System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting information on a wrong case; means for receiving the input information and storing the information in a database; means for using a generated AI to optimize the stored information; means for receiving a medical history and worries from a user and retrieving a similar case from the database; means for providing a retrieval result to the user; and means for connecting users in the same situation to each other by chat.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In the medical field, when faced with failed or difficult-to-treat cases, doctors often find it difficult to find appropriate solutions. Furthermore, patients and their families often lack access to information about similar situations, leaving them feeling isolated and anxious. Current medical literature and textbooks only contain successful cases, and there is insufficient information on specific countermeasures and treatment methods for failed cases. This raises the possibility of similar failures being repeated, making it difficult for both doctors and patients to receive treatment with peace of mind. To solve these problems, a system is needed that systematically collects and shares information about failed cases and provides useful information for both doctors and patients. [Means for solving the problem]

[0005] This invention provides a system that uses generative AI to input information about failed or difficult-to-treat cases, and then receives, stores, and optimizes that information. When users input their medical history and concerns, the system uses that information to search for similar cases in a database and provides treatments, progress, and explanations. Furthermore, with consent, users with similar circumstances can connect via chat. This system aggregates information about failed cases and builds a database that maintains accuracy and relevance. This allows doctors to find appropriate treatment methods and explanations, and also gives patients and their families the feeling that they are not alone, providing psychological relief. Furthermore, by sharing information with pharmaceutical companies and medical device manufacturers, it can contribute to the development of effective treatments.

[0006] A "failed case" refers to a medical procedure or treatment that did not produce the expected results.

[0007] "Means for inputting information" refers to an interface that allows a user to input information about a failed case into the system.

[0008] "Means for receiving information and storing it in a database" refers to the process by which the server receives the input information and stores it appropriately in a database.

[0009] "Generative AI methods" refers to processes that use artificial intelligence to analyze and optimize stored information.

[0010] "Means for searching for similar cases" refers to the process of searching a database for cases with the most similar characteristics based on the medical history and concerns entered by the user.

[0011] "Means for providing search results to the user" refers to the process of presenting information on the searched similar cases to the user.

[0012] "Means of connecting through chat" refers to the process of creating and providing chat rooms for users in the same situation to share information.

[0013] "Means for maintaining the accuracy and relevance of information" refers to the process for verifying the accuracy of collected information and maintaining its relevance by appropriately classifying and organizing it.

[0014] "Means for inputting medical history and concerns" refers to an interface that allows a user to provide the system with their current medical history and concerns.

[0015] "Consent obtained" refers to when a user gives permission to use the chat function or information sharing.

[0016] "Information sharing with pharmaceutical companies and medical device manufacturers" refers to the process of sharing collected medical information with medical-related companies to contribute to the development of new treatments and medical devices.

[0017] "Gaining a sense of psychological security" refers to the sense of security that users feel through sharing information with others in the same situation. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a 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.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0032] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This invention is a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The system aims to provide a forum for sharing information that is beneficial for both doctors and patients.

[0040] Data Collection Module Embodiments

[0041] Entering information

[0042] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface must be designed to be intuitive and easy to use.

[0043] Users can add more detailed information as needed and even upload related documents and reports.

[0044] Sending and Receiving Information

[0045] The terminal formats the information entered by the user and transmits it over the Internet to a server.

[0046] The server receives the submitted information and stores it in the appropriate database, performing some initial evaluation and checks to ensure the information is consistent and accurate.

[0047] Database Construction Module Embodiments

[0048] Data Acquisition and Optimization

[0049] The server periodically retrieves information on all failed and difficult-to-treat cases stored in the database.

[0050] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[0051] Saving optimization data

[0052] The optimized data is then stored in the database again and used when the user searches later.

[0053] Case Search Module Embodiments

[0054] Enter your medical history and concerns

[0055] Users input their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0056] Submitting and Retrieving Information

[0057] The terminal transmits the input information to the server.

[0058] The server analyzes the received information and searches the database for similar cases, taking into account the treatment, prognosis, and explanation of the case.

[0059] Providing search results

[0060] The server generates information about the searched similar cases and transmits it to the terminal.

[0061] The terminal displays the received search results to the user, who can then plan the next course of treatment based on the provided information.

[0062] Chat Function Module Embodiment

[0063] Obtaining User Consent

[0064] The user confirms on the device that they agree to use the chat function.

[0065] Sending and matching consent information

[0066] The terminal transmits the consent information to the server.

[0067] The server searches the database for users in the same situation based on the consent information and performs matching.

[0068] Creating a chat room

[0069] The server creates a chat room for the matched users.

[0070] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[0071] Information sharing and support

[0072] In the chat room, users can share information and experiences about failed cases, which gives users a sense of psychological security.

[0073] Specific examples

[0074] Example 1: When a user enters information and searches for similar cases

[0075] The user enters details about their failed surgery into the terminal.

[0076] The terminal sends the information to the server, which then searches the database for similar cases.

[0077] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[0078] Example 2: When users share information through chat

[0079] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[0080] The server generates a chat room and notifies the user through the terminal.

[0081] Users share information, experiences and advice with other users in chat rooms.

[0082] This invention is a system that contributes to solving problems in the medical field by effectively collecting and optimizing information on failed cases and providing it to users, allowing both medical professionals and patients to proceed with treatment with peace of mind.

[0083] The processing flow will be explained below.

[0084] Data collection module processing flow

[0085] Step 1:

[0086] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[0087] Step 2:

[0088] The terminal formats the entered information and sends it to the server.

[0089] Step 3:

[0090] The server performs an initial evaluation of the information received to check for accuracy and consistency.

[0091] Step 4:

[0092] The server stores the information that passes the initial evaluation in a database.

[0093] Database construction module processing flow

[0094] Step 1:

[0095] The server periodically retrieves all data stored in the database.

[0096] Step 2:

[0097] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[0098] Step 3:

[0099] The server saves the optimized data back into the database.

[0100] Case search module processing flow

[0101] Step 1:

[0102] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0103] Step 2:

[0104] The terminal transmits the input information to the server.

[0105] Step 3:

[0106] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[0107] Step 4:

[0108] The server generates search results and sends them to the terminal.

[0109] Step 5:

[0110] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[0111] Chat function module processing flow

[0112] Step 1:

[0113] The user will be asked to confirm consent to use of the chat feature on their device.

[0114] Step 2:

[0115] The terminal transmits the consent information to the server.

[0116] Step 3:

[0117] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0118] Step 4:

[0119] The server creates a chat room for the matched users.

[0120] Step 5:

[0121] The terminal notifies the user of the chat room information.

[0122] Step 6:

[0123] Users can join chat rooms and share information with other users, which gives them a sense of psychological security.

[0124] Example 1

[0125] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0126] In the current medical field, information about failed or difficult-to-treat cases is not effectively shared, making it difficult for doctors and patients to find the optimal treatment. Furthermore, there are few forums for users in the same situation to share information, making it difficult to obtain psychological support. To improve this situation, a system is needed that collects, optimizes, and shares reliable information among users.

[0127] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0128] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in an information storage device, a means for using a generative AI model to optimize the stored information, a means for receiving medical history and concerns from the user and searching for similar cases from the information storage device, a means for providing the search results to the user, and a means for connecting users in similar situations through chat. This makes it possible to collect, optimize, and provide highly reliable information. Users can also share information and receive psychological support.

[0129] A "failure case" is a medical case in which a treatment did not achieve the intended result.

[0130] "Information storage device" refers to equipment or systems for storing and managing data and information.

[0131] A "generative AI model" is an artificial intelligence model that analyzes large amounts of data and generates an output that is optimal for a specific task.

[0132] "Medical history" refers to information that records a patient's past illnesses and treatment history.

[0133] "Worries" refer to health-related problems or anxieties that the user currently has.

[0134] A "similar case" is a case in which the current case and a past case share similarities.

[0135] "Chat" is a form of communication in which users exchange messages in real time.

[0136] "Matching" is the process of connecting users with similar circumstances and needs.

[0137] A "chat room" is a virtual space where specific users can converse and exchange information.

[0138] This invention is a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using a generative AI model, and provides it to users. This system promotes information sharing in medical settings and makes it easier for users to exchange information.

[0139] Hardware and software used

[0140] server

[0141] The server uses a common cloud computing platform (e.g., a cloud service provider's infrastructure).

[0142] MySQL is used for database management.

[0143] A large-scale language model is used as the generative AI model.

[0144] Terminal

[0145] A terminal is a device used by a user, such as a computer or smartphone, that provides an input interface.

[0146] The front end uses an interactive web application (e.g., a JavaScript framework) that runs in a web browser.

[0147] It uses Node.js for the backend.

[0148] Program processing explanation

[0149] Data collection

[0150] The user uses the terminal to input information about failed or difficult cases (such as progress, treatment, details, and how to explain the procedure to the family). The terminal converts this information into JSON format and sends it to the server via an HTTP POST request. The server analyzes the received data and stores it in a MySQL database.

[0151] Data Optimization

[0152] The server periodically retrieves information on failed or difficult-to-treat cases from the database, analyzes and classifies the data using a generative AI model, and optimizes it by removing incomplete and duplicate data.

[0153] Case Search

[0154] The user inputs their current medical history and concerns into the device. The device sends this information to the server, which then uses a generative AI model to search for similar cases. The server generates search results and sends them to the device. The user then decides on the next course of treatment based on this information.

[0155] Chat feature

[0156] The user agrees to use the chat function, and the device sends the consent information to the server. The server searches the database for users with similar circumstances and matches them. A chat room is created for the matched user, and the user joins the chat room through the device.

[0157] Specific examples

[0158] Example 1: User inputs information to search for similar cases

[0159] The user enters details about a failed surgery last year into the terminal, including detailed information about the patient's infection outbreak and treatment protocol.

[0160] The device converts this data into JSON format and sends it to the server.

[0161] The server inputs this information into a generative AI model and searches a database for similar cases.

[0162] Treatment and prognosis information for similar cases, such as "cases where similar surgical failures have occurred in the past," will be provided to the terminal.

[0163] Example 2: When users share information through chat

[0164] The user agrees to use the chat function and enters consent information on the device.

[0165] The terminal sends the consent information to the server, and the server searches for users in similar situations.

[0166] The server creates a chat room for the matched users and notifies the terminal.

[0167] Users join chat rooms and share information about "experiences of failed surgery" and "how to explain to family members."

[0168] Prompt Sentence Examples

[0169] An example of a prompt that the user might enter is:

[0170] "Please provide details of any infections that occurred during the patient's surgical course. Upload any relevant documentation as needed."

[0171] This system allows reliable information to be collected and optimized in the medical field, and enables users to share information effectively with each other.

[0172] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0173] Step 1:

[0174] The user uses the input interface on the terminal to input information about failed or difficult-to-treat cases (such as progress, treatment, details, and how to explain to the family).

[0175] Input: Text information and related materials (e.g. PDF files) on failed or difficult-to-treat cases

[0176] What happens: A user fills in a form with details about a "failed surgery due to infection" and uploads a PDF file of the associated treatment protocol.

[0177] Step 2:

[0178] The device converts the input information into JSON format and sends it to the server via an HTTP POST request.

[0179] Input: User-entered text information and uploaded files

[0180] Output: Data converted to JSON format

[0181] Specific operation: The device generates a JSON object containing details of "surgery failed due to infection" and related protocols and sends it to the server.

[0182] Step 3:

[0183] The server analyzes the received data and stores it in a MySQL database.

[0184] Input: JSON format data

[0185] Output: Information stored in the database

[0186] Specific operation: The server parses the JSON data and stores the data "Surgery failed due to infection" in the database.

[0187] Step 4:

[0188] The server periodically retrieves information on failed or difficult-to-treat cases from the database and analyzes and classifies the data using a generative AI model.

[0189] Input: Information on failed cases in the database

[0190] Output: Optimized data

[0191] How it works: The server runs a scheduled task at night, extracting new data from the database and inputting it into the generative AI model to generate optimized data.

[0192] Step 5:

[0193] The server removes incomplete and duplicate data and stores the optimized data back into the database.

