7:

[1197] Users implement the suggested solutions and provide feedback on their effectiveness. They input the effects and evaluations in natural language and click the "Submit" button.

[1198] Input: User feedback (e.g., "I feel less tired")

[1199] Output: Natural language feedback data

[1200] Step 8:

[1201] The device then sends the user's feedback data back to the server. This allows the feedback to be accumulated in the system.

[1202] Input: User's natural language feedback data

[1203] Data processing: Format conversion of natural language feedback

[1204] Output: Formatted feedback data

[1205] Step 9:

[1206] The server receives feedback data and stores it in a database. The stored feedback data is statistically analyzed and used to optimize search results for future searches.

[1207] Input: Formatted feedback data

[1208] Data processing: Accumulation and statistical analysis of feedback data.

[1209] Output: Optimized search algorithm

[1210] Thus, the system of the present invention provides the optimal course of action based on changes in the user's physical condition, and realizes a process in which the system is continuously optimized through that feedback.

[1211] 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.

[1212] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[1213] 1. User processing

[1214] 1. Enter your health status

[1215] Users open the application on their device and input changes in their physical condition using natural language. For example, they might input "I've been feeling a bit anemic lately" and also input any anxiety they feel as a result.

[1216] Once the user has finished entering the information, they click the "Submit" button.

[1217] 2. Terminal processing

[1218] 1. Input acquisition and transmission

[1219] The device acquires user input and stores it as data. This data may include not only text data but also audio data.

[1220] The terminal formats the input data and converts it into a format that can be sent to the server.

[1221] Send the formatted data to the server.

[1222] 3. Server processing

[1223] 1. Input Analysis

[1224] The server analyzes the received data. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the input sentence "I feel a bit anemic."

[1225] If audio data is included, use an audio analysis tool to identify the content and emotion of the statements.

[1226] 2. Recognition by the Emotion Engine

[1227] The server uses an emotion engine to recognize the user's emotional state (e.g., "anxious," "restless," "relaxed") from the analyzed data.

[1228] 3. Obtaining related data

[1229] Based on the extracted keywords and recognized emotional states, the system searches the database for appropriate coping strategies, health supplements, and medical information. For example, it might find solutions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[1230] If the user's emotional state is identified as "anxiety," advice to alleviate it can also be included.

[1231] 4. Generating and sending responses

[1232] The server consolidates the search results into a single response message. Specifically, it includes the following information:

[1233] List of solutions

[1234] Recommended health supplements

[1235] Information on the nearest medical institution

[1236] Additional psychological advice (e.g., "Take deep breaths to relax")

[1237] The server sends the generated response message to the terminal.

[1238] 4. Terminal processing (continued)

[1239] 1. Obtaining and displaying the response

[1240] The terminal receives a response from the server and analyzes its contents.

[1241] The analysis results are displayed in a format that is easy for the user to understand. For example, the displayed content might include: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to help you relax."

[1242] 5. User processing (continued)

[1243] 1. Implementation of countermeasures and provision of feedback

[1244] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[1245] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[1246] 6. Terminal Processing (continued)

[1247] 1. Obtaining and sending feedback

[1248] The device collects user feedback and sends it to the server.

[1249] 7. Server processing (continued)

[1250] 1. Accumulation and optimization of feedback

[1251] The server saves the received feedback to the database.

[1252] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[1253] This allows us to adjust the priority of solutions based on user feedback and improve the accuracy of the system.

[1254] Specific example

[1255] For example, if a user types "I've been feeling a bit anemic lately" and says "I'm very anxious" in voice, the server analyzes the input and extracts the keyword "anemia" and the emotional state of "anxiety." The server then searches its database for coping strategies such as "eat iron-rich foods," "take iron-rich foods," and "get rest," as well as psychological advice such as "take deep breaths to relax," and provides this information to the user. Based on this information, the user implements the necessary coping strategies and provides feedback on the results to contribute to the optimization of the system.

[1256] In this way, the system of the present invention can provide rapid and effective health management support while also taking into account the user's psychological state.

[1257] The following describes the processing flow.

[1258] Step 1:

[1259] The user enters a change in their physical condition. The user opens the application on their device and enters "I've been feeling anemic lately" in natural language into the text input field, along with their feelings about the condition (e.g., "I'm very anxious"). They then click the "Submit" button.

[1260] Step 2:

[1261] The terminal obtains user input. The terminal retrieves the data "I've been feeling anemic lately" and "I'm very anxious" from the text input field and converts it into an internal data format.

[1262] Step 3:

[1263] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[1264] Step 4:

[1265] The server receives the data. The server receives the user input data sent from the terminal ("I've been feeling anemic lately" and "I'm very anxious") and passes it to the analysis program.

[1266] Step 5:

[1267] The server performs natural language analysis. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I've been feeling a bit anemic lately."

[1268] Step 6:

[1269] The server performs emotion recognition using an emotion engine. From the input "I am very anxious," the emotion engine recognizes the emotional state as "anxiety."

[1270] Step 7:

[1271] The server searches the database. Based on the extracted keywords "anemia" and emotional state "anxiety," it searches the database for appropriate treatments, health supplements, and medical institution information.

[1272] Step 8:

[1273] The server compiles the search results. It combines the suggested solutions (e.g., "Consume foods rich in iron," "Consume vitamin C together," "Get rest"), health supplements (e.g., "Iron supplements"), information on nearby medical facilities, and psychological advice to alleviate anxiety (e.g., "Take deep breaths to relax") into a single response message.

[1274] Step 9:

[1275] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[1276] Step 10:

[1277] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[1278] Step 11:

[1279] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. The displayed content may include statements such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. We also recommend deep breathing to alleviate anxiety. The nearest clinic is XX Clinic."

[1280] Step 12:

[1281] The user implements coping strategies. The user practices the coping strategies provided by the system, such as purchasing supplements or visiting a medical institution. They may also follow advice to alleviate anxiety, such as practicing deep breathing.

[1282] Step 13:

[1283] The user provides feedback. The user enters feedback on the effectiveness of the implemented countermeasures and clicks the "Submit" button to send it to their device.

[1284] Step 14:

[1285] The device retrieves the feedback. The device retrieves the feedback content (e.g., "The iron supplement worked") from the text input field and converts it into a data format.

[1286] Step 15:

[1287] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[1288] Step 16:

[1289] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[1290] Step 17:

[1291] The server optimizes based on feedback. It analyzes received feedback (e.g., "iron supplements worked") and evaluates the effectiveness of the suggested solutions. This information is used in subsequent search processes to help adjust the priority of suggested solutions.

[1292] This series of processes allows users to acquire coping mechanisms to respond quickly and effectively to changes in their physical condition, and the system is continuously optimized through user feedback. Furthermore, the combination of emotional engines enables detailed responses that also take into account the user's psychological state.

[1293] (Example 2)

[1294] 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."

[1295] Conventional medical support systems have a problem in that they do not adequately suggest the most suitable treatment methods or health supplements in response to changes in the user's physical condition. Furthermore, advice provided without considering the user's psychological state is often ineffective. In addition, there is a lack of mechanisms to continuously optimize the system using user feedback. Therefore, there is a need for a system that can more effectively support users' health management.

[1296] 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.

[1297] In this invention, the server includes means for the user to input changes in their physical condition in natural language and voice data; means for analyzing the input natural language and voice data and extracting relevant keywords and emotional states; means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords and emotional states; means for displaying the search results to the user; means for obtaining feedback from the user and storing it in the database; and means for optimizing the search results based on the feedback. This enables the provision of remedies that take into account the user's changes in physical condition and psychological state, and continuous optimization of the system using feedback.

[1298] A "user" refers to an individual who uses the system to input changes in their physical condition and emotional state.

[1299] "Changes in physical condition" refers to a state in which a user expresses, in natural language, any abnormalities or problems they have experienced regarding their physical condition.

[1300] "Natural language" refers to language used by humans on a daily basis, and is not limited to any specific form of language description.

[1301] "Audio data" refers to data that records the content of what a user has said in digital format.

[1302] "Analysis" refers to the process of mechanically analyzing input natural language or audio data to identify and classify its meaning and emotions.

[1303] "Keywords" refer to important words extracted from analyzed natural language and speech data.