[0194] Input: Data analyzed and optimized by the generative AI model

[0195] Output: Optimized data stored in the database

[0196] Specific operation: The server deletes duplicate and incomplete data and stores it in the database as clean data.

[0197] Step 6:

[0198] The user inputs their current medical history and concerns into the terminal.

[0199] Input: Information about the user's medical history and concerns

[0200] Output: Data sent to the server as an HTTP request

[0201] Specific operation: The user inputs "chest pain" and "recent medical history."

[0202] Step 7:

[0203] The device sends the input information to the server, which then uses the generated AI model to search for similar cases in the database.

[0204] Input: Information about the user's medical history and concerns

[0205] Output: Search results for similar cases

[0206] Specific operation: The server inputs prompts into the generative AI model and retrieves relevant cases from the database.

[0207] Step 8:

[0208] The server generates search results and sends them to the terminal, which displays them to the user.

[0209] Input: Search result data

[0210] Output: Similar case information provided to the user

[0211] Specific operation: The server collects data on "cases of similar chest pain in the past" and sends it to the terminal, which then displays it to the user.

[0212] Step 9:

[0213] The user agrees to use the chat function, and the device sends the consent information to the server.

[0214] Input: Chat function usage consent information

[0215] Output: The consent information sent to the server

[0216] Specific operation: The user clicks the "Agree to Terms of Use for Chat Function" button. The device sends a request to the server.

[0217] Step 10:

[0218] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0219] Input: consent information

[0220] Output: Matched user information

[0221] What happens: The server searches its database for other consenting users and finds the best match.

[0222] Step 11:

[0223] The server creates a chat room for the matched users and notifies the terminal.

[0224] Input: Matched user information

[0225] Output: Chat room creation and notification

[0226] Specific operation: The server sends a "matching completion notification" to the terminal and provides the user with a link to the chat room.

[0227] Step 12:

[0228] The user receives a notification and joins the chat room.

[0229] Input: Chat room link

[0230] Output: Conversations in participating chat rooms

[0231] What happens: A user clicks on a chat room link, accesses the chat room, and shares information with other users.

[0232] (Application example 1)

[0233] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0234] Conventional medical information systems do not adequately manage or share information about failed or difficult-to-treat cases, making it difficult for both doctors and patients to select effective treatments. Furthermore, there is a lack of information about treatment costs and optimal payment methods, which can place a heavy financial burden on patients. Furthermore, there are limited opportunities for patients in the same situation to share information, and psychological support is also insufficient.

[0235] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0236] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generating AI to optimize the stored information, a means for receiving the user's medical history and concerns and searching the database for similar cases, a means for providing the user with the search results, a means for users with similar circumstances to connect via chat, and a means for users to select the optimal payment plan based on the treatment content and costs. This allows doctors and patients to effectively share information, enabling more appropriate treatment options, and patients to reduce their financial burden by selecting the optimal payment plan. Furthermore, patients with similar circumstances can share information and receive psychological support.

[0237] "Failure cases" refer to cases in which treatment did not go as expected and resulted in unexpected outcomes.

[0238] "Means for inputting information" refers to a device or interface that allows a user to input information about a failure case.

[0239] "Means for receiving information and storing it in a database" refers to a device or system that allows the server to receive input information and store it in a database.

[0240] "Generative AI instruments" refers to instruments that use artificial intelligence technology to analyze, optimize, and classify information.

[0241] "Means for receiving medical history and concerns and searching for similar cases from a database" refers to a device or system that receives a user's medical history and concerns as input and searches for similar cases from a database based on that information.

[0242] The term "means for providing search results to the user" refers to a device or system that outputs information on searched similar cases to the user.

[0243] "A means for users in similar circumstances to connect through chat" refers to a device or system that has the functionality to enable users with similar conditions to communicate through chat.

[0244] The "means for selecting a payment plan" refers to a device or system that allows a user to select the optimal payment method based on the treatment content and treatment costs.

[0245] A "database" refers to a system or device that stores information in an organized manner so that it can be retrieved or accessed later.

[0246] "Financial burden" refers to the financial costs incurred by the user in relation to the cost of treatment.

[0247] System Overview

[0248] This invention is a system that integrates medical information management and the proposal of optimal payment plans. The system inputs, stores, optimizes, searches, and proposes information about failed cases, and then provides users with optimal payment plans based on that information. The system can use a smartphone application and operates in conjunction with a cloud-based server. Its main components include a database, a generative AI model, and a user interface.

[0249] Data collection and storage

[0250] Users enter detailed information about their failed cases through a smartphone app. This information includes the course of treatment, the treatment methods used, case details, and a breakdown of treatment costs. The entered information is sent to a server via the Internet and stored in a database. The input interface is designed to be intuitive and easy to use during this process.

[0251] Data Optimization

[0252] The server periodically retrieves the information stored in the database and uses a generative AI model (e.g., GPT-3) to analyze, optimize, and classify the information. During this process, incomplete and duplicate data is removed and processed to produce accurate and useful information. The optimized data is then used for user searches and suggestions.

[0253] Case search and suggestions

[0254] When a user enters their current medical history and concerns into the app, that information is sent to the server, which then searches the database for similar cases and uses generative AI to suggest appropriate treatments, prognoses, and necessary explanations. This information is displayed intuitively to the user.

[0255] Payment plan proposal

[0256] Furthermore, when users input the details of treatment and costs, the AI ​​generator will use that information to suggest the optimal payment plan, which may include installment payments, loans, or changing insurance plans, allowing users to choose the plan that best suits their financial situation.

[0257] Chat feature

[0258] It also provides a chat function for users to share information and support each other. If a user agrees, the server searches the database for other users in the same situation, matches them, and creates a chat room. In the chat room, users can exchange experiences and advice about treatment.

[0259] Hardware and software used

[0260] The main hardware includes smartphones (iOS, Android), cloud-based servers (AWS, Google Cloud), and software using generative AI models (GPT-3) and database management systems (SQL, NoSQL).

[0261] Prompt Sentence Examples

[0262] Examples of prompts used in this system are as follows:

[0263] "If a patient undergoing diabetes treatment has an annual treatment cost of 500,000 yen, of which 70% is covered by insurance, how would generative AI optimize the payment plan?"

[0264] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0265] Step 1:

[0266] Users enter information about failed cases through a smartphone app, including the treatment progress, treatment methods used, case details, and a breakdown of treatment costs. The information is then sent to the device via an input interface.

[0267] Step 2:

[0268] The device formats the information it receives and sends it over the Internet to a server, which stores the data and performs an initial evaluation and validation check. Correct data is then stored in a database.

[0269] Step 3:

[0270] The server periodically retrieves the information stored in the database and optimizes the data using a generative AI model (e.g., GPT-3). Specifically, the generative AI removes incomplete and duplicate data and converts it into accurate and useful information. This is where the data is optimized.

[0271] Step 4:

[0272] The user enters their current medical history and concerns into a smartphone app. This information includes details of symptoms and past treatment history. The entered information is then sent back to the server via the device.

[0273] Step 5:

[0274] The server analyzes the received patient information and searches the database for similar cases. During this process, the generative AI searches for relevant data, including treatment, prognosis, and explanation methods, and extracts the optimal solution. The search results are then provided to the user in an optimized form.

[0275] Step 6:

[0276] When a user enters the details of treatment and costs into the smartphone app, the information is sent to a server. The server analyzes this information and uses generative AI to propose the optimal payment plan. Proposed plans include installment payments, loans, and changes to insurance plans.

[0277] Step 7:

[0278] The server generates payment plan proposals and provides them to the user via a smartphone app, who can then select the plan that best suits their financial situation.

[0279] Step 8:

[0280] When a user agrees to use the chat function, the device sends the consent information to the server, which then searches the database for other users with similar circumstances and matches them. A chat room is then created, allowing users to share information with other users.

[0281] Step 9:

[0282] In the chat room, users exchange experiences and advice about failed cases, which allows users to receive psychological support and deepen their knowledge about better treatments and payment methods.

[0283] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0284] This invention is an integrated system that combines an emotion engine with a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The emotion engine recognizes the user's emotional state, provides optimal information, and optimizes the interface, improving the user experience.

[0285] Data Collection Module Embodiments

[0286] Entering information

[0287] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface will be designed to be intuitive and easy to use so that users do not feel stressed.

[0288] Sending and Receiving Information

[0289] The terminal formats the entered information and transmits it over the Internet to a server.

[0290] The server receives the transmitted information and stores it in the appropriate database, where it performs some initial evaluation and checks to ensure the information is consistent and accurate.

[0291] Embodiment using emotion engine

[0292] Emotion recognition

[0293] The server recognizes emotions in real time from the content and actions entered by the user into the device, using natural language processing and image analysis technologies.

[0294] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[0295] Interface optimization

[0296] Emotion-based information provision

[0297] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is under a lot of stress, it will prioritize displaying encouraging words and success stories.

[0298] The terminal displays the information received from the server in an appropriate format for the user.

[0299] Database Construction Module Embodiments

[0300] Data Acquisition and Optimization

[0301] The server periodically retrieves all data stored in the database.

[0302] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[0303] Saving optimization data

[0304] The optimized data is then stored in the database again and used when the user searches later.

[0305] Case Search Module Embodiments

[0306] Enter your medical history and concerns

[0307] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0308] Submitting and Retrieving Information

[0309] The terminal transmits the input information to the server.

[0310] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[0311] Providing search results

[0312] The server generates search results and sends them to the terminal.

[0313] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[0314] Chat Function Module Embodiment

[0315] Obtaining User Consent

[0316] The user will be asked to confirm consent to use of the chat feature on their device.

[0317] Sending and matching consent information

[0318] The terminal transmits the consent information to the server.

[0319] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0320] Creating a chat room

[0321] The server creates a chat room for the matched users.

[0322] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[0323] Sentiment Analysis and Support

[0324] Within the chat room, an emotion engine analyzes users' emotions and provides appropriate support and advice, promoting a sense of psychological security.

[0325] Specific examples

[0326] Example 1: When a user enters information and searches for similar cases

[0327] The user inputs details about their failed surgery into the terminal, and the emotion engine recognizes the user's emotions from the input.

[0328] The device sends the information to the server, which then searches a database for similar cases, taking into account emotional data and providing appropriate information preferentially.

[0329] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[0330] Example 2: When users share information through chat

[0331] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[0332] The server generates a chat room and notifies the user through the terminal.

[0333] Users share information with other users in chat rooms, and the emotion engine analyzes the emotions expressed during the conversation to provide appropriate support and advice.

[0334] In this way, the present invention, which combines an emotion engine, provides optimal information and support according to the user's psychological needs, providing an environment in which both doctors and patients can proceed with treatment with peace of mind.

[0335] The processing flow will be explained below.

[0336] Data collection module processing flow

[0337] Step 1:

[0338] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[0339] Step 2:

[0340] The terminal formats the entered information and transmits it over the Internet to a server.

[0341] Step 3:

[0342] The server receives the transmitted information.

[0343] Step 4:

[0344] The server initially verifies the information for accuracy and consistency and stores it in the appropriate database.

[0345] Embodiment using emotion engine

[0346] Step 1:

[0347] While the user is inputting information into the device, the emotion engine recognizes the user's emotions in real time, using natural language processing and image analysis technologies.

[0348] Step 2:

[0349] The recognized emotion data is sent to a server and stored in a database.

[0350] Interface optimization

[0351] Step 1:

[0352] The server selects appropriate information based on the user's emotional data. For example, if the user is feeling stressed, it will prioritize relaxing information and encouraging messages.

[0353] Step 2:

[0354] The server transmits the selected information to the terminal.

[0355] Step 3:

[0356] The terminal displays the received information to the user in an appropriate format.

[0357] Database construction module processing flow

[0358] Step 1:

[0359] The server periodically retrieves all data stored in the database.

[0360] Step 2:

[0361] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[0362] Step 3:

[0363] The server saves the optimized data back into the database.