[1304] "Emotional state" refers to the user's psychological state, which the system identifies through analysis of voice data and other information.

[1305] "Solutions" refer to specific examples of actions or measures suggested in response to changes in the user's physical condition.

[1306] "Health supplements" refer to foods and supplements consumed with the purpose of supporting or improving the user's health.

[1307] "Medical institution information" refers to information about medical facilities such as hospitals and clinics where users can receive treatment.

[1308] A "database" refers to a collection of data that stores and allows searching for information such as treatment methods, health supplements, and medical institutions.

[1309] "Searching" refers to the process of extracting data that matches specific criteria from information stored in a database.

[1310] "Feedback" refers to the act of a user sending back information to the system regarding the effectiveness and satisfaction level of the solutions provided.

[1311] "Optimization" refers to the process by which a system improves its search algorithms and methods of providing solutions based on user feedback, thereby increasing the accuracy of search results in subsequent searches.

[1312] This invention is a medical support system that considers the user's physical and psychological changes, provides the optimal course of action accordingly, and continuously optimizes the system based on feedback. The system analyzes the user's natural language and voice input to identify keywords indicating changes in physical condition and emotional states. This enables more effective health management support.

[1313] Hardware and software to be used

[1314] Devices: Smartphones, tablets, PCs, etc.

[1315] Server: An information processing device with high-performance computing capabilities.

[1316] Natural language processing tools: Google Cloud Natural Language API, IBM Watson Natural Language Understanding.

[1317] Speech analysis tools: Google Cloud Speech-to-Text, Amazon Transcribe.

[1318] Emotion recognition engine: Microsoft Azure Emotion API, Affectiva SDK.

[1319] Database: A database that stores information on treatments, health supplements, and medical institutions.

[1320] System Operation Description

[1321] This system operates using the following steps.

[1322] 1. User's physical condition information and emotional input

[1323] Users open the application on their device and input changes in their physical condition using natural language. For example, they might type, "I've been feeling a bit anemic lately," and then use voice input to say, "I'm very anxious."

[1324] 2. Sending input data

[1325] The terminal formats the acquired text and audio data and sends it to the server.

[1326] 3. Data analysis on the server

[1327] The server analyzes the received data. It uses natural language processing tools to extract relevant keywords such as "anemia" from the text data. It converts the audio data into text using speech analysis tools and identifies emotional states (e.g., "anxiety") using an emotion recognition engine.

[1328] 4. Searching for and generating solutions

[1329] Based on the extracted keywords and emotional state, the server searches the database for appropriate coping strategies, health supplements, and medical information. This may include advice such as "consume iron-rich foods" or "visit a nearby clinic." Furthermore, considering that the emotional state is "anxiety," it may also include additional advice such as "take deep breaths to relax."

[1330] 5. Displaying search results

[1331] The device displays search results received from the server. For example, it might show advice such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax."

[1332] 6. User Feedback

[1333] Users who implement the solution will input feedback regarding its effectiveness and their satisfaction level, and this feedback will also be sent to the server via their device.

[1334] 7. Accumulation and optimization of feedback

[1335] The server stores feedback data in a database and statistically analyzes the effectiveness of the countermeasures. Based on the results of this analysis, the system is optimized to improve the accuracy of subsequent search processes.

[1336] Specific example

[1337] For example, if a user types "I've been feeling a bit anemic lately" and says "I'm very anxious" via voice, the server extracts the keyword "anemia" and the emotional state "anxiety." Based on this, the server searches the database for coping strategies such as "eat iron-rich foods," "take vitamin C along with it," and "get rest," as well as psychological advice such as "take deep breaths to relax," and provides these to the user. The user then uses this information to implement the necessary coping strategies and provides feedback on the results to help optimize the system.

[1338] As a result, the system of the present invention can provide rapid and effective health management support while taking into account the user's physical condition and psychological state.

[1339] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1340] Step 1:

[1341] Users input changes in their physical condition into the device using natural language and voice. For example, they might type "I've been feeling a bit anemic lately" into the text input field and then say "I'm very worried" into the microphone.

[1342] Input: Natural language text and audio data

[1343] Output: Text and audio data temporarily stored on the device.

[1344] Step 2:

[1345] The terminal formats the user's input data. Specifically, it converts text data to JSON format and saves audio data as an audio file. This converts the data into a format that can be transmitted.

[1346] Input: Natural language text and audio data

[1347] Output: Formatted JSON text data and audio files

[1348] Step 3:

[1349] The terminal sends the formatted data to the server. The data is sent using a communication protocol (e.g., HTTP).

[1350] Input: Formatted JSON text data and audio files

[1351] Output: Text and audio data sent to the server

[1352] Step 4:

[1353] The server analyzes the received data. Using natural language processing tools, it extracts keywords related to solutions from the text data. Simultaneously, it converts audio data into text using speech analysis tools and identifies the user's emotional state using an emotion recognition engine.

[1354] Input: Text data and audio data

[1355] Output: Extracted keywords (e.g., "anemia") and emotional states (e.g., "anxiety")

[1356] Step 5:

[1357] The server searches the database for relevant information based on the extracted keywords and emotional state. It retrieves coping strategies, health supplements, and medical information. This includes specific advice such as "consume iron-rich foods" or "visit a nearby clinic."

[1358] Input: Keywords and emotional state

[1359] Output: Search results (solutions, health supplements, medical institution information, etc.)

[1360] Step 6:

[1361] The server generates search results as a response message. It then summarizes specific advice into a single message and sends it to the terminal.

[1362] Input: Search Results

[1363] Output: Response message (Example: "Please increase your iron intake. Here are some recommended supplements.")

[1364] Step 7:

[1365] The terminal analyzes the response message received from the server and displays it to the user. For example, it might be displayed as a message box on the application screen.

[1366] Input: Response message

[1367] Output: Display of the analyzed message

[1368] Step 8:

[1369] The user implements the provided solution. For example, they might purchase and take an iron supplement. Afterwards, they input feedback on the effectiveness and satisfaction level of the solution and send it to their device.

[1370] Input: Feedback on solutions

[1371] Output: Feedback data

[1372] Step 9:

[1373] The device formats the user's feedback data and sends it to the server. This allows the feedback to be reflected in the system.

[1374] Input: Feedback data

[1375] Output: Feedback data sent to the server

[1376] Step 10:

[1377] The server accumulates feedback data and analyzes it statistically. Based on this, it evaluates the effectiveness of the countermeasures and optimizes the search process for subsequent searches.

[1378] Input: Feedback data

[1379] Output: Optimized search algorithms and a list of solutions

[1380] This allows the system to take into account changes in the user's physical and psychological state and continuously provide optimized solutions.

[1381] (Application Example 2)

[1382] 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."

[1383] Traditional health management systems can provide basic coping strategies based on changes in a user's physical condition, but they struggle to offer strategies that take into account the user's emotional state. Furthermore, their limited ability to optimize the system based on feedback made it difficult to provide optimal solutions for individual users. This highlights the need for flexible health management support tailored to the user's psychological state.

[1384] 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.

[1385] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on treatment methods, health supplements, and medical institutions based on the extracted keywords and emotional state, means for displaying the search results to the user, means for obtaining user feedback and storing it in the database, means for optimizing the search results based on the feedback, and further means for emotion recognition. This makes it possible to provide the optimal treatment method that simultaneously considers the user's physical condition and emotions.

[1386] A "user" is someone who uses the system to input changes in their physical condition and emotions.

[1387] "Natural language" refers to the language that humans use on a daily basis, and is used by users to input changes in their physical condition and emotions.

[1388] A "natural language input method" refers to a device or program that provides an interface for users to input changes in their physical condition or emotions in natural language.

[1389] "Analysis means" refers to a device or program that has the function of analyzing input natural language and extracting relevant keywords.

[1390] "Keywords" are highly relevant words or phrases extracted from the input natural language using analysis tools.

[1391] "Emotional state" refers to the psychological state of a user, as recognized by analytical methods.

[1392] "Emotion recognition means" refers to a device or program used to determine a user's psychological state from natural language or speech input.

[1393] "Solutions" refer to methods and means of health management provided based on the user's physical and emotional state.

[1394] "Health supplements" refer to foods and supplements recommended to users for the purpose of maintaining or restoring health.