[0364] Case search module processing flow

[0365] Step 1:

[0366] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0367] Step 2:

[0368] The terminal transmits the input information to the server.

[0369] Step 3:

[0370] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[0371] Step 4:

[0372] The server generates search results and sends them to the terminal.

[0373] Step 5:

[0374] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[0375] Chat function module processing flow

[0376] Step 1:

[0377] The user will be asked to confirm consent to use of the chat feature on their device.

[0378] Step 2:

[0379] The terminal transmits the consent information to the server.

[0380] Step 3:

[0381] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0382] Step 4:

[0383] The server creates a chat room for the matched users.

[0384] Step 5:

[0385] The terminal notifies the user of the chat room information.

[0386] Step 6:

[0387] Users participate in chat rooms and share information with other users.

[0388] Step 7:

[0389] Within the chat room, the emotion engine analyzes the user's emotions and provides appropriate support and advice, giving the user a sense of psychological security.

[0390] Example 2

[0391] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0392] Conventional medical information provision systems do not adequately collect and classify information on failed or difficult-to-treat cases, making it difficult to quickly provide users with the optimal information they need. Furthermore, information provided is not tailored to the user's emotional state, resulting in a lack of improvement in the user experience. To solve these problems, an integrated system equipped with an emotion engine is needed.

[0393] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0394] In this invention, the server includes means for inputting information about failed cases, means for receiving the input information and storing it in a database, means for optimizing the stored information using a generation AI, means for receiving the medical history and concerns from the user and searching for similar cases in the database, means for providing the search results to the user, means for connecting users in similar situations through chat, means for recognizing the user's emotional state in real time and generating emotional data, and means for optimizing information provision and interface based on the emotional state. This enables optimal information and support to be provided in accordance with the user's psychological needs, improving the user experience.

[0395] A "failed case" is one in which the treatment or surgery did not produce the expected results, and the patient's physical condition or symptoms did not improve or worsened.

[0396] The "means for inputting information" refers to an interface that allows users to intuitively and easily input information about failed cases or difficult-to-treat cases using a terminal.

[0397] "Means for receiving information and storing it in a database" refers to a system whereby the server receives the information sent from the terminal, checks it for consistency and accuracy, and then stores it in a designated database.

[0398] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs optimization and classification. In this invention, it refers to a model for performing precise analysis and processing of information.

[0399] "Optimization" refers to the process of using generative AI to analyze and classify stored information, remove incomplete or duplicate data, and transform it into more accurate and useful information.

[0400] "Means for receiving medical history and concerns" refers to a function that allows a user to input their medical history and current concerns into a terminal and send that data to a server.

[0401] The "means for searching for similar cases" refers to a system that searches for similar cases from a database based on the information received by the server and extracts information that will be useful to the user.

[0402] "Means for providing search results" refers to the method by which the server displays and provides the results to the user in the most appropriate format based on the information searched.

[0403] "A means for users in similar situations to connect through chat" refers to a function that matches consenting users, creates chat rooms, and allows them to communicate in real time.

[0404] "Means for recognizing emotional states" refers to a system that uses natural language processing and image analysis technology to grasp the emotions of a user in real time from the text, image, and audio data entered by the user.

[0405] The "means for generating emotion data" refers to a function that generates the recognized emotion of the user as data and stores it in a database.

[0406] "Means for optimizing information provision and interfaces based on emotional state" refers to a process for improving the user experience by providing optimal information and interfaces according to the user's current emotional state.

[0407] This invention is an integrated system that combines an emotion engine with a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. Specifically, it is composed of the following modules: a data collection module, an emotion engine, an interface optimization module, a database construction module, a case search module, and a chat function module.

[0408] Data Collection Module

[0409] A user uses a terminal to input information about failed or difficult-to-treat cases. The input interface should be designed to be intuitive and easy to use. The terminal formats the input information and sends it to a server via the internet. The server receives the transmitted information and stores it in an appropriate database. When storing the information, an initial evaluation and check is performed to ensure consistency and accuracy. A database management system (e.g., MySQL, PostgreSQL) is used for this process.

[0410] Emotion Engine

[0411] The server recognizes emotions in real time from the user's input and actions. This emotion recognition uses natural language processing technology (e.g., the BERT model) and image analysis technology (e.g., OpenCV, TensorFlow). The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[0412] Interface Optimization Module

[0413] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is highly stressed, it will prioritize displaying encouraging words and success stories. The device then displays this information to the user in an appropriate format that is easy for the user to view and understand. This process uses information search technology (e.g., Elasticsearch).

[0414] Database construction module

[0415] The server periodically retrieves all data stored in the database and analyzes and classifies it using a generation AI (e.g., GPT-3, BERT). The generation AI removes incomplete and duplicate data and processes it to make it more accurate and useful information, and the optimized data is then stored back in the database.

[0416] Case Search Module

[0417] The user inputs their current medical history and concerns into the device. The input information is sent to the server, which analyzes the received information and searches for similar cases in the database. This process uses machine learning algorithms (e.g., k-NN, SVM). The server generates search results and sends them to the device, which then displays them to the user.

[0418] Chat Function Module

[0419] The user agrees to use the chat function and sends the consent information from the device to the server. The server uses the consent information to search for users in the same situation in its database and matches them. The server creates a chat room for the matched user, and the device notifies the user of the chat room information. The user joins the chat room and shares information with other users, and the emotion engine analyzes the conversation content in real time to provide appropriate support and advice.

[0420] Specific examples

[0421] Example 1: When a user enters information and searches for similar cases

[0422] The user enters details about their own failed surgery into the device. The emotion engine then recognizes the user's emotions from the input. The device then sends the information to the server, which then searches the database for similar cases. Emotional data is also taken into consideration, and appropriate information is provided preferentially. Search results provide details of follow-up treatments and prognoses for past cases of similar failed surgery.

[0423] Example 2: When users share information through chat

[0424] Users agree to use the chat function, and the server matches them with other users in the same situation. The server creates a chat room and notifies the user via their device. The user joins the chat room and shares information with other users. The emotion engine analyzes the content of the conversation and provides appropriate support and advice.

[0425] This system provides optimal information and support according to the user's psychological needs, creating an environment in which both doctors and patients can proceed with treatment with peace of mind.

[0426] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0427] Step 1: Enter your information

[0428] The user uses the terminal to input detailed information about failed or difficult-to-treat cases (such as progress, treatment, case details, and how to explain the case to the family).

[0429] Input: Case data (text, images, etc.)

[0430] Specific operation: The terminal temporarily stores the entered data in memory and checks the format. If there is an error in the entered data, the user is prompted to re-enter it.

[0431] Step 2: Submit your information

[0432] The terminal transmits the input information to the server.

[0433] Input: User-entered case data

[0434] Output: Formatted case data sent to the server

[0435] Specific operation: The terminal converts the case data into an appropriate format (JSON, XML, etc.), encrypts it using SSL / TLS, and sends it to the server.

[0436] Step 3: Receiving and storing information

[0437] The server receives the information sent from the terminal and stores it in a database.

[0438] Input: Encrypted case data

[0439] Output: Case data stored in a database

[0440] What it does: The server decrypts the data it receives and stores the information using a database management system (e.g., MySQL, PostgreSQL). It checks for consistency and accuracy.

[0441] Step 4: Recognize emotions

[0442] The server recognizes emotions in real time from the user's input and actions.

[0443] Input: User input and behavioral data (text, images, audio)

[0444] Output: Emotion data

[0445] Specific operation: Using natural language processing technology (BERT model) and image analysis technology (OpenCV, TensorFlow), the system analyzes user emotions, generates emotion data, and stores it.

[0446] Step 5: Storing and using emotion data

[0447] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[0448] Input: Emotion data

[0449] Output: Emotion data stored in a database

[0450] Specific operation: The server stores the generated emotion data in a database, making it available for searches and information provision.

[0451] Step 6: Regularly collect and optimize information

[0452] The server periodically retrieves all data stored in the database and optimizes it using generative AI.

[0453] Input: Case data and emotion data stored in the database

[0454] Output: Optimized data

[0455] Specific operation: The server periodically imports data and uses generative AI (GPT-3, BERT) to analyze, classify, and optimize the information, removing incomplete and duplicate data.

[0456] Step 7: Restoring the optimized data

[0457] The optimized data is then saved back into the database.

[0458] Input: Optimized data

[0459] Output: Data resaved to the database

[0460] Specific operation: The data optimized by the generative AI is stored back in the database, making it available for future searches and information provision.

[0461] Step 8: Enter your medical history and concerns

[0462] The user inputs their current medical history and concerns into the terminal.

[0463] Input: Current medical history and concerns

[0464] Output: Entered medical history and problem data

[0465] Specific operation: The device receives this data, checks the format again, and then saves it.

[0466] Step 9: Submit and retrieve information

[0467] The terminal sends the input information to the server, which analyzes the received information and searches the database for similar cases.

[0468] Input: Medical history and problem data

[0469] Output: Search results for similar cases

[0470] Specific operation: The server uses machine learning algorithms (k-NN, SVM) to search for similar cases and generate search results.

[0471] Step 10: Serving search results

[0472] The server transmits the generated search results to the terminal, which displays the results to the user.

[0473] Input: Search results for similar cases

[0474] Output: Search results displayed to the user

[0475] Specific operation: The server sends the search results to the terminal, and the terminal displays the results in an easy-to-read format for the user.

[0476] Step 11: Gather consent and match for chat features

[0477] Users agree to use the chat function, and the server matches users with similar circumstances based on the consent information.

[0478] Input: consent information

[0479] Output: Chat partner matching information

[0480] Specific operation: The server records the consent information in a database and uses similarity calculations (e.g., Jaccard coefficient) to match users with the same concerns or symptoms.

[0481] Step 12: Create and notify chat rooms

[0482] The server creates a chat room for the matched user, and the terminal sends a notification to the user to join the chat room.

[0483] Input: Matching information

[0484] Output: Generated chat room information

[0485] Specific operation: The server creates a chat room and sends the information to the device. The user is notified and can join the chat room.

[0486] Step 13: Chat sentiment analysis and support

[0487] The server uses an emotion engine in the chat room to analyze the user's emotions in real time and provide appropriate support.

[0488] Input: Chat content

[0489] Output: Sentiment analysis results and supporting information

[0490] Specific operation: The server analyzes chat content, generates emotional data, and provides appropriate advice and support information based on the analysis results.

[0491] (Application example 2)

[0492] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0493] Conventional medical information systems lack the ability to collect and analyze information on failed or difficult-to-treat cases, and are often unable to provide optimal information tailored to the user's emotional state. Furthermore, there are issues with utilizing information in physical stores that sell health-related products, making it difficult to receive effective support.

[0494] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0495] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generation AI to optimize the stored information, a means for receiving the medical history and concerns from the user and searching for similar cases from the database, a means for providing the search results to the user, a means for connecting users with similar circumstances through chat, a means for performing emotion recognition and providing information according to the user's emotional state, and a means for use in physical stores that handle health-related products. This enables the provision of optimal information and support tailored to the user's emotional state, improving the quality of medical services in physical stores.

[0496] "Failed cases" are cases in which treatment or surgery did not produce the expected results.

[0497] "Means for inputting information" refers to an interface or device that allows a user to input information into the system.

[0498] "Means for receiving information and storing it in a database" refers to the technical means for receiving input information and storing it in a database.

[0499] "Generative AI" is an artificial intelligence technique used to analyze, optimize, and classify large amounts of data.

[0500] The "means for receiving medical history and concerns from the user" refers to an interface or device that allows the user to input their current medical history and concerns.

[0501] The "means for searching for similar cases" refers to a technical means for searching for similar cases from a database based on user input.

[0502] The "means for providing search results to the user" refers to an interface or device for displaying and providing the searched information to the user.

[0503] "A means for users in similar circumstances to connect through chat" is a technology that matches users with similar medical histories and concerns, allowing them to exchange information through chat.

[0504] "Means for emotion recognition" refers to technology for analyzing and recognizing emotions from user input and behavior.

[0505] "Means for providing information according to the user's emotional state" refers to technology that provides optimal information and advice to the user based on the results of emotion recognition.