[1395] "Medical institution information" refers to information such as contact details and addresses of clinics, hospitals, and other medical facilities that provide the medical services that users need.

[1396] A "database" is a collection of data that stores and manages information such as treatment methods, health supplements, and medical institutions in a searchable format.

[1397] A "search tool" refers to a device or program that has the function of extracting necessary information from a database.

[1398] "Display means" refers to a device or program that has the function of visualizing and providing search results to the user.

[1399] "Feedback" refers to information provided to the system about the effectiveness and impressions of the solutions implemented by the user.

[1400] An "optimization tool" is a device or program that has the function of improving the system's search results or solutions based on the feedback it receives.

[1401] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[1402] 1. System Configuration

[1403] This system consists of the following main components:

[1404] User device: (e.g., smartphone or computer)

[1405] Natural language input method: An interface for users to input changes in their physical condition or emotions using natural language.

[1406] Display method: An interface for displaying search results and solutions to the user.

[1407] server:

[1408] Analysis method: Software (e.g., Transformers library) for analyzing user-inputted natural language data and extracting relevant keywords and emotional states.

[1409] Emotion recognition means: Software for identifying a user's emotional state.

[1410] Search method: Software for searching databases for relevant treatments, health supplements, and information on medical institutions.

[1411] Optimization method: Software to improve search results based on feedback provided by users.

[1412] 2. Usage of Hardware and Software

[1413] User terminal:

[1414] Install an application that runs on a smartphone or computer. The user uses this application to input changes in their physical condition and emotions in natural language.

[1415] server:

[1416] The server uses generative AI models for natural language processing and emotion recognition. Specifically, it uses Python and the Transformers library. It analyzes user input and recognizes emotional states.

[1417] An API (Application Programming Interface) endpoint will be set up to communicate with the database and search for information on appropriate treatments, health supplements, and medical institutions.

[1418] After receiving feedback from users, the system is optimized based on statistical analysis.

[1419] 3. Specific Examples

[1420] For example, if a user enters "I've been feeling a bit anemic lately," the server analyzes this input and extracts the keyword "anemia." Simultaneously, it uses an emotion recognition engine to determine the user's feelings and recognize that the user is feeling anxious. The server then provides advice from its database as a solution, such as "consume iron-rich foods," "it's recommended to take them with vitamin C," and "take deep breaths to relax." This allows the user to implement the necessary solutions and provide feedback to the system.

[1421] 4. Example of a prompt statement

[1422] The following are examples of prompts that the user will enter:

[1423] "I've been feeling a bit anemic lately. I'm very worried. What can I do?"

[1424] "I've had a persistent headache. Which medicine would you recommend?"

[1425] "I can't shake off this fatigue. Do you have any recommendations for solutions?"

[1426] Based on these inputs, the system can perform appropriate analysis and searches, and propose the optimal course of action.

[1427] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1428] Step 1:

[1429] Users input changes in their physical condition and emotions into the device using natural language. Specifically, they open a smartphone application and enter text such as, "I've been feeling anemic lately. I'm very worried." The input data is text data in natural language format.

[1430] Step 2:

[1431] The terminal retrieves natural language text entered by the user and prepares an API request to send it to the server. The terminal converts the input text data into JSON format and sends it to the server. The input is the user's input text, and the output is the JSON data sent to the server.

[1432] Step 3:

[1433] The server parses the received JSON data and processes the input natural language to extract keywords. Specifically, it uses a generative AI model (e.g., the Transformers library) to extract keywords such as "anemia" and "anxiety." The input is JSON data, and the output is a list of extracted keywords.

[1434] Step 4:

[1435] The server uses an emotion recognition engine to identify the user's emotional state. Specifically, it uses an emotion recognition model to extract emotions (e.g., "anxiety," "restlessness") from text. The input is the user's text data, and the output is the identified emotional state.

[1436] Step 5:

[1437] The server searches its database for relevant coping strategies, health supplements, and healthcare information based on extracted keywords and emotional states. The server generates search queries and retrieves relevant information from a pre-stored database. Inputs are keywords and emotional states, while output is a list of coping strategies and recommended information.

[1438] Step 6:

[1439] The server consolidates the search results into a single response message and sends it to the terminal. Specifically, it generates a response that includes a list of solutions, recommended health supplements, information on the nearest medical facility, and additional psychological advice. The input is the search results, and the output is the response message.

[1440] Step 7:

[1441] The terminal analyzes the received response message and displays it in a user-friendly format. Specifically, it displays messages such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax," on the application screen. The input is the response message, and the output is the content displayed to the user.

[1442] Step 8:

[1443] The user implements the displayed solution and inputs the results as feedback. Specifically, they use the application to input the effectiveness and their impressions of the solution, such as "It was effective" or "My tension eased." The feedback data is then converted back into JSON format and sent from the terminal to the server. The input is the user's feedback text, and the output is the JSON data sent to the server.

[1444] Step 9:

[1445] The server analyzes the received feedback data and stores it in a database. Furthermore, it performs statistical analysis based on the feedback to continuously optimize search results and solutions. This data is then used for future search and selection processes. The input is feedback data, and the output is an updated database and an optimized list of solutions.

[1446] 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.

[1447] 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.

[1448] 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.

[1449] [Fourth Embodiment]

[1450] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1451] 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.

[1452] 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).

[1453] 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.

[1454] 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.

[1455] 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).

[1456] 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.

[1457] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1458] 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.

[1459] 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.

[1460] 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.

[1461] 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.

[1462] 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".

[1463] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. The specific operation of the system is described below.

[1464] 1. User processing

[1465] 1. Enter your health status

[1466] The user opens the application on their device and enters changes in their physical condition in natural language. For example, they might enter, "I've been feeling a bit anemic lately."

[1467] Once the user has finished entering the information, they click the "Submit" button.

[1468] 2. Terminal processing

[1469] 1. Input acquisition and transmission

[1470] The terminal retrieves the user's input and stores it as data.

[1471] The terminal formats the input data and converts it into a format that can be sent to the server.

[1472] Send the formatted data to the server.

[1473] 3. Server processing

[1474] 1. Input Analysis

[1475] The server analyzes the received data. Specifically, it uses a natural language processing (NLP) program to analyze the input "feeling anemic."

[1476] The analysis extracts relevant keywords (e.g., "anemia," "iron deficiency").

[1477] 2. Obtaining related data

[1478] The server searches the database for appropriate solutions based on the extracted keywords. For example, it might find solutions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[1479] The system uses relevant health supplements (e.g., "iron supplements") and the user's location information to retrieve information about nearby medical facilities.

[1480] 3. Generating and sending responses

[1481] The server consolidates the search results into a single response message. Specifically, it includes the following information:

[1482] List of solutions

[1483] Recommended health supplements

[1484] Information on the nearest medical institution

[1485] The server sends the generated response message to the terminal.

[1486] 4. Terminal processing (continued)

[1487] 1. Obtaining and displaying the response

[1488] The terminal receives and analyzes the response from the server.

[1489] Display the analysis results to the user. For example:

[1490] "To combat anemia, try the following: 1) Eat iron-rich foods, 2) Take iron with vitamin C, 3) Get plenty of rest."

[1491] "Recommended health supplement: Iron supplements"

[1492] "Nearest medical institution: ○○ Clinic (address and contact information)"

[1493] 5. User processing (continued)

[1494] 1. Implementation of countermeasures and provision of feedback

[1495] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[1496] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[1497] 6. Terminal Processing (continued)

[1498] 1. Obtaining and sending feedback

[1499] The device collects user feedback and sends it to the server.

[1500] 7. Server processing (continued)

[1501] 1. Accumulation and optimization of feedback

[1502] The server saves the received feedback to the database.

[1503] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[1504] This allows us to adjust the priority of solutions based on user feedback and improve the accuracy of the system.

[1505] Specific example

[1506] For example, if a user enters "I feel a bit anemic" and submits it, the server analyzes the input and extracts the keyword "anemia." Next, it searches its database for possible solutions such as "eating iron-rich foods," "taking vitamin C along with iron," and "getting rest," and recommends these to the user. It also simultaneously provides information on iron supplements and a guide to a medical institution near the user's home (e.g., "○○ Clinic"). The user then implements these solutions based on this information and provides the results as feedback to the system. This feedback is used to optimize the search results for the next time.