[0506] A "brick and mortar store" is a physical store that sells health-related products.

[0507] In order to implement the present invention, it is important to link various hardware and software components. The specific configurations and operation methods of each component will be described below.

[0508] Enter and submit information

[0509] Users use devices such as smartphones or tablets to input information about failed or difficult-to-treat cases (e.g., progression of symptoms, treatment, case details, how to explain to family members, etc.). The input interface is designed to be intuitive and easy to use. The input information is sent from the device to the server.

[0510] Receiving and storing information

[0511] The server stores the received information in a database in an appropriate format, with some initial evaluation and consistency checks to ensure the information is consistent and accurate. This process is carried out using a database management system (DBMS).

[0512] emotion recognition

[0513] The server recognizes emotions in real time from the content and actions the user inputs into the device. This emotion recognition uses natural language processing and image analysis technologies. Specifically, it uses the Hugging Face transformers library to analyze emotions from the user's input text. This emotional data is used to provide subsequent information and optimize the interface.

[0514] Information optimization and classification

[0515] The server analyzes and optimizes all stored data using a generative AI model. Specifically, it combines natural language processing and topic modeling (e.g., using TfidfVectorizer and NMF) to classify and organize the input information. The optimized data is then re-stored in the database.

[0516] Search and Information

[0517] When a user enters their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in its database. The search results, including information on the case's treatment, prognosis, and explanation method, are provided to the user's device from the server.

[0518] Chat feature

[0519] When a user agrees to use the chat function, the server searches the database for other users in the same situation and matches them. The server then creates a chat room so that matched users can share information through chat. Within this chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[0520] Use in physical stores

[0521] In physical stores, patients and medical staff can collect and share case information using smartphones or tablets. For example, pharmacies and medical equipment stores can provide advice and product information based on past treatment failures or difficult cases. An emotion engine can also simultaneously provide information to reduce users' stress and anxiety.

[0522] Examples of concrete examples and prompts

[0523] A concrete example is a smartphone application for pharmacies. When a patient purchases medicine at the pharmacy, the application searches for information on past treatment failures or difficult cases and provides the most appropriate advice and product information. In addition, an emotion engine detects the patient's anxiety or stress and provides encouraging messages and self-care information.

[0524] Example prompt sentence:

[0525] "I would like to gather detailed information about a recent treatment failure for patient XYZ and recommend the best course of action to remedy this."

[0526] In this way, the present invention can provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[0527] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0528] Step 1:

[0529] Entering information

[0530] Users use the input interface on their smartphone or tablet to input information about failed or difficult-to-treat cases, such as the progression of symptoms, treatment, case details, and how to explain the case to family members. This information is then stored on the device.

[0531] Input and Output:

[0532] Input: Detailed information about failed or difficult cases

[0533] Output: Information stored on the device

[0534] Step 2:

[0535] Sending information

[0536] The device formats the information entered by the user and transmits it over the Internet to a server, ensuring the data remains consistent and accurate.

[0537] Input and Output:

[0538] Input: Information stored on your device

[0539] Output: Formatted information is sent to the server

[0540] Step 3:

[0541] Receiving and storing information

[0542] The server receives the information sent from the device and stores it in a database in an appropriate format, with an initial evaluation and consistency check of the information before storing it.

[0543] Input and Output:

[0544] Input: Formatted information

[0545] Output: Information stored in the database

[0546] Step 4:

[0547] emotion recognition

[0548] The server analyzes the input and actions of the user on the device and performs emotion recognition. This emotion recognition uses the Hugging Face transformers library for text analysis. The recognized emotion data is stored in a database.

[0549] Input and Output:

[0550] Input: User-entered text and action data

[0551] Output: Analyzed sentiment data

[0552] Step 5:

[0553] Information optimization and classification

[0554] The server analyzes the information stored in the database using a generative AI model to optimize and classify the information. Topic modeling using TfidfVectorizer and NMF is performed here. The optimized data is then stored back in the database.

[0555] Input and Output:

[0556] Input: Information stored in a database

[0557] Output: Optimized information data

[0558] Step 6:

[0559] Search and Information

[0560] When a user inputs their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in the database and selects the most appropriate information. The selected information is then provided to the user's device from the server.

[0561] Input and Output:

[0562] Input: User-entered medical history and problem information

[0563] Output: Information on similar cases is provided to the user's device.

[0564] Step 7:

[0565] Chat feature

[0566] When a user agrees to use the chat function, the server searches for other users in the same situation and matches them. The server then creates a chat room so that matched users can exchange information through chat. Within the chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[0567] Input and Output:

[0568] Input: User information that you have agreed to use

[0569] Output: Matched chat room information

[0570] Step 8:

[0571] Use in physical stores

[0572] In physical stores, patients and medical staff can use smartphones and tablets to collect and share case information. For example, advice and product information based on past treatment failures or difficult cases can be provided. An emotion engine also provides information to reduce users' stress and anxiety.

[0573] Input and Output:

[0574] Input: Case information and emotion data

[0575] Output: In-store advice and product information

[0576] This allows the system to provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[0577] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0578] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0579] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0580] [Second embodiment]

[0581] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0582] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0583] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0584] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0585] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0586] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0587] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0588] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0589] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0590] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0591] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0592] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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] This invention is a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The system aims to provide a forum for sharing information that is beneficial for both doctors and patients.

[0594] Data Collection Module Embodiments

[0595] Entering information

[0596] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface must be designed to be intuitive and easy to use.

[0597] Users can add more detailed information as needed and even upload related documents and reports.

[0598] Sending and Receiving Information

[0599] The terminal formats the information entered by the user and transmits it over the Internet to a server.

[0600] The server receives the submitted information and stores it in the appropriate database, performing some initial evaluation and checks to ensure the information is consistent and accurate.

[0601] Database Construction Module Embodiments

[0602] Data Acquisition and Optimization

[0603] The server periodically retrieves information on all failed and difficult-to-treat cases stored in the database.

[0604] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[0605] Saving optimization data

[0606] The optimized data is then stored in the database again and used when the user searches later.

[0607] Case Search Module Embodiments

[0608] Enter your medical history and concerns

[0609] Users input their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0610] Submitting and Retrieving Information

[0611] The terminal transmits the input information to the server.

[0612] The server analyzes the received information and searches the database for similar cases, taking into account the treatment, prognosis, and explanation of the case.

[0613] Providing search results

[0614] The server generates information about the searched similar cases and transmits it to the terminal.

[0615] The terminal displays the received search results to the user, who can then plan the next course of treatment based on the provided information.

[0616] Chat Function Module Embodiment

[0617] Obtaining User Consent

[0618] The user confirms on the device that they agree to use the chat function.

[0619] Sending and matching consent information

[0620] The terminal transmits the consent information to the server.

[0621] The server searches the database for users in the same situation based on the consent information and performs matching.

[0622] Creating a chat room

[0623] The server creates a chat room for the matched users.

[0624] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[0625] Information sharing and support

[0626] In the chat room, users can share information and experiences about failed cases, which gives users a sense of psychological security.

[0627] Specific examples

[0628] Example 1: When a user enters information and searches for similar cases

[0629] The user enters details about their failed surgery into the terminal.

[0630] The terminal sends the information to the server, which then searches the database for similar cases.

[0631] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[0632] Example 2: When users share information through chat

[0633] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[0634] The server generates a chat room and notifies the user through the terminal.

[0635] Users share information, experiences and advice with other users in chat rooms.

[0636] This invention is a system that contributes to solving problems in the medical field by effectively collecting and optimizing information on failed cases and providing it to users, allowing both medical professionals and patients to proceed with treatment with peace of mind.

[0637] The processing flow will be explained below.

[0638] Data collection module processing flow

[0639] Step 1:

[0640] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[0641] Step 2:

[0642] The terminal formats the entered information and sends it to the server.

[0643] Step 3:

[0644] The server performs an initial evaluation of the information received to check for accuracy and consistency.

[0645] Step 4:

[0646] The server stores the information that passes the initial evaluation in a database.

[0647] Database construction module processing flow

[0648] Step 1:

[0649] The server periodically retrieves all data stored in the database.

[0650] Step 2:

[0651] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[0652] Step 3:

[0653] The server saves the optimized data back into the database.

[0654] Case search module processing flow

[0655] Step 1:

[0656] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0657] Step 2:

[0658] The terminal transmits the input information to the server.

[0659] Step 3:

[0660] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[0661] Step 4:

[0662] The server generates search results and sends them to the terminal.

[0663] Step 5:

[0664] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[0665] Chat function module processing flow

[0666] Step 1:

[0667] The user will be asked to confirm consent to use of the chat feature on their device.

[0668] Step 2:

[0669] The terminal transmits the consent information to the server.

[0670] Step 3:

[0671] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0672] Step 4:

[0673] The server creates a chat room for the matched users.

[0674] Step 5:

[0675] The terminal notifies the user of the chat room information.

[0676] Step 6:

[0677] Users can join chat rooms and share information with other users, which gives them a sense of psychological security.

[0678] Example 1

[0679] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0680] In the current medical field, information about failed or difficult-to-treat cases is not effectively shared, making it difficult for doctors and patients to find the optimal treatment. Furthermore, there are few forums for users in the same situation to share information, making it difficult to obtain psychological support. To improve this situation, a system is needed that collects, optimizes, and shares reliable information among users.

[0681] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0682] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in an information storage device, a means for using a generative AI model to optimize the stored information, a means for receiving medical history and concerns from the user and searching for similar cases from the information storage device, a means for providing the search results to the user, and a means for connecting users in similar situations through chat. This makes it possible to collect, optimize, and provide highly reliable information. Users can also share information and receive psychological support.

[0683] A "failure case" is a medical case in which a treatment did not achieve the intended result.

[0684] "Information storage device" refers to equipment or systems for storing and managing data and information.

[0685] A "generative AI model" is an artificial intelligence model that analyzes large amounts of data and generates an output that is optimal for a specific task.

[0686] "Medical history" refers to information that records a patient's past illnesses and treatment history.

[0687] "Worries" refer to health-related problems or anxieties that the user currently has.

[0688] A "similar case" is a case in which the current case and a past case share similarities.

[0689] "Chat" is a form of communication in which users exchange messages in real time.

[0690] "Matching" is the process of connecting users with similar circumstances and needs.

[0691] A "chat room" is a virtual space where specific users can converse and exchange information.

[0692] This invention is a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using a generative AI model, and provides it to users. This system promotes information sharing in medical settings and makes it easier for users to exchange information.

[0693] Hardware and software used

[0694] server

[0695] The server uses a common cloud computing platform (e.g., a cloud service provider's infrastructure).

[0696] MySQL is used for database management.

[0697] A large-scale language model is used as the generative AI model.

[0698] Terminal

[0699] A terminal is a device used by a user, such as a computer or smartphone, that provides an input interface.

[0700] The front end uses an interactive web application (e.g., a JavaScript framework) that runs in a web browser.

[0701] It uses Node.js for the backend.

[0702] Program processing explanation

[0703] Data collection

[0704] The user uses the terminal to input information about failed or difficult cases (such as progress, treatment, details, and how to explain the procedure to the family). The terminal converts this information into JSON format and sends it to the server via an HTTP POST request. The server analyzes the received data and stores it in a MySQL database.

[0705] Data Optimization

[0706] The server periodically retrieves information on failed or difficult-to-treat cases from the database, analyzes and classifies the data using a generative AI model, and optimizes it by removing incomplete and duplicate data.

[0707] Case Search

[0708] The user inputs their current medical history and concerns into the device. The device sends this information to the server, which then uses a generative AI model to search for similar cases. The server generates search results and sends them to the device. The user then decides on the next course of treatment based on this information.

[0709] Chat feature

[0710] The user agrees to use the chat function, and the device sends the consent information to the server. The server searches the database for users with similar circumstances and matches them. A chat room is created for the matched user, and the user joins the chat room through the device.