[1507] In this way, the system of the present invention supports the user's health management and enables continuous improvement.

[1508] The following describes the processing flow.

[1509] Step 1:

[1510] The user enters a change in their physical condition. The user opens the application on their device, types "I feel a bit anemic" in natural language into the text input field, and clicks the "Send" button.

[1511] Step 2:

[1512] The terminal obtains user input. The terminal retrieves the data "I feel a bit anemic" from the text input field and converts it into an internal data format.

[1513] Step 3:

[1514] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[1515] Step 4:

[1516] The server receives the data. The server receives the data "I feel a bit anemic" sent from the terminal and passes it to the analysis program.

[1517] Step 5:

[1518] The server performs natural language analysis. Using natural language processing (NLP) tools, the server extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I feel a bit anemic."

[1519] Step 6:

[1520] The server searches the database. Based on the extracted keywords, it searches the database for solutions, health supplements, and medical institution information.

[1521] Step 7:

[1522] The server compiles the search results. It combines the suggested solutions obtained from the search results (e.g., "Eat foods rich in iron," "Take vitamin C"), health supplements (e.g., "Iron supplements"), and information on nearby medical facilities into a single response message.

[1523] Step 8:

[1524] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[1525] Step 9:

[1526] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[1527] Step 10:

[1528] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. For example, the displayed content might be: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic."

[1529] Step 11:

[1530] The user implements the suggested course of action. The user follows the course of action provided by the system, either purchasing the recommended supplement or seeking medical attention.

[1531] Step 12:

[1532] Users provide feedback. Users enter feedback on the effectiveness of the implemented solutions and click the "Submit" button.

[1533] Step 13:

[1534] The device retrieves the feedback. The device retrieves the feedback content from the text input field and converts it into a data format.

[1535] Step 14:

[1536] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[1537] Step 15:

[1538] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[1539] Step 16:

[1540] The server optimizes based on the feedback. It analyzes the received feedback and evaluates the effectiveness of the solutions. This information is used in subsequent search processes to help adjust the priority of solutions.

[1541] This series of processes allows users to quickly and effectively obtain ways to deal with changes in their physical condition, and the system is gradually optimized through feedback.

[1542] (Example 1)

[1543] 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".

[1544] In modern society, users need quick and accurate ways to respond to daily changes in their physical condition. However, for the average user, managing their health and finding appropriate treatment methods is difficult. In particular, for users who do not accurately recognize their own symptoms and lack specialized knowledge, it is difficult to determine what actions to take. Against this backdrop, there is a need for a system that can quickly and accurately analyze changes in the user's physical condition, provide optimal treatment methods, and continuously optimize the system itself based on feedback.

[1545] 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.

[1546] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means including a generative AI model for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user, means for obtaining feedback from the user and storing it in the database, and means for continuously optimizing the search results based on the feedback. As a result, the user can quickly obtain appropriate remedies for changes in their physical condition, and the system itself is continuously improved through feedback, enabling more accurate responses.

[1547] A "user" refers to an individual who uses the system to input their health information and receive appropriate treatment.

[1548] A "terminal" is a device used by a user to access a system, and includes mobile devices and computers.

[1549] "Natural language" refers to the language used in everyday conversation that users use to input changes in their physical condition.

[1550] A "generative AI model" refers to artificial intelligence technology that analyzes natural language data input by users and extracts relevant keywords.

[1551] "Analysis" refers to the process of using generative AI models to process natural language data input by users and extract important information.

[1552] "Keywords" are important words or phrases extracted through analysis, and include information related to changes in the user's physical condition.

[1553] "Solutions" refer to specific actions or advice that users should take based on the extracted keywords.

[1554] "Health supplements" refer to nutritional supplements and vitamins recommended to support the user's health.

[1555] "Medical institutions" refer to facilities such as hospitals and clinics that users can visit to receive appropriate medical treatment.

[1556] A "database" refers to a centralized location where information on treatments, health supplements, and medical institutions is stored.

[1557] "Feedback" refers to information that users provide to the system, evaluating the effectiveness of the solutions and advice offered by the system.

[1558] "Optimization" refers to the process of improving and refining the system's search results and suggestions based on feedback.

[1559] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Specific embodiments for carrying out this invention are described in detail below.

[1560] System Configuration

[1561] This system consists of a multi-stage process that includes user input, data processing by the terminal, and analysis and optimization by the server. The following describes how each of these processes is implemented.

[1562] User processing

[1563] The user uses the application on their device to input changes in their physical condition in natural language. For example, they might input, "I've been feeling a bit anemic lately." This input is captured as text on the application. Once the user has finished inputting, they click the "Submit" button to send the data to the next processing step.

[1564] Terminal processing

[1565] The terminal retrieves user input and first stores it as text data. The software used here is the application's interface; for example, Kotlin or Swift are often used for mobile apps, while React or Angular are commonly used for web apps. Next, the retrieved text data is formatted and converted into a format such as JSON that can be sent to the server. Scripting languages ​​such as Python or JavaScript are used for this process. The formatted data is sent to the server using the HTTPS protocol.

[1566] Server Processing

[1567] The server receives data sent from the terminal and first temporarily stores it in a database. Databases such as MySQL and PostgreSQL are used. Next, the received data is analyzed using a generative AI model. Specifically, NLP models such as BERT (Bidirectional Encoder Representations from Transformers) and GPT-3 (Generative Pre-trained Transformer 3) are used. Through analysis, relevant keywords (e.g., "anemia," "iron deficiency") are extracted from the text. The server then searches the database for appropriate solutions based on the extracted keywords. For example, it might use SQL queries to find suggestions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[1568] Next, the system retrieves information about nearby medical facilities using relevant health supplements (e.g., "iron supplements") and the user's location. This information is then combined into a single response message as search results, and the server sends the generated response message back to the device.

[1569] Terminal response processing

[1570] The terminal receives response messages from the server, parses them, and formats them into a format that can be displayed on the user interface. JavaScript and HTML are often used in the display portion of the application. The analysis results are then displayed to the user. Specifically, the following information is included: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take it with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," "Nearest medical institution: XX Clinic (address and contact information)."

[1571] User feedback

[1572] The user implements the suggested solution and inputs the results as feedback into the application on their device. Once the input is complete, they click the "Submit" button. This feedback is then sent from the device to the server.

[1573] Server feedback processing

[1574] The server stores user feedback in a database. This data is stored in a dedicated table for accumulating user feedback information. Subsequently, statistical analysis is performed based on this feedback data to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches.

[1575] Specific example

[1576] For example, if a user enters "I've been feeling a bit anemic lately" into the device and clicks the "Send" button, the device receives the input, formats it, and sends it to the server. The server analyzes the received data using an NLP model and extracts keywords such as "anemia" and "iron deficiency." Next, it searches the database for solutions such as "consume iron-rich foods," "take vitamin C along with it," and "get rest," and retrieves information on nearby medical facilities along with this information to generate a response. The device receives this response and displays it to the user.

[1577] Users implement solutions and provide feedback on their effectiveness to the system. Based on this feedback, the system is continuously optimized, resulting in more accurate search results in the future.

[1578] Example of a prompt

[1579] "What are some recommended ways to increase iron intake when experiencing symptoms of anemia?"

[1580] In this way, the system of the present invention supports the user's health management, and through continuous system improvement, it enables the provision of more efficient and accurate treatment methods.

[1581] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1582] Step 1: User enters their health status.

[1583] The user opens the application on their device. Next, they input changes in their physical condition or symptoms they are experiencing in natural language. For example, they might input, "I've been feeling a bit anemic lately." Once they have finished inputting, they click the submit button. Thus, the input in this step is the user's natural language text, and the output is the data sent to the device.

[1584] Step 2: Data acquisition and formatting on the device

[1585] The terminal receives natural language text sent by the user. Next, it processes this input data and converts it into a format that can be sent to the server (e.g., JSON). Scripting languages ​​such as Python or JavaScript are used for this process. The input for this step is the user's natural language text, and the output is formatted JSON data. The formatted data is then sent to the server via the HTTPS protocol.

[1586] Step 3: Receiving and temporarily storing data on the server

[1587] The server receives JSON data sent from the terminal. The received data is temporarily stored in a database. Databases such as MySQL or PostgreSQL are used. The input for this step is formatted JSON data, and the output is the information stored in the database.