[0711] Specific examples

[0712] Example 1: User inputs information to search for similar cases

[0713] The user enters details about a failed surgery last year into the terminal, including detailed information about the patient's infection outbreak and treatment protocol.

[0714] The device converts this data into JSON format and sends it to the server.

[0715] The server inputs this information into a generative AI model and searches a database for similar cases.

[0716] Treatment and prognosis information for similar cases, such as "cases where similar surgical failures have occurred in the past," will be provided to the terminal.

[0717] Example 2: When users share information through chat

[0718] The user agrees to use the chat function and enters consent information on the device.

[0719] The terminal sends the consent information to the server, and the server searches for users in similar situations.

[0720] The server creates a chat room for the matched users and notifies the terminal.

[0721] Users join chat rooms and share information about "experiences of failed surgery" and "how to explain to family members."

[0722] Prompt Sentence Examples

[0723] An example of a prompt that the user might enter is:

[0724] "Please provide details of any infections that occurred during the patient's surgical course. Upload any relevant documentation as needed."

[0725] This system allows reliable information to be collected and optimized in the medical field, and enables users to share information effectively with each other.

[0726] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0727] Step 1:

[0728] The user uses the input interface on the terminal to input information about failed or difficult-to-treat cases (such as progress, treatment, details, and how to explain to the family).

[0729] Input: Text information and related materials (e.g. PDF files) on failed or difficult-to-treat cases

[0730] What happens: A user fills in a form with details about a "failed surgery due to infection" and uploads a PDF file of the associated treatment protocol.

[0731] Step 2:

[0732] The device converts the input information into JSON format and sends it to the server via an HTTP POST request.

[0733] Input: User-entered text information and uploaded files

[0734] Output: Data converted to JSON format

[0735] Specific operation: The device generates a JSON object containing details of "surgery failed due to infection" and related protocols and sends it to the server.

[0736] Step 3:

[0737] The server analyzes the received data and stores it in a MySQL database.

[0738] Input: JSON format data

[0739] Output: Information stored in the database

[0740] Specific operation: The server parses the JSON data and stores the data "Surgery failed due to infection" in the database.

[0741] Step 4:

[0742] The server periodically retrieves information on failed or difficult-to-treat cases from the database and analyzes and classifies the data using a generative AI model.

[0743] Input: Information on failed cases in the database

[0744] Output: Optimized data

[0745] How it works: The server runs a scheduled task at night, extracting new data from the database and inputting it into the generative AI model to generate optimized data.

[0746] Step 5:

[0747] The server removes incomplete and duplicate data and stores the optimized data back into the database.

[0748] Input: Data analyzed and optimized by the generative AI model

[0749] Output: Optimized data stored in the database

[0750] Specific operation: The server deletes duplicate and incomplete data and stores it in the database as clean data.

[0751] Step 6:

[0752] The user inputs their current medical history and concerns into the terminal.

[0753] Input: Information about the user's medical history and concerns

[0754] Output: Data sent to the server as an HTTP request

[0755] Specific operation: The user inputs "chest pain" and "recent medical history."

[0756] Step 7:

[0757] The device sends the input information to the server, which then uses the generated AI model to search for similar cases in the database.

[0758] Input: Information about the user's medical history and concerns

[0759] Output: Search results for similar cases

[0760] Specific operation: The server inputs prompts into the generative AI model and retrieves relevant cases from the database.

[0761] Step 8:

[0762] The server generates search results and sends them to the terminal, which displays them to the user.

[0763] Input: Search result data

[0764] Output: Similar case information provided to the user

[0765] Specific operation: The server collects data on "cases of similar chest pain in the past" and sends it to the terminal, which then displays it to the user.

[0766] Step 9:

[0767] The user agrees to use the chat function, and the device sends the consent information to the server.

[0768] Input: Chat function usage consent information

[0769] Output: The consent information sent to the server

[0770] Specific operation: The user clicks the "Agree to Terms of Use for Chat Function" button. The device sends a request to the server.

[0771] Step 10:

[0772] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0773] Input: consent information

[0774] Output: Matched user information

[0775] What happens: The server searches its database for other consenting users and finds the best match.

[0776] Step 11:

[0777] The server creates a chat room for the matched users and notifies the terminal.

[0778] Input: Matched user information

[0779] Output: Chat room creation and notification

[0780] Specific operation: The server sends a "matching completion notification" to the terminal and provides the user with a link to the chat room.

[0781] Step 12:

[0782] The user receives a notification and joins the chat room.

[0783] Input: Chat room link

[0784] Output: Conversations in participating chat rooms

[0785] What happens: A user clicks on a chat room link, accesses the chat room, and shares information with other users.

[0786] (Application example 1)

[0787] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0788] Conventional medical information systems do not adequately manage or share information about failed or difficult-to-treat cases, making it difficult for both doctors and patients to select effective treatments. Furthermore, there is a lack of information about treatment costs and optimal payment methods, which can place a heavy financial burden on patients. Furthermore, there are limited opportunities for patients in the same situation to share information, and psychological support is also insufficient.

[0789] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0790] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generating AI to optimize the stored information, a means for receiving the user's medical history and concerns and searching the database for similar cases, a means for providing the user with the search results, a means for users with similar circumstances to connect via chat, and a means for users to select the optimal payment plan based on the treatment content and costs. This allows doctors and patients to effectively share information, enabling more appropriate treatment options, and patients to reduce their financial burden by selecting the optimal payment plan. Furthermore, patients with similar circumstances can share information and receive psychological support.

[0791] "Failure cases" refer to cases in which treatment did not go as expected and resulted in unexpected outcomes.

[0792] "Means for inputting information" refers to a device or interface that allows a user to input information about a failure case.

[0793] "Means for receiving information and storing it in a database" refers to a device or system that allows the server to receive input information and store it in a database.

[0794] "Generative AI instruments" refers to instruments that use artificial intelligence technology to analyze, optimize, and classify information.

[0795] "Means for receiving medical history and concerns and searching for similar cases from a database" refers to a device or system that receives a user's medical history and concerns as input and searches for similar cases from a database based on that information.

[0796] The term "means for providing search results to the user" refers to a device or system that outputs information on searched similar cases to the user.

[0797] "A means for users in similar circumstances to connect through chat" refers to a device or system that has the functionality to enable users with similar conditions to communicate through chat.

[0798] The "means for selecting a payment plan" refers to a device or system that allows a user to select the optimal payment method based on the treatment content and treatment costs.

[0799] A "database" refers to a system or device that stores information in an organized manner so that it can be retrieved or accessed later.

[0800] "Financial burden" refers to the financial costs incurred by the user in relation to the cost of treatment.

[0801] System Overview

[0802] This invention is a system that integrates medical information management and the proposal of optimal payment plans. The system inputs, stores, optimizes, searches, and proposes information about failed cases, and then provides users with optimal payment plans based on that information. The system can use a smartphone application and operates in conjunction with a cloud-based server. Its main components include a database, a generative AI model, and a user interface.

[0803] Data collection and storage

[0804] Users enter detailed information about their failed cases through a smartphone app. This information includes the course of treatment, the treatment methods used, case details, and a breakdown of treatment costs. The entered information is sent to a server via the Internet and stored in a database. The input interface is designed to be intuitive and easy to use during this process.

[0805] Data Optimization

[0806] The server periodically retrieves the information stored in the database and uses a generative AI model (e.g., GPT-3) to analyze, optimize, and classify the information. During this process, incomplete and duplicate data is removed and processed to produce accurate and useful information. The optimized data is then used for user searches and suggestions.

[0807] Case search and suggestions

[0808] When a user enters their current medical history and concerns into the app, that information is sent to the server, which then searches the database for similar cases and uses generative AI to suggest appropriate treatments, prognoses, and necessary explanations. This information is displayed intuitively to the user.

[0809] Payment plan proposal

[0810] Furthermore, when users input the details of treatment and costs, the AI ​​generator will use that information to suggest the optimal payment plan, which may include installment payments, loans, or changing insurance plans, allowing users to choose the plan that best suits their financial situation.

[0811] Chat feature

[0812] It also provides a chat function for users to share information and support each other. If a user agrees, the server searches the database for other users in the same situation, matches them, and creates a chat room. In the chat room, users can exchange experiences and advice about treatment.

[0813] Hardware and software used

[0814] The main hardware includes smartphones (iOS, Android), cloud-based servers (AWS, Google Cloud), and software using generative AI models (GPT-3) and database management systems (SQL, NoSQL).

[0815] Prompt Sentence Examples

[0816] Examples of prompts used in this system are as follows:

[0817] "If a patient undergoing diabetes treatment has an annual treatment cost of 500,000 yen, of which 70% is covered by insurance, how would generative AI optimize the payment plan?"

[0818] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0819] Step 1:

[0820] Users enter information about failed cases through a smartphone app, including the treatment progress, treatment methods used, case details, and a breakdown of treatment costs. The information is then sent to the device via an input interface.

[0821] Step 2:

[0822] The device formats the information it receives and sends it over the Internet to a server, which stores the data and performs an initial evaluation and validation check. Correct data is then stored in a database.

[0823] Step 3:

[0824] The server periodically retrieves the information stored in the database and optimizes the data using a generative AI model (e.g., GPT-3). Specifically, the generative AI removes incomplete and duplicate data and converts it into accurate and useful information. This is where the data is optimized.

[0825] Step 4:

[0826] The user enters their current medical history and concerns into a smartphone app. This information includes details of symptoms and past treatment history. The entered information is then sent back to the server via the device.

[0827] Step 5:

[0828] The server analyzes the received patient information and searches the database for similar cases. During this process, the generative AI searches for relevant data, including treatment, prognosis, and explanation methods, and extracts the optimal solution. The search results are then provided to the user in an optimized form.

[0829] Step 6:

[0830] When a user enters the details of treatment and costs into the smartphone app, the information is sent to a server. The server analyzes this information and uses generative AI to propose the optimal payment plan. Proposed plans include installment payments, loans, and changes to insurance plans.

[0831] Step 7:

[0832] The server generates payment plan proposals and provides them to the user via a smartphone app, who can then select the plan that best suits their financial situation.

[0833] Step 8:

[0834] When a user agrees to use the chat function, the device sends the consent information to the server, which then searches the database for other users with similar circumstances and matches them. A chat room is then created, allowing users to share information with other users.

[0835] Step 9:

[0836] In the chat room, users exchange experiences and advice about failed cases, which allows users to receive psychological support and deepen their knowledge about better treatments and payment methods.

[0837] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0838] This invention is an integrated system that combines an emotion engine with a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The emotion engine recognizes the user's emotional state, provides optimal information, and optimizes the interface, improving the user experience.

[0839] Data Collection Module Embodiments

[0840] Entering information

[0841] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface will be designed to be intuitive and easy to use so that users do not feel stressed.

[0842] Sending and Receiving Information

[0843] The terminal formats the entered information and transmits it over the Internet to a server.

[0844] The server receives the transmitted information and stores it in the appropriate database, where it performs some initial evaluation and checks to ensure the information is consistent and accurate.

[0845] Embodiment using emotion engine

[0846] Emotion recognition

[0847] The server recognizes emotions in real time from the content and actions entered by the user into the device, using natural language processing and image analysis technologies.

[0848] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[0849] Interface optimization

[0850] Emotion-based information provision

[0851] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is under a lot of stress, it will prioritize displaying encouraging words and success stories.

[0852] The terminal displays the information received from the server in an appropriate format for the user.

[0853] Database Construction Module Embodiments

[0854] Data Acquisition and Optimization

[0855] The server periodically retrieves all data stored in the database.

[0856] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[0857] Saving optimization data

[0858] The optimized data is then stored in the database again and used when the user searches later.

[0859] Case Search Module Embodiments

[0860] Enter your medical history and concerns

[0861] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0862] Submitting and Retrieving Information

[0863] The terminal transmits the input information to the server.

[0864] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[0865] Providing search results

[0866] The server generates search results and sends them to the terminal.

[0867] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[0868] Chat Function Module Embodiment

[0869] Obtaining User Consent

[0870] The user will be asked to confirm consent to use of the chat feature on their device.