[1588] Step 4: Natural Language Processing (NLP)

[1589] The server uses a generative AI model to analyze the stored data. Specifically, NLP models such as BERT and GPT-3 extract relevant keywords from natural language text. The input for this step is temporarily stored data, and the output is the extracted keywords. For example, keywords such as "anemia" and "iron deficiency" are extracted.

[1590] Step 5: Retrieve relevant data from the database

[1591] The server searches the database for information on remedies, health supplements, and medical institutions based on the extracted keywords. Using SQL queries, it finds information such as iron-rich foods, ways to consume vitamin C together, and ways to get enough rest. The input for this step is the extracted keywords, and the output is the retrieved information on remedies and medical institutions.

[1592] Step 6: Response generation and sending

[1593] The server generates a response message based on the retrieved information. This message includes the following information: a list of countermeasures, recommended health supplements, and information on the nearest medical facility. The generated response message is sent to the terminal. The input for this step is the search result data, and the output is the generated response message.

[1594] Step 7: Receiving and analyzing the terminal's response

[1595] The terminal receives and analyzes the response message from the server. It then formats the analysis results into a format that can be displayed on the user interface. The input for this step is the response message from the server, and the output is the information displayed on the user interface. Specific examples of the displayed information include: "To deal with anemia, please try the following: 1) Eat foods rich in iron, 2) Take iron with vitamin C, 3) Get enough rest," "Recommended health supplements: Iron supplements," and "Nearest medical institution: XX Clinic (address and contact information)."

[1596] Step 8: User implements corrective action and enters feedback.

[1597] The user implements the suggested solutions, such as purchasing supplements or visiting a medical institution. Afterward, they evaluate whether the provided solutions were effective and enter feedback. Once feedback is complete, they click the "Submit" button. The input in this step is the user's feedback, and the output is the submitted feedback data.

[1598] Step 9: Obtain and send feedback from the device.

[1599] The terminal receives user feedback and formats it into a format that can be sent to the server. The input for this step is the user feedback, and the output is the formatted feedback data. The formatted data is then sent to the server.

[1600] Step 10: Server feedback accumulation and optimization

[1601] The server stores the received feedback data in a database. Based on this feedback data, statistical analysis is performed to optimize the system's search algorithm and keyword weighting. This improves the accuracy of search results in subsequent searches. The input for this step is the feedback data, and the output is the optimized search algorithm. This allows for continuous improvement of the system through feedback.

[1602] (Application Example 1)

[1603] 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".

[1604] Conventional medical support systems made it difficult for users to obtain the information necessary to appropriately address changes in their own health. Furthermore, the lack of means to continuously optimize the system based on feedback made it difficult to provide personalized and appropriate medical information. As a result, users were unable to manage their health quickly and accurately, leading to a decrease in the efficiency of health management.

[1605] 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.

[1606] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords, means for displaying the search results to the user on a visual display device or virtual store, means for obtaining feedback from the user and storing it in the database, means for optimizing the search results based on the feedback, and means for using a generative AI model to suggest remedies and related information corresponding to the changes in physical condition within the virtual store. This allows the user to obtain quick and accurate remedies for changes in their physical condition, and the system is optimized based on the feedback, enabling the provision of personalized and appropriate medical information.

[1607] "User" refers to an individual or legal entity that uses the system.

[1608] "Changes in physical condition" refers to changes or abnormalities in the user's health status.

[1609] "Natural language" refers to the words and sentences that humans use on a daily basis, and does not require any special format or structure for input.

[1610] "Related keywords" refer to words or phrases related to changes in physical condition that the user enters in natural language.

[1611] "Solutions" refer to methods that indicate appropriate responses or improvements to changes in the user's physical condition.

[1612] "Health supplements" refer to substances or products consumed to maintain or promote health.

[1613] A "medical institution" refers to a facility or organization where doctors provide medical care.

[1614] A "database" refers to a system or device for systematically storing and managing large amounts of data.

[1615] A "visual display device" refers to a device such as a monitor or display used to show information to a user.

[1616] A "virtual store" refers to a virtual shop that provides goods and services on the internet.

[1617] "Feedback" refers to the act of users returning feedback on the effectiveness and evaluation of the solutions or information they have provided, as well as the content of that feedback.

[1618] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to generate and analyze information.

[1619] "Optimization" refers to making adjustments and improvements to maximize the performance and efficiency of a system.

[1620] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on that feedback. The system begins with the user inputting changes in their physical condition in natural language.

[1621] System program

[1622] The system is built using the following hardware and software:

[1623] Hardware:

[1624] Mobile devices or information processing devices (smartphones, personal computers, tablets, etc.)

[1625] Visual display devices (monitors, displays, etc.)

[1626] software:

[1627] Natural Language Processing (NLP): Natural Language Toolkit (nltk)

[1628] Server program: Flask

[1629] Machine learning models: scikit-learn

[1630] Database Management System (DBMS)

[1631] Processing procedure

[1632] The server receives information about changes in the user's physical condition in natural language, entered through a mobile device or information processing device. Next, it analyzes the input using natural language processing technology and extracts relevant keywords. Specifically, if the user enters "I've been getting tired easily lately," the server analyzes this input and extracts the keyword "gets tired easily."

[1633] Based on these extracted keywords, the server searches the database for information on appropriate treatments, health supplements, and medical institutions. The search results are then presented to the user as optimal treatments and relevant information using a generative AI model.

[1634] For example, if a user enters "I've been feeling tired lately," the server will search its database for solutions based on the keyword "feeling tired," such as "get enough sleep," "eat a balanced diet," and "reduce stress." It will also simultaneously provide information on health supplements like "iron supplements" and information on nearby medical facilities, such as "○○ Clinic (address and contact information)."

[1635] Users implement the suggested solutions and input their results into the system as feedback. This feedback is collected and stored on the server and used as reference in subsequent search and selection processes. This allows the system's accuracy and efficiency to continuously improve based on user feedback.

[1636] Specific example

[1637] When a user enters "I've been feeling tired lately," the system suggests the most suitable solutions based on that input. For example, it might suggest "getting enough sleep," "eating a balanced diet," or "reducing stress." At the same time, it provides information on nearby medical facilities based on the user's location. Furthermore, it may also display a purchase link for "iron supplements" as a health supplement.

[1638] Example of a prompt

[1639] Please suggest solutions for the user who enters "I've been feeling tired lately." Please also include relevant health supplements and information on the nearest medical facilities.

[1640] In this way, the system of the present invention can continue to support the user's health management and improve the accuracy of providing individualized information.

[1641] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1642] Step 1:

[1643] Users input changes in their physical condition using natural language via a mobile device or information processing device. For example, they might input, "I've been feeling tired lately." After inputting the information, the user clicks the "Submit" button.

[1644] Input: User's natural language description of changes in their physical condition (e.g., "I've been feeling tired lately").

[1645] Output: Natural language input data

[1646] Step 2:

[1647] The terminal acquires the user's natural language input data, formats it, and sends it to the server. The formatted data is often converted to JSON or XML format.

[1648] Input: User's natural language input data (e.g., "I've been feeling tired lately")

[1649] Data processing: Formatting natural language input into JSON or XML.

[1650] Output: Formatted data

[1651] Step 3:

[1652] The server receives formatted data sent from the terminal. The received data is analyzed using a natural language processing (NLP) program, and relevant keywords are extracted. For example, the keyword "easily fatigued" might be extracted.

[1653] Input: Formatted data (e.g., "I've been feeling tired lately")

[1654] Data processing: Keyword extraction using Natural Language Processing (NLP)

[1655] Output: Extracted keywords (e.g., "easily fatigued")

[1656] Step 4:

[1657] The server searches the database for appropriate treatments, health supplements, and medical information based on the extracted keywords. The search results are optimized using a generative AI model for presentation to the user.

[1658] Input: Extracted keywords (e.g., "easily fatigued")

[1659] Data Search: Search for relevant information from the database.

[1660] Data processing: Optimizing information using generative AI models.

[1661] Output: Optimized treatment methods, health supplements, and healthcare information.