[0871] Sending and matching consent information

[0872] The terminal transmits the consent information to the server.

[0873] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0874] Creating a chat room

[0875] The server creates a chat room for the matched users.

[0876] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[0877] Sentiment Analysis and Support

[0878] Within the chat room, an emotion engine analyzes users' emotions and provides appropriate support and advice, promoting a sense of psychological security.

[0879] Specific examples

[0880] Example 1: When a user enters information and searches for similar cases

[0881] The user inputs details about their failed surgery into the terminal, and the emotion engine recognizes the user's emotions from the input.

[0882] The device sends the information to the server, which then searches a database for similar cases, taking into account emotional data and providing appropriate information preferentially.

[0883] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[0884] Example 2: When users share information through chat

[0885] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[0886] The server generates a chat room and notifies the user through the terminal.

[0887] Users share information with other users in chat rooms, and the emotion engine analyzes the emotions expressed during the conversation to provide appropriate support and advice.

[0888] In this way, the present invention, which combines an emotion engine, provides optimal information and support according to the user's psychological needs, providing an environment in which both doctors and patients can proceed with treatment with peace of mind.

[0889] The processing flow will be explained below.

[0890] Data collection module processing flow

[0891] Step 1:

[0892] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[0893] Step 2:

[0894] The terminal formats the entered information and transmits it over the Internet to a server.

[0895] Step 3:

[0896] The server receives the transmitted information.

[0897] Step 4:

[0898] The server initially verifies the information for accuracy and consistency and stores it in the appropriate database.

[0899] Embodiment using emotion engine

[0900] Step 1:

[0901] While the user is inputting information into the device, the emotion engine recognizes the user's emotions in real time, using natural language processing and image analysis technologies.

[0902] Step 2:

[0903] The recognized emotion data is sent to a server and stored in a database.

[0904] Interface optimization

[0905] Step 1:

[0906] The server selects appropriate information based on the user's emotional data. For example, if the user is feeling stressed, it will prioritize relaxing information and encouraging messages.

[0907] Step 2:

[0908] The server transmits the selected information to the terminal.

[0909] Step 3:

[0910] The terminal displays the received information to the user in an appropriate format.

[0911] Database construction module processing flow

[0912] Step 1:

[0913] The server periodically retrieves all data stored in the database.

[0914] Step 2:

[0915] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[0916] Step 3:

[0917] The server saves the optimized data back into the database.

[0918] Case search module processing flow

[0919] Step 1:

[0920] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[0921] Step 2:

[0922] The terminal transmits the input information to the server.

[0923] Step 3:

[0924] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[0925] Step 4:

[0926] The server generates search results and sends them to the terminal.

[0927] Step 5:

[0928] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[0929] Chat function module processing flow

[0930] Step 1:

[0931] The user will be asked to confirm consent to use of the chat feature on their device.

[0932] Step 2:

[0933] The terminal transmits the consent information to the server.

[0934] Step 3:

[0935] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[0936] Step 4:

[0937] The server creates a chat room for the matched users.

[0938] Step 5:

[0939] The terminal notifies the user of the chat room information.

[0940] Step 6:

[0941] Users participate in chat rooms and share information with other users.

[0942] Step 7:

[0943] Within the chat room, the emotion engine analyzes the user's emotions and provides appropriate support and advice, giving the user a sense of psychological security.

[0944] Example 2

[0945] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0946] Conventional medical information provision systems do not adequately collect and classify information on failed or difficult-to-treat cases, making it difficult to quickly provide users with the optimal information they need. Furthermore, information provided is not tailored to the user's emotional state, resulting in a lack of improvement in the user experience. To solve these problems, an integrated system equipped with an emotion engine is needed.

[0947] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0948] In this invention, the server includes means for inputting information about failed cases, means for receiving the input information and storing it in a database, means for optimizing the stored information using a generation AI, means for receiving the medical history and concerns from the user and searching for similar cases in the database, means for providing the search results to the user, means for connecting users in similar situations through chat, means for recognizing the user's emotional state in real time and generating emotional data, and means for optimizing information provision and interface based on the emotional state. This enables optimal information and support to be provided in accordance with the user's psychological needs, improving the user experience.

[0949] A "failed case" is one in which the treatment or surgery did not produce the expected results, and the patient's physical condition or symptoms did not improve or worsened.

[0950] The "means for inputting information" refers to an interface that allows users to intuitively and easily input information about failed cases or difficult-to-treat cases using a terminal.

[0951] "Means for receiving information and storing it in a database" refers to a system whereby the server receives the information sent from the terminal, checks it for consistency and accuracy, and then stores it in a designated database.

[0952] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs optimization and classification. In this invention, it refers to a model for performing precise analysis and processing of information.

[0953] "Optimization" refers to the process of using generative AI to analyze and classify stored information, remove incomplete or duplicate data, and transform it into more accurate and useful information.

[0954] "Means for receiving medical history and concerns" refers to a function that allows a user to input their medical history and current concerns into a terminal and send that data to a server.

[0955] The "means for searching for similar cases" refers to a system that searches for similar cases from a database based on the information received by the server and extracts information that will be useful to the user.

[0956] "Means for providing search results" refers to the method by which the server displays and provides the results to the user in the most appropriate format based on the information searched.

[0957] "A means for users in similar situations to connect through chat" refers to a function that matches consenting users, creates chat rooms, and allows them to communicate in real time.

[0958] "Means for recognizing emotional states" refers to a system that uses natural language processing and image analysis technology to grasp the emotions of a user in real time from the text, image, and audio data entered by the user.

[0959] The "means for generating emotion data" refers to a function that generates the recognized emotion of the user as data and stores it in a database.

[0960] "Means for optimizing information provision and interfaces based on emotional state" refers to a process for improving the user experience by providing optimal information and interfaces according to the user's current emotional state.

[0961] This invention is an integrated system that combines an emotion engine with a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. Specifically, it is composed of the following modules: a data collection module, an emotion engine, an interface optimization module, a database construction module, a case search module, and a chat function module.

[0962] Data Collection Module

[0963] A user uses a terminal to input information about failed or difficult-to-treat cases. The input interface should be designed to be intuitive and easy to use. The terminal formats the input information and sends it to a server via the internet. The server receives the transmitted information and stores it in an appropriate database. When storing the information, an initial evaluation and check is performed to ensure consistency and accuracy. A database management system (e.g., MySQL, PostgreSQL) is used for this process.

[0964] Emotion Engine

[0965] The server recognizes emotions in real time from the user's input and actions. This emotion recognition uses natural language processing technology (e.g., the BERT model) and image analysis technology (e.g., OpenCV, TensorFlow). The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[0966] Interface Optimization Module

[0967] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is highly stressed, it will prioritize displaying encouraging words and success stories. The device then displays this information to the user in an appropriate format that is easy for the user to view and understand. This process uses information search technology (e.g., Elasticsearch).

[0968] Database construction module

[0969] The server periodically retrieves all data stored in the database and analyzes and classifies it using a generation AI (e.g., GPT-3, BERT). The generation AI removes incomplete and duplicate data and processes it to make it more accurate and useful information, and the optimized data is then stored back in the database.

[0970] Case Search Module

[0971] The user inputs their current medical history and concerns into the device. The input information is sent to the server, which analyzes the received information and searches for similar cases in the database. This process uses machine learning algorithms (e.g., k-NN, SVM). The server generates search results and sends them to the device, which then displays them to the user.

[0972] Chat Function Module

[0973] The user agrees to use the chat function and sends the consent information from the device to the server. The server uses the consent information to search for users in the same situation in its database and matches them. The server creates a chat room for the matched user, and the device notifies the user of the chat room information. The user joins the chat room and shares information with other users, and the emotion engine analyzes the conversation content in real time to provide appropriate support and advice.

[0974] Specific examples

[0975] Example 1: When a user enters information and searches for similar cases

[0976] The user enters details about their own failed surgery into the device. The emotion engine then recognizes the user's emotions from the input. The device then sends the information to the server, which then searches the database for similar cases. Emotional data is also taken into consideration, and appropriate information is provided preferentially. Search results provide details of follow-up treatments and prognoses for past cases of similar failed surgery.

[0977] Example 2: When users share information through chat

[0978] Users agree to use the chat function, and the server matches them with other users in the same situation. The server creates a chat room and notifies the user via their device. The user joins the chat room and shares information with other users. The emotion engine analyzes the content of the conversation and provides appropriate support and advice.

[0979] This system provides optimal information and support according to the user's psychological needs, creating an environment in which both doctors and patients can proceed with treatment with peace of mind.

[0980] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0981] Step 1: Enter your information

[0982] The user uses the terminal to input detailed information about failed or difficult-to-treat cases (such as progress, treatment, case details, and how to explain the case to the family).

[0983] Input: Case data (text, images, etc.)

[0984] Specific operation: The terminal temporarily stores the entered data in memory and checks the format. If there is an error in the entered data, the user is prompted to re-enter it.

[0985] Step 2: Submit your information

[0986] The terminal transmits the input information to the server.

[0987] Input: User-entered case data

[0988] Output: Formatted case data sent to the server

[0989] Specific operation: The terminal converts the case data into an appropriate format (JSON, XML, etc.), encrypts it using SSL / TLS, and sends it to the server.

[0990] Step 3: Receiving and storing information

[0991] The server receives the information sent from the terminal and stores it in a database.

[0992] Input: Encrypted case data

[0993] Output: Case data stored in a database

[0994] What it does: The server decrypts the data it receives and stores the information using a database management system (e.g., MySQL, PostgreSQL). It checks for consistency and accuracy.

[0995] Step 4: Recognize emotions

[0996] The server recognizes emotions in real time from the user's input and actions.

[0997] Input: User input and behavioral data (text, images, audio)

[0998] Output: Emotion data

[0999] Specific operation: Using natural language processing technology (BERT model) and image analysis technology (OpenCV, TensorFlow), the system analyzes user emotions, generates emotion data, and stores it.

[1000] Step 5: Storing and using emotion data

[1001] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[1002] Input: Emotion data

[1003] Output: Emotion data stored in a database

[1004] Specific operation: The server stores the generated emotion data in a database, making it available for searches and information provision.

[1005] Step 6: Regularly collect and optimize information

[1006] The server periodically retrieves all data stored in the database and optimizes it using generative AI.

[1007] Input: Case data and emotion data stored in the database

[1008] Output: Optimized data

[1009] Specific operation: The server periodically imports data and uses generative AI (GPT-3, BERT) to analyze, classify, and optimize the information, removing incomplete and duplicate data.

[1010] Step 7: Restoring the optimized data

[1011] The optimized data is then saved back into the database.

[1012] Input: Optimized data

[1013] Output: Data resaved to the database

[1014] Specific operation: The data optimized by the generative AI is stored back in the database, making it available for future searches and information provision.

[1015] Step 8: Enter your medical history and concerns

[1016] The user inputs their current medical history and concerns into the terminal.

[1017] Input: Current medical history and concerns

[1018] Output: Entered medical history and problem data

[1019] Specific operation: The device receives this data, checks the format again, and then saves it.

[1020] Step 9: Submit and retrieve information

[1021] The terminal sends the input information to the server, which analyzes the received information and searches the database for similar cases.

[1022] Input: Medical history and problem data

[1023] Output: Search results for similar cases

[1024] Specific operation: The server uses machine learning algorithms (k-NN, SVM) to search for similar cases and generate search results.

[1025] Step 10: Serving search results

[1026] The server transmits the generated search results to the terminal, which displays the results to the user.

[1027] Input: Search results for similar cases

[1028] Output: Search results displayed to the user

[1029] Specific operation: The server sends the search results to the terminal, and the terminal displays the results in an easy-to-read format for the user.

[1030] Step 11: Gather consent and match for chat features

[1031] Users agree to use the chat function, and the server matches users with similar circumstances based on the consent information.

[1032] Input: consent information

[1033] Output: Chat partner matching information

[1034] Specific operation: The server records the consent information in a database and uses similarity calculations (e.g., Jaccard coefficient) to match users with the same concerns or symptoms.

[1035] Step 12: Create and notify chat rooms

[1036] The server creates a chat room for the matched user, and the terminal sends a notification to the user to join the chat room.

[1037] Input: Matching information

[1038] Output: Generated chat room information

[1039] Specific operation: The server creates a chat room and sends the information to the device. The user is notified and can join the chat room.

[1040] Step 13: Chat sentiment analysis and support

[1041] The server uses an emotion engine in the chat room to analyze the user's emotions in real time and provide appropriate support.

[1042] Input: Chat content

[1043] Output: Sentiment analysis results and supporting information

[1044] Specific operation: The server analyzes chat content, generates emotional data, and provides appropriate advice and support information based on the analysis results.

[1045] (Application example 2)

[1046] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1047] Conventional medical information systems lack the ability to collect and analyze information on failed or difficult-to-treat cases, and are often unable to provide optimal information tailored to the user's emotional state. Furthermore, there are issues with utilizing information in physical stores that sell health-related products, making it difficult to receive effective support.

[1048] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1049] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generation AI to optimize the stored information, a means for receiving the medical history and concerns from the user and searching for similar cases from the database, a means for providing the search results to the user, a means for connecting users with similar circumstances through chat, a means for performing emotion recognition and providing information according to the user's emotional state, and a means for use in physical stores that handle health-related products. This enables the provision of optimal information and support tailored to the user's emotional state, improving the quality of medical services in physical stores.

[1050] "Failed cases" are cases in which treatment or surgery did not produce the expected results.

[1051] "Means for inputting information" refers to an interface or device that allows a user to input information into the system.

[1052] "Means for receiving information and storing it in a database" refers to the technical means for receiving input information and storing it in a database.

[1053] "Generative AI" is an artificial intelligence technique used to analyze, optimize, and classify large amounts of data.

[1054] The "means for receiving medical history and concerns from the user" refers to an interface or device that allows the user to input their current medical history and concerns.

[1055] The "means for searching for similar cases" refers to a technical means for searching for similar cases from a database based on user input.

[1056] The "means for providing search results to the user" refers to an interface or device for displaying and providing the searched information to the user.

[1057] "A means for users in similar circumstances to connect through chat" is a technology that matches users with similar medical histories and concerns, allowing them to exchange information through chat.

[1058] "Means for emotion recognition" refers to technology for analyzing and recognizing emotions from user input and behavior.

[1059] "Means for providing information according to the user's emotional state" refers to technology that provides optimal information and advice to the user based on the results of emotion recognition.

[1060] A "brick and mortar store" is a physical store that sells health-related products.

[1061] In order to implement the present invention, it is important to link various hardware and software components. The specific configurations and operation methods of each component will be described below.

[1062] Enter and submit information

[1063] Users use devices such as smartphones or tablets to input information about failed or difficult-to-treat cases (e.g., progression of symptoms, treatment, case details, how to explain to family members, etc.). The input interface is designed to be intuitive and easy to use. The input information is sent from the device to the server.

[1064] Receiving and storing information

[1065] The server stores the received information in a database in an appropriate format, with some initial evaluation and consistency checks to ensure the information is consistent and accurate. This process is carried out using a database management system (DBMS).

[1066] emotion recognition

[1067] The server recognizes emotions in real time from the content and actions the user inputs into the device. This emotion recognition uses natural language processing and image analysis technologies. Specifically, it uses the Hugging Face transformers library to analyze emotions from the user's input text. This emotional data is used to provide subsequent information and optimize the interface.

[1068] Information optimization and classification

[1069] The server analyzes and optimizes all stored data using a generative AI model. Specifically, it combines natural language processing and topic modeling (e.g., using TfidfVectorizer and NMF) to classify and organize the input information. The optimized data is then re-stored in the database.

[1070] Search and Information

[1071] When a user enters their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in its database. The search results, including information on the case's treatment, prognosis, and explanation method, are provided to the user's device from the server.

[1072] Chat feature

[1073] When a user agrees to use the chat function, the server searches the database for other users in the same situation and matches them. The server then creates a chat room so that matched users can share information through chat. Within this chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[1074] Use in physical stores

[1075] In physical stores, patients and medical staff can collect and share case information using smartphones or tablets. For example, pharmacies and medical equipment stores can provide advice and product information based on past treatment failures or difficult cases. An emotion engine can also simultaneously provide information to reduce users' stress and anxiety.

[1076] Examples of concrete examples and prompts

[1077] A concrete example is a smartphone application for pharmacies. When a patient purchases medicine at the pharmacy, the application searches for information on past treatment failures or difficult cases and provides the most appropriate advice and product information. In addition, an emotion engine detects the patient's anxiety or stress and provides encouraging messages and self-care information.

[1078] Example prompt sentence:

[1079] "I would like to gather detailed information about a recent treatment failure for patient XYZ and recommend the best course of action to remedy this."

[1080] In this way, the present invention can provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[1081] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1082] Step 1:

[1083] Entering information

[1084] Users use the input interface on their smartphone or tablet to input information about failed or difficult-to-treat cases, such as the progression of symptoms, treatment, case details, and how to explain the case to family members. This information is then stored on the device.

[1085] Input and Output:

[1086] Input: Detailed information about failed or difficult cases

[1087] Output: Information stored on the device

[1088] Step 2:

[1089] Sending information

[1090] The device formats the information entered by the user and transmits it over the Internet to a server, ensuring the data remains consistent and accurate.

[1091] Input and Output:

[1092] Input: Information stored on your device

[1093] Output: Formatted information is sent to the server

[1094] Step 3:

[1095] Receiving and storing information

[1096] The server receives the information sent from the device and stores it in a database in an appropriate format, with an initial evaluation and consistency check of the information before storing it.

[1097] Input and Output:

[1098] Input: Formatted information

[1099] Output: Information stored in the database

[1100] Step 4:

[1101] emotion recognition

[1102] The server analyzes the input and actions of the user on the device and performs emotion recognition. This emotion recognition uses the Hugging Face transformers library for text analysis. The recognized emotion data is stored in a database.

[1103] Input and Output:

[1104] Input: User-entered text and action data

[1105] Output: Analyzed sentiment data

[1106] Step 5:

[1107] Information optimization and classification

[1108] The server analyzes the information stored in the database using a generative AI model to optimize and classify the information. Topic modeling using TfidfVectorizer and NMF is performed here. The optimized data is then stored back in the database.

[1109] Input and Output:

[1110] Input: Information stored in a database

[1111] Output: Optimized information data

[1112] Step 6:

[1113] Search and Information

[1114] When a user inputs their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in the database and selects the most appropriate information. The selected information is then provided to the user's device from the server.

[1115] Input and Output:

[1116] Input: User-entered medical history and problem information

[1117] Output: Information on similar cases is provided to the user's device.

[1118] Step 7:

[1119] Chat feature

[1120] When a user agrees to use the chat function, the server searches for other users in the same situation and matches them. The server then creates a chat room so that matched users can exchange information through chat. Within the chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[1121] Input and Output:

[1122] Input: User information that you have agreed to use

[1123] Output: Matched chat room information

[1124] Step 8:

[1125] Use in physical stores

[1126] In physical stores, patients and medical staff can use smartphones and tablets to collect and share case information. For example, advice and product information based on past treatment failures or difficult cases can be provided. An emotion engine also provides information to reduce users' stress and anxiety.

[1127] Input and Output:

[1128] Input: Case information and emotion data

[1129] Output: In-store advice and product information

[1130] This allows the system to provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[1131] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1132] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1133] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1134] [Third embodiment]

[1135] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1136] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1137] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1138] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1139] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1141] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1142] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1143] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1144] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1145] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1146] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1147] This invention is a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The system aims to provide a forum for sharing information that is beneficial for both doctors and patients.

[1148] Data Collection Module Embodiments

[1149] Entering information

[1150] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface must be designed to be intuitive and easy to use.

[1151] Users can add more detailed information as needed and even upload related documents and reports.

[1152] Sending and Receiving Information

[1153] The terminal formats the information entered by the user and transmits it over the Internet to a server.

[1154] The server receives the submitted information and stores it in the appropriate database, performing some initial evaluation and checks to ensure the information is consistent and accurate.

[1155] Database Construction Module Embodiments

[1156] Data Acquisition and Optimization

[1157] The server periodically retrieves information on all failed and difficult-to-treat cases stored in the database.

[1158] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[1159] Saving optimization data

[1160] The optimized data is then stored in the database again and used when the user searches later.

[1161] Case Search Module Embodiments

[1162] Enter your medical history and concerns

[1163] Users input their current medical history and concerns into the device, including details of symptoms and past treatment history.

[1164] Submitting and Retrieving Information

[1165] The terminal transmits the input information to the server.

[1166] The server analyzes the received information and searches the database for similar cases, taking into account the treatment, prognosis, and explanation of the case.

[1167] Providing search results

[1168] The server generates information about the searched similar cases and transmits it to the terminal.

[1169] The terminal displays the received search results to the user, who can then plan the next course of treatment based on the provided information.

[1170] Chat Function Module Embodiment

[1171] Obtaining User Consent

[1172] The user confirms on the device that they agree to use the chat function.

[1173] Sending and matching consent information

[1174] The terminal transmits the consent information to the server.

[1175] The server searches the database for users in the same situation based on the consent information and performs matching.

[1176] Creating a chat room

[1177] The server creates a chat room for the matched users.

[1178] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[1179] Information sharing and support

[1180] In the chat room, users can share information and experiences about failed cases, which gives users a sense of psychological security.

[1181] Specific examples

[1182] Example 1: When a user enters information and searches for similar cases

[1183] The user enters details about their failed surgery into the terminal.

[1184] The terminal sends the information to the server, which then searches the database for similar cases.

[1185] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[1186] Example 2: When users share information through chat

[1187] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[1188] The server generates a chat room and notifies the user through the terminal.

[1189] Users share information, experiences and advice with other users in chat rooms.

[1190] This invention is a system that contributes to solving problems in the medical field by effectively collecting and optimizing information on failed cases and providing it to users, allowing both medical professionals and patients to proceed with treatment with peace of mind.

[1191] The processing flow will be explained below.

[1192] Data collection module processing flow

[1193] Step 1:

[1194] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[1195] Step 2:

[1196] The terminal formats the entered information and sends it to the server.

[1197] Step 3:

[1198] The server performs an initial evaluation of the information received to check for accuracy and consistency.

[1199] Step 4:

[1200] The server stores the information that passes the initial evaluation in a database.

[1201] Database construction module processing flow

[1202] Step 1:

[1203] The server periodically retrieves all data stored in the database.

[1204] Step 2:

[1205] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[1206] Step 3:

[1207] The server saves the optimized data back into the database.

[1208] Case search module processing flow

[1209] Step 1:

[1210] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[1211] Step 2:

[1212] The terminal transmits the input information to the server.

[1213] Step 3:

[1214] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[1215] Step 4:

[1216] The server generates search results and sends them to the terminal.

[1217] Step 5:

[1218] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[1219] Chat function module processing flow

[1220] Step 1:

[1221] The user will be asked to confirm consent to use of the chat feature on their device.

[1222] Step 2:

[1223] The terminal transmits the consent information to the server.

[1224] Step 3:

[1225] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[1226] Step 4:

[1227] The server creates a chat room for the matched users.

[1228] Step 5:

[1229] The terminal notifies the user of the chat room information.

[1230] Step 6:

[1231] Users can join chat rooms and share information with other users, which gives them a sense of psychological security.

[1232] Example 1

[1233] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1234] In the current medical field, information about failed or difficult-to-treat cases is not effectively shared, making it difficult for doctors and patients to find the optimal treatment. Furthermore, there are few forums for users in the same situation to share information, making it difficult to obtain psychological support. To improve this situation, a system is needed that collects, optimizes, and shares reliable information among users.

[1235] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1236] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in an information storage device, a means for using a generative AI model to optimize the stored information, a means for receiving medical history and concerns from the user and searching for similar cases from the information storage device, a means for providing the search results to the user, and a means for connecting users in similar situations through chat. This makes it possible to collect, optimize, and provide highly reliable information. Users can also share information and receive psychological support.