[1662] Step 5:

[1663] The server sends optimized information to the terminal. This information includes a list of solutions, recommendations for health supplements, and information on the nearest medical facilities.

[1664] Input: Optimized treatment methods, health supplements, medical institution information

[1665] Data processing: Packaging and transmission of information

[1666] Output: Packaged data

[1667] Step 6:

[1668] The terminal receives data from the server and displays it to the user. The user can view the information through a visual display device. Specifically, this includes lists of countermeasures (e.g., "Get enough sleep," "Eat a balanced diet," "Reduce stress"), recommendations for health supplements (e.g., "Iron supplements"), and information on the nearest medical institution (e.g., "○○ Clinic").

[1669] Input: Packaged data received from the server

[1670] Data processing: Parsing and displaying received data

[1671] Output: Information displayed to the user

[1672] Step 7:

[1673] Users implement the suggested solutions and provide feedback on their effectiveness. They input the effects and evaluations in natural language and click the "Submit" button.

[1674] Input: User feedback (e.g., "I feel less tired")

[1675] Output: Natural language feedback data

[1676] Step 8:

[1677] The device then sends the user's feedback data back to the server. This allows the feedback to be accumulated in the system.

[1678] Input: User's natural language feedback data

[1679] Data processing: Format conversion of natural language feedback

[1680] Output: Formatted feedback data

[1681] Step 9:

[1682] The server receives feedback data and stores it in a database. The stored feedback data is statistically analyzed and used to optimize search results for future searches.

[1683] Input: Formatted feedback data

[1684] Data processing: Accumulation and statistical analysis of feedback data.

[1685] Output: Optimized search algorithm

[1686] Thus, the system of the present invention provides the optimal course of action based on changes in the user's physical condition, and realizes a process in which the system is continuously optimized through that feedback.

[1687] 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.

[1688] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[1689] 1. User processing

[1690] 1. Enter your health status

[1691] Users open the application on their device and input changes in their physical condition using natural language. For example, they might input "I've been feeling a bit anemic lately" and also input any anxiety they feel as a result.

[1692] Once the user has finished entering the information, they click the "Submit" button.

[1693] 2. Terminal processing

[1694] 1. Input acquisition and transmission

[1695] The device acquires user input and stores it as data. This data may include not only text data but also audio data.

[1696] The terminal formats the input data and converts it into a format that can be sent to the server.

[1697] Send the formatted data to the server.

[1698] 3. Server processing

[1699] 1. Input Analysis

[1700] The server analyzes the received data. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the input sentence "I feel a bit anemic."

[1701] If audio data is included, use an audio analysis tool to identify the content and emotion of the statements.

[1702] 2. Recognition by the Emotion Engine

[1703] The server uses an emotion engine to recognize the user's emotional state (e.g., "anxious," "restless," "relaxed") from the analyzed data.

[1704] 3. Obtaining related data

[1705] Based on the extracted keywords and recognized emotional states, the system searches the database for appropriate coping strategies, health supplements, and medical information. For example, it might find solutions such as "consume iron-rich foods," "take vitamin C together," or "get rest."

[1706] If the user's emotional state is identified as "anxiety," advice to alleviate it can also be included.

[1707] 4. Generating and sending responses

[1708] The server consolidates the search results into a single response message. Specifically, it includes the following information:

[1709] List of solutions

[1710] Recommended health supplements

[1711] Information on the nearest medical institution

[1712] Additional psychological advice (e.g., "Take deep breaths to relax")

[1713] The server sends the generated response message to the terminal.

[1714] 4. Terminal processing (continued)

[1715] 1. Obtaining and displaying the response

[1716] The terminal receives a response from the server and analyzes its contents.

[1717] The analysis results are displayed in a format that is easy for the user to understand. For example, the displayed content might include: "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to help you relax."

[1718] 5. User processing (continued)

[1719] 1. Implementation of countermeasures and provision of feedback

[1720] The user then takes the suggested course of action, such as purchasing supplements or visiting a medical institution.

[1721] Evaluate whether the provided solution was effective and enter your feedback. Once you have finished entering your feedback, click the "Submit" button to send it to your device.

[1722] 6. Terminal Processing (continued)

[1723] 1. Obtaining and sending feedback

[1724] The device collects user feedback and sends it to the server.

[1725] 7. Server processing (continued)

[1726] 1. Accumulation and optimization of feedback

[1727] The server saves the received feedback to the database.

[1728] The feedback data will be used to statistically analyze the effectiveness of the solutions and will be referenced in future search and selection processes.

[1729] This allows us to adjust the priority of solutions based on user feedback and improve the accuracy of the system.

[1730] Specific example

[1731] For example, if a user types "I've been feeling a bit anemic lately" and says "I'm very anxious" in voice, the server analyzes the input and extracts the keyword "anemia" and the emotional state of "anxiety." The server then searches its database for coping strategies such as "eat iron-rich foods," "take iron-rich foods," and "get rest," as well as psychological advice such as "take deep breaths to relax," and provides this information to the user. Based on this information, the user implements the necessary coping strategies and provides feedback on the results to contribute to the optimization of the system.

[1732] In this way, the system of the present invention can provide rapid and effective health management support while also taking into account the user's psychological state.

[1733] The following describes the processing flow.

[1734] Step 1:

[1735] The user enters a change in their physical condition. The user opens the application on their device and enters "I've been feeling anemic lately" in natural language into the text input field, along with their feelings about the condition (e.g., "I'm very anxious"). They then click the "Submit" button.

[1736] Step 2:

[1737] The terminal obtains user input. The terminal retrieves the data "I've been feeling anemic lately" and "I'm very anxious" from the text input field and converts it into an internal data format.

[1738] Step 3:

[1739] The terminal sends data to the server. The retrieved data is sent to the server as an HTTP POST request.

[1740] Step 4:

[1741] The server receives the data. The server receives the user input data sent from the terminal ("I've been feeling anemic lately" and "I'm very anxious") and passes it to the analysis program.

[1742] Step 5:

[1743] The server performs natural language analysis. Using natural language processing (NLP) tools, it extracts relevant keywords such as "anemia" and "iron deficiency" from the sentence "I've been feeling a bit anemic lately."

[1744] Step 6:

[1745] The server performs emotion recognition using an emotion engine. From the input "I am very anxious," the emotion engine recognizes the emotional state as "anxiety."

[1746] Step 7:

[1747] The server searches the database. Based on the extracted keywords "anemia" and emotional state "anxiety," it searches the database for appropriate treatments, health supplements, and medical institution information.

[1748] Step 8:

[1749] The server compiles the search results. It combines the suggested solutions (e.g., "Consume foods rich in iron," "Consume vitamin C together," "Get rest"), health supplements (e.g., "Iron supplements"), information on nearby medical facilities, and psychological advice to alleviate anxiety (e.g., "Take deep breaths to relax") into a single response message.

[1750] Step 9:

[1751] The server sends a response to the terminal. The compiled response message is sent to the terminal as an HTTP response.

[1752] Step 10:

[1753] The terminal receives a response. The terminal receives a response from the server and parses its contents.

[1754] Step 11:

[1755] The device displays search results to the user. The analyzed results are displayed in a format that is easy for the user to understand. The displayed content may include statements such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. We also recommend deep breathing to alleviate anxiety. The nearest clinic is XX Clinic."

[1756] Step 12:

[1757] The user implements coping strategies. The user practices the coping strategies provided by the system, such as purchasing supplements or visiting a medical institution. They may also follow advice to alleviate anxiety, such as practicing deep breathing.

[1758] Step 13:

[1759] The user provides feedback. The user enters feedback on the effectiveness of the implemented countermeasures and clicks the "Submit" button to send it to their device.

[1760] Step 14:

[1761] The device retrieves the feedback. The device retrieves the feedback content (e.g., "The iron supplement worked") from the text input field and converts it into a data format.

[1762] Step 15:

[1763] The device sends feedback to the server. The received feedback is sent to the server as an HTTP POST request.

[1764] Step 16:

[1765] The server receives the feedback. The server receives the feedback sent from the terminal and stores it in the database.

[1766] Step 17:

[1767] The server optimizes based on feedback. It analyzes received feedback (e.g., "iron supplements worked") and evaluates the effectiveness of the suggested solutions. This information is used in subsequent search processes to help adjust the priority of suggested solutions.

[1768] This series of processes allows users to acquire coping mechanisms to respond quickly and effectively to changes in their physical condition, and the system is continuously optimized through user feedback. Furthermore, the combination of emotional engines enables detailed responses that also take into account the user's psychological state.

[1769] (Example 2)

[1770] 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".

[1771] Conventional medical support systems have a problem in that they do not adequately suggest the most suitable treatment methods or health supplements in response to changes in the user's physical condition. Furthermore, advice provided without considering the user's psychological state is often ineffective. In addition, there is a lack of mechanisms to continuously optimize the system using user feedback. Therefore, there is a need for a system that can more effectively support users' health management.

[1772] 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.

[1773] In this invention, the server includes means for the user to input changes in their physical condition in natural language and voice data; means for analyzing the input natural language and voice data and extracting relevant keywords and emotional states; means for searching a database for information on remedies, health supplements, and medical institutions based on the extracted keywords and emotional states; means for displaying the search results to the user; means for obtaining feedback from the user and storing it in the database; and means for optimizing the search results based on the feedback. This enables the provision of remedies that take into account the user's changes in physical condition and psychological state, and continuous optimization of the system using feedback.

[1774] A "user" refers to an individual who uses the system to input changes in their physical condition and emotional state.

[1775] "Changes in physical condition" refers to a state in which a user expresses, in natural language, any abnormalities or problems they have experienced regarding their physical condition.

[1776] "Natural language" refers to language used by humans on a daily basis, and is not limited to any specific form of language description.

[1777] "Audio data" refers to data that records the content of what a user has said in digital format.

[1778] "Analysis" refers to the process of mechanically analyzing input natural language or audio data to identify and classify its meaning and emotions.

[1779] "Keywords" refer to important words extracted from analyzed natural language and speech data.

[1780] "Emotional state" refers to the user's psychological state, which the system identifies through analysis of voice data and other information.

[1781] "Solutions" refer to specific examples of actions or measures suggested in response to changes in the user's physical condition.

[1782] "Health supplements" refer to foods and supplements consumed with the purpose of supporting or improving the user's health.

[1783] "Medical institution information" refers to information about medical facilities such as hospitals and clinics where users can receive treatment.

[1784] A "database" refers to a collection of data that stores and allows searching for information such as treatment methods, health supplements, and medical institutions.

[1785] "Searching" refers to the process of extracting data that matches specific criteria from information stored in a database.

[1786] "Feedback" refers to the act of a user sending back information to the system regarding the effectiveness and satisfaction level of the solutions provided.

[1787] "Optimization" refers to the process by which a system improves its search algorithms and methods of providing solutions based on user feedback, thereby increasing the accuracy of search results in subsequent searches.

[1788] This invention is a medical support system that considers the user's physical and psychological changes, provides the optimal course of action accordingly, and continuously optimizes the system based on feedback. The system analyzes the user's natural language and voice input to identify keywords indicating changes in physical condition and emotional states. This enables more effective health management support.

[1789] Hardware and software to be used

[1790] Devices: Smartphones, tablets, PCs, etc.

[1791] Server: An information processing device with high-performance computing capabilities.

[1792] Natural language processing tools: Google Cloud Natural Language API, IBM Watson Natural Language Understanding.

[1793] Speech analysis tools: Google Cloud Speech-to-Text, Amazon Transcribe.

[1794] Emotion recognition engine: Microsoft Azure Emotion API, Affectiva SDK.

[1795] Database: A database that stores information on treatments, health supplements, and medical institutions.

[1796] System Operation Description

[1797] This system operates using the following steps.

[1798] 1. User's physical condition information and emotional input

[1799] Users open the application on their device and input changes in their physical condition using natural language. For example, they might type, "I've been feeling a bit anemic lately," and then use voice input to say, "I'm very anxious."

[1800] 2. Sending input data

[1801] The terminal formats the acquired text and audio data and sends it to the server.

[1802] 3. Data analysis on the server

[1803] The server analyzes the received data. It uses natural language processing tools to extract relevant keywords such as "anemia" from the text data. It converts the audio data into text using speech analysis tools and identifies emotional states (e.g., "anxiety") using an emotion recognition engine.

[1804] 4. Searching for and generating solutions

[1805] Based on the extracted keywords and emotional state, the server searches the database for appropriate coping strategies, health supplements, and medical information. This may include advice such as "consume iron-rich foods" or "visit a nearby clinic." Furthermore, considering that the emotional state is "anxiety," it may also include additional advice such as "take deep breaths to relax."

[1806] 5. Displaying search results

[1807] The device displays search results received from the server. For example, it might show advice such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax."

[1808] 6. User Feedback

[1809] Users who implement the solution will input feedback regarding its effectiveness and their satisfaction level, and this feedback will also be sent to the server via their device.

[1810] 7. Accumulation and optimization of feedback

[1811] The server stores feedback data in a database and statistically analyzes the effectiveness of the countermeasures. Based on the results of this analysis, the system is optimized to improve the accuracy of subsequent search processes.

[1812] Specific example

[1813] For example, if a user types "I've been feeling a bit anemic lately" and says "I'm very anxious" via voice, the server extracts the keyword "anemia" and the emotional state "anxiety." Based on this, the server searches the database for coping strategies such as "eat iron-rich foods," "take vitamin C along with it," and "get rest," as well as psychological advice such as "take deep breaths to relax," and provides these to the user. The user then uses this information to implement the necessary coping strategies and provides feedback on the results to help optimize the system.

[1814] As a result, the system of the present invention can provide rapid and effective health management support while taking into account the user's physical condition and psychological state.

[1815] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1816] Step 1:

[1817] Users input changes in their physical condition into the device using natural language and voice. For example, they might type "I've been feeling a bit anemic lately" into the text input field and then say "I'm very worried" into the microphone.

[1818] Input: Natural language text and audio data

[1819] Output: Text and audio data temporarily stored on the device.

[1820] Step 2:

[1821] The terminal formats the user's input data. Specifically, it converts text data to JSON format and saves audio data as an audio file. This converts the data into a format that can be transmitted.

[1822] Input: Natural language text and audio data

[1823] Output: Formatted JSON text data and audio files

[1824] Step 3:

[1825] The terminal sends the formatted data to the server. The data is sent using a communication protocol (e.g., HTTP).

[1826] Input: Formatted JSON text data and audio files

[1827] Output: Text and audio data sent to the server

[1828] Step 4:

[1829] The server analyzes the received data. Using natural language processing tools, it extracts keywords related to solutions from the text data. Simultaneously, it converts audio data into text using speech analysis tools and identifies the user's emotional state using an emotion recognition engine.

[1830] Input: Text data and audio data

[1831] Output: Extracted keywords (e.g., "anemia") and emotional states (e.g., "anxiety")

[1832] Step 5:

[1833] The server searches the database for relevant information based on the extracted keywords and emotional state. It retrieves coping strategies, health supplements, and medical information. This includes specific advice such as "consume iron-rich foods" or "visit a nearby clinic."

[1834] Input: Keywords and emotional state

[1835] Output: Search results (solutions, health supplements, medical institution information, etc.)

[1836] Step 6:

[1837] The server generates search results as a response message. It then summarizes specific advice into a single message and sends it to the terminal.

[1838] Input: Search Results

[1839] Output: Response message (Example: "Please increase your iron intake. Here are some recommended supplements.")

[1840] Step 7:

[1841] The terminal analyzes the response message received from the server and displays it to the user. For example, it might be displayed as a message box on the application screen.

[1842] Input: Response message

[1843] Output: Display of the analyzed message

[1844] Step 8:

[1845] The user implements the provided solution. For example, they might purchase and take an iron supplement. Afterwards, they input feedback on the effectiveness and satisfaction level of the solution and send it to their device.

[1846] Input: Feedback on solutions

[1847] Output: Feedback data

[1848] Step 9:

[1849] The device formats the user's feedback data and sends it to the server. This allows the feedback to be reflected in the system.

[1850] Input: Feedback data

[1851] Output: Feedback data sent to the server

[1852] Step 10:

[1853] The server accumulates feedback data and analyzes it statistically. Based on this, it evaluates the effectiveness of the countermeasures and optimizes the search process for subsequent searches.

[1854] Input: Feedback data

[1855] Output: Optimized search algorithms and a list of solutions

[1856] This allows the system to take into account changes in the user's physical and psychological state and continuously provide optimized solutions.

[1857] (Application Example 2)

[1858] 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".

[1859] Traditional health management systems can provide basic coping strategies based on changes in a user's physical condition, but they struggle to offer strategies that take into account the user's emotional state. Furthermore, their limited ability to optimize the system based on feedback made it difficult to provide optimal solutions for individual users. This highlights the need for flexible health management support tailored to the user's psychological state.

[1860] 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.

[1861] In this invention, the server includes means for the user to input changes in their physical condition in natural language, means for analyzing the input natural language and extracting relevant keywords, means for searching a database for information on treatment methods, health supplements, and medical institutions based on the extracted keywords and emotional state, means for displaying the search results to the user, means for obtaining user feedback and storing it in the database, means for optimizing the search results based on the feedback, and further means for emotion recognition. This makes it possible to provide the optimal treatment method that simultaneously considers the user's physical condition and emotions.

[1862] A "user" is someone who uses the system to input changes in their physical condition and emotions.

[1863] "Natural language" refers to the language that humans use on a daily basis, and is used by users to input changes in their physical condition and emotions.

[1864] A "natural language input method" refers to a device or program that provides an interface for users to input changes in their physical condition or emotions in natural language.

[1865] "Analysis means" refers to a device or program that has the function of analyzing input natural language and extracting relevant keywords.

[1866] "Keywords" are highly relevant words or phrases extracted from the input natural language using analysis tools.

[1867] "Emotional state" refers to the psychological state of a user, as recognized by analytical methods.

[1868] "Emotion recognition means" refers to a device or program used to determine a user's psychological state from natural language or speech input.

[1869] "Solutions" refer to methods and means of health management provided based on the user's physical and emotional state.

[1870] "Health supplements" refer to foods and supplements recommended to users for the purpose of maintaining or restoring health.

[1871] "Medical institution information" refers to information such as contact details and addresses of clinics, hospitals, and other medical facilities that provide the medical services that users need.

[1872] A "database" is a collection of data that stores and manages information such as treatment methods, health supplements, and medical institutions in a searchable format.

[1873] A "search tool" refers to a device or program that has the function of extracting necessary information from a database.

[1874] "Display means" refers to a device or program that has the function of visualizing and providing search results to the user.

[1875] "Feedback" refers to information provided to the system about the effectiveness and impressions of the solutions implemented by the user.

[1876] An "optimization tool" is a device or program that has the function of improving the system's search results or solutions based on the feedback it receives.

[1877] This invention is a medical support system that provides optimal treatment methods based on changes in the user's physical condition and continuously optimizes the system based on feedback. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it becomes possible to provide treatment methods that also take the user's psychological state into consideration.

[1878] 1. System Configuration

[1879] This system consists of the following main components:

[1880] User device: (e.g., smartphone or computer)

[1881] Natural language input method: An interface for users to input changes in their physical condition or emotions using natural language.

[1882] Display method: An interface for displaying search results and solutions to the user.

[1883] server:

[1884] Analysis method: Software (e.g., Transformers library) for analyzing user-inputted natural language data and extracting relevant keywords and emotional states.

[1885] Emotion recognition means: Software for identifying a user's emotional state.

[1886] Search method: Software for searching databases for relevant treatments, health supplements, and information on medical institutions.

[1887] Optimization method: Software to improve search results based on feedback provided by users.

[1888] 2. Usage of Hardware and Software

[1889] User terminal:

[1890] Install an application that runs on a smartphone or computer. The user uses this application to input changes in their physical condition and emotions in natural language.

[1891] server:

[1892] The server uses generative AI models for natural language processing and emotion recognition. Specifically, it uses Python and the Transformers library. It analyzes user input and recognizes emotional states.

[1893] An API (Application Programming Interface) endpoint will be set up to communicate with the database and search for information on appropriate treatments, health supplements, and medical institutions.

[1894] After receiving feedback from users, the system is optimized based on statistical analysis.

[1895] 3. Specific Examples

[1896] For example, if a user enters "I've been feeling a bit anemic lately," the server analyzes this input and extracts the keyword "anemia." Simultaneously, it uses an emotion recognition engine to determine the user's feelings and recognize that the user is feeling anxious. The server then provides advice from its database as a solution, such as "consume iron-rich foods," "it's recommended to take them with vitamin C," and "take deep breaths to relax." This allows the user to implement the necessary solutions and provide feedback to the system.

[1897] 4. Example of a prompt statement

[1898] The following are examples of prompts that the user will enter:

[1899] "I've been feeling a bit anemic lately. I'm very worried. What can I do?"

[1900] "I've had a persistent headache. Which medicine would you recommend?"

[1901] "I can't shake off this fatigue. Do you have any recommendations for solutions?"

[1902] Based on these inputs, the system can perform appropriate analysis and searches, and propose the optimal course of action.

[1903] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1904] Step 1:

[1905] Users input changes in their physical condition and emotions into the device using natural language. Specifically, they open a smartphone application and enter text such as, "I've been feeling anemic lately. I'm very worried." The input data is text data in natural language format.

[1906] Step 2:

[1907] The terminal retrieves natural language text entered by the user and prepares an API request to send it to the server. The terminal converts the input text data into JSON format and sends it to the server. The input is the user's input text, and the output is the JSON data sent to the server.

[1908] Step 3:

[1909] The server parses the received JSON data and processes the input natural language to extract keywords. Specifically, it uses a generative AI model (e.g., the Transformers library) to extract keywords such as "anemia" and "anxiety." The input is JSON data, and the output is a list of extracted keywords.

[1910] Step 4:

[1911] The server uses an emotion recognition engine to identify the user's emotional state. Specifically, it uses an emotion recognition model to extract emotions (e.g., "anxiety," "restlessness") from text. The input is the user's text data, and the output is the identified emotional state.

[1912] Step 5:

[1913] The server searches its database for relevant coping strategies, health supplements, and healthcare information based on extracted keywords and emotional states. The server generates search queries and retrieves relevant information from a pre-stored database. Inputs are keywords and emotional states, while output is a list of coping strategies and recommended information.

[1914] Step 6:

[1915] The server consolidates the search results into a single response message and sends it to the terminal. Specifically, it generates a response that includes a list of solutions, recommended health supplements, information on the nearest medical facility, and additional psychological advice. The input is the search results, and the output is the response message.

[1916] Step 7:

[1917] The terminal analyzes the received response message and displays it in a user-friendly format. Specifically, it displays messages such as, "As a remedy, please consume foods rich in iron. Here are some recommended iron supplements. The nearest clinic is XX Clinic. We also recommend deep breathing to relax," on the application screen. The input is the response message, and the output is the content displayed to the user.

[1918] Step 8:

[1919] The user implements the displayed solution and inputs the results as feedback. Specifically, they use the application to input the effectiveness and their impressions of the solution, such as "It was effective" or "My tension eased." The feedback data is then converted back into JSON format and sent from the terminal to the server. The input is the user's feedback text, and the output is the JSON data sent to the server.

[1920] Step 9:

[1921] The server analyzes the received feedback data and stores it in a database. Furthermore, it performs statistical analysis based on the feedback to continuously optimize search results and solutions. This data is then used for future search and selection processes. The input is feedback data, and the output is an updated database and an optimized list of solutions.

[1922] 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.

[1923] 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.

[1924] 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.

[1925] 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.

[1926] 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.

[1927] 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.

[1928] 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.

[1929] 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.

[1930] 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."

[1931] 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. ...

Claims

1. A means for users to input changes in their physical condition in natural language, A means for analyzing the input natural language and extracting relevant keywords, A means for searching a database for information on countermeasures, health supplements, and medical institutions based on the extracted keywords, Means for displaying the aforementioned search results to the user, A means for obtaining user feedback and storing it in the database, A means for optimizing search results based on the aforementioned feedback, A system that includes this.

2. The system according to claim 1, characterized in that the natural language input means is implemented as an application executed on a mobile terminal or computer.

3. The system according to claim 1, characterized in that the feedback relates to the effectiveness of the countermeasures, and the optimization means adjusts the priority of the countermeasures based on a statistical analysis of the feedback.

Images