[1237] A "failure case" is a medical case in which a treatment did not achieve the intended result.

[1238] "Information storage device" refers to equipment or systems for storing and managing data and information.

[1239] A "generative AI model" is an artificial intelligence model that analyzes large amounts of data and generates an output that is optimal for a specific task.

[1240] "Medical history" refers to information that records a patient's past illnesses and treatment history.

[1241] "Worries" refer to health-related problems or anxieties that the user currently has.

[1242] A "similar case" is a case in which the current case and a past case share similarities.

[1243] "Chat" is a form of communication in which users exchange messages in real time.

[1244] "Matching" is the process of connecting users with similar circumstances and needs.

[1245] A "chat room" is a virtual space where specific users can converse and exchange information.

[1246] This invention is a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using a generative AI model, and provides it to users. This system promotes information sharing in medical settings and makes it easier for users to exchange information.

[1247] Hardware and software used

[1248] server

[1249] The server uses a common cloud computing platform (e.g., a cloud service provider's infrastructure).

[1250] MySQL is used for database management.

[1251] A large-scale language model is used as the generative AI model.

[1252] Terminal

[1253] A terminal is a device used by a user, such as a computer or smartphone, that provides an input interface.

[1254] The front end uses an interactive web application (e.g., a JavaScript framework) that runs in a web browser.

[1255] It uses Node.js for the backend.

[1256] Program processing explanation

[1257] Data collection

[1258] The user uses the terminal to input information about failed or difficult cases (such as progress, treatment, details, and how to explain the procedure to the family). The terminal converts this information into JSON format and sends it to the server via an HTTP POST request. The server analyzes the received data and stores it in a MySQL database.

[1259] Data Optimization

[1260] The server periodically retrieves information on failed or difficult-to-treat cases from the database, analyzes and classifies the data using a generative AI model, and optimizes it by removing incomplete and duplicate data.

[1261] Case Search

[1262] The user inputs their current medical history and concerns into the device. The device sends this information to the server, which then uses a generative AI model to search for similar cases. The server generates search results and sends them to the device. The user then decides on the next course of treatment based on this information.

[1263] Chat feature

[1264] The user agrees to use the chat function, and the device sends the consent information to the server. The server searches the database for users with similar circumstances and matches them. A chat room is created for the matched user, and the user joins the chat room through the device.

[1265] Specific examples

[1266] Example 1: User inputs information to search for similar cases

[1267] The user enters details about a failed surgery last year into the terminal, including detailed information about the patient's infection outbreak and treatment protocol.

[1268] The device converts this data into JSON format and sends it to the server.

[1269] The server inputs this information into a generative AI model and searches a database for similar cases.

[1270] Treatment and prognosis information for similar cases, such as "cases where similar surgical failures have occurred in the past," will be provided to the terminal.

[1271] Example 2: When users share information through chat

[1272] The user agrees to use the chat function and enters consent information on the device.

[1273] The terminal sends the consent information to the server, and the server searches for users in similar situations.

[1274] The server creates a chat room for the matched users and notifies the terminal.

[1275] Users join chat rooms and share information about "experiences of failed surgery" and "how to explain to family members."

[1276] Prompt Sentence Examples

[1277] An example of a prompt that the user might enter is:

[1278] "Please provide details of any infections that occurred during the patient's surgical course. Upload any relevant documentation as needed."

[1279] This system allows reliable information to be collected and optimized in the medical field, and enables users to share information effectively with each other.

[1280] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1281] Step 1:

[1282] The user uses the input interface on the terminal to input information about failed or difficult-to-treat cases (such as progress, treatment, details, and how to explain to the family).

[1283] Input: Text information and related materials (e.g. PDF files) on failed or difficult-to-treat cases

[1284] What happens: A user fills in a form with details about a "failed surgery due to infection" and uploads a PDF file of the associated treatment protocol.

[1285] Step 2:

[1286] The device converts the input information into JSON format and sends it to the server via an HTTP POST request.

[1287] Input: User-entered text information and uploaded files

[1288] Output: Data converted to JSON format

[1289] Specific operation: The device generates a JSON object containing details of "surgery failed due to infection" and related protocols and sends it to the server.

[1290] Step 3:

[1291] The server analyzes the received data and stores it in a MySQL database.

[1292] Input: JSON format data

[1293] Output: Information stored in the database

[1294] Specific operation: The server parses the JSON data and stores the data "Surgery failed due to infection" in the database.

[1295] Step 4:

[1296] The server periodically retrieves information on failed or difficult-to-treat cases from the database and analyzes and classifies the data using a generative AI model.

[1297] Input: Information on failed cases in the database

[1298] Output: Optimized data

[1299] How it works: The server runs a scheduled task at night, extracting new data from the database and inputting it into the generative AI model to generate optimized data.

[1300] Step 5:

[1301] The server removes incomplete and duplicate data and stores the optimized data back into the database.

[1302] Input: Data analyzed and optimized by the generative AI model

[1303] Output: Optimized data stored in the database

[1304] Specific operation: The server deletes duplicate and incomplete data and stores it in the database as clean data.

[1305] Step 6:

[1306] The user inputs their current medical history and concerns into the terminal.

[1307] Input: Information about the user's medical history and concerns

[1308] Output: Data sent to the server as an HTTP request

[1309] Specific operation: The user inputs "chest pain" and "recent medical history."

[1310] Step 7:

[1311] The device sends the input information to the server, which then uses the generated AI model to search for similar cases in the database.

[1312] Input: Information about the user's medical history and concerns

[1313] Output: Search results for similar cases

[1314] Specific operation: The server inputs prompts into the generative AI model and retrieves relevant cases from the database.

[1315] Step 8:

[1316] The server generates search results and sends them to the terminal, which displays them to the user.

[1317] Input: Search result data

[1318] Output: Similar case information provided to the user

[1319] Specific operation: The server collects data on "cases of similar chest pain in the past" and sends it to the terminal, which then displays it to the user.

[1320] Step 9:

[1321] The user agrees to use the chat function, and the device sends the consent information to the server.

[1322] Input: Chat function usage consent information

[1323] Output: The consent information sent to the server

[1324] Specific operation: The user clicks the "Agree to Terms of Use for Chat Function" button. The device sends a request to the server.

[1325] Step 10:

[1326] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[1327] Input: consent information

[1328] Output: Matched user information

[1329] What happens: The server searches its database for other consenting users and finds the best match.

[1330] Step 11:

[1331] The server creates a chat room for the matched users and notifies the terminal.

[1332] Input: Matched user information

[1333] Output: Chat room creation and notification

[1334] Specific operation: The server sends a "matching completion notification" to the terminal and provides the user with a link to the chat room.

[1335] Step 12:

[1336] The user receives a notification and joins the chat room.

[1337] Input: Chat room link

[1338] Output: Conversations in participating chat rooms

[1339] What happens: A user clicks on a chat room link, accesses the chat room, and shares information with other users.

[1340] (Application example 1)

[1341] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1342] Conventional medical information systems do not adequately manage or share information about failed or difficult-to-treat cases, making it difficult for both doctors and patients to select effective treatments. Furthermore, there is a lack of information about treatment costs and optimal payment methods, which can place a heavy financial burden on patients. Furthermore, there are limited opportunities for patients in the same situation to share information, and psychological support is also insufficient.

[1343] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1344] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generating AI to optimize the stored information, a means for receiving the user's medical history and concerns and searching the database for similar cases, a means for providing the user with the search results, a means for users with similar circumstances to connect via chat, and a means for users to select the optimal payment plan based on the treatment content and costs. This allows doctors and patients to effectively share information, enabling more appropriate treatment options, and patients to reduce their financial burden by selecting the optimal payment plan. Furthermore, patients with similar circumstances can share information and receive psychological support.

[1345] "Failure cases" refer to cases in which treatment did not go as expected and resulted in unexpected outcomes.

[1346] "Means for inputting information" refers to a device or interface that allows a user to input information about a failure case.

[1347] "Means for receiving information and storing it in a database" refers to a device or system that allows the server to receive input information and store it in a database.

[1348] "Generative AI instruments" refers to instruments that use artificial intelligence technology to analyze, optimize, and classify information.

[1349] "Means for receiving medical history and concerns and searching for similar cases from a database" refers to a device or system that receives a user's medical history and concerns as input and searches for similar cases from a database based on that information.

[1350] The term "means for providing search results to the user" refers to a device or system that outputs information on searched similar cases to the user.

[1351] "A means for users in similar circumstances to connect through chat" refers to a device or system that has the functionality to enable users with similar conditions to communicate through chat.

[1352] The "means for selecting a payment plan" refers to a device or system that allows a user to select the optimal payment method based on the treatment content and treatment costs.

[1353] A "database" refers to a system or device that stores information in an organized manner so that it can be retrieved or accessed later.

[1354] "Financial burden" refers to the financial costs incurred by the user in relation to the cost of treatment.

[1355] System Overview

[1356] This invention is a system that integrates medical information management and the proposal of optimal payment plans. The system inputs, stores, optimizes, searches, and proposes information about failed cases, and then provides users with optimal payment plans based on that information. The system can use a smartphone application and operates in conjunction with a cloud-based server. Its main components include a database, a generative AI model, and a user interface.

[1357] Data collection and storage

[1358] Users enter detailed information about their failed cases through a smartphone app. This information includes the course of treatment, the treatment methods used, case details, and a breakdown of treatment costs. The entered information is sent to a server via the Internet and stored in a database. The input interface is designed to be intuitive and easy to use during this process.

[1359] Data Optimization

[1360] The server periodically retrieves the information stored in the database and uses a generative AI model (e.g., GPT-3) to analyze, optimize, and classify the information. During this process, incomplete and duplicate data is removed and processed to produce accurate and useful information. The optimized data is then used for user searches and suggestions.

[1361] Case search and suggestions

[1362] When a user enters their current medical history and concerns into the app, that information is sent to the server, which then searches the database for similar cases and uses generative AI to suggest appropriate treatments, prognoses, and necessary explanations. This information is displayed intuitively to the user.

[1363] Payment plan proposal

[1364] Furthermore, when users input the details of treatment and costs, the AI ​​generator will use that information to suggest the optimal payment plan, which may include installment payments, loans, or changing insurance plans, allowing users to choose the plan that best suits their financial situation.

[1365] Chat feature

[1366] It also provides a chat function for users to share information and support each other. If a user agrees, the server searches the database for other users in the same situation, matches them, and creates a chat room. In the chat room, users can exchange experiences and advice about treatment.

[1367] Hardware and software used

[1368] The main hardware includes smartphones (iOS, Android), cloud-based servers (AWS, Google Cloud), and software using generative AI models (GPT-3) and database management systems (SQL, NoSQL).

[1369] Prompt Sentence Examples

[1370] Examples of prompts used in this system are as follows:

[1371] "If a patient undergoing diabetes treatment has an annual treatment cost of 500,000 yen, of which 70% is covered by insurance, how would generative AI optimize the payment plan?"

[1372] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1373] Step 1:

[1374] Users enter information about failed cases through a smartphone app, including the treatment progress, treatment methods used, case details, and a breakdown of treatment costs. The information is then sent to the device via an input interface.

[1375] Step 2:

[1376] The device formats the information it receives and sends it over the Internet to a server, which stores the data and performs an initial evaluation and validation check. Correct data is then stored in a database.

[1377] Step 3:

[1378] The server periodically retrieves the information stored in the database and optimizes the data using a generative AI model (e.g., GPT-3). Specifically, the generative AI removes incomplete and duplicate data and converts it into accurate and useful information. This is where the data is optimized.

[1379] Step 4:

[1380] The user enters their current medical history and concerns into a smartphone app. This information includes details of symptoms and past treatment history. The entered information is then sent back to the server via the device.

[1381] Step 5:

[1382] The server analyzes the received patient information and searches the database for similar cases. During this process, the generative AI searches for relevant data, including treatment, prognosis, and explanation methods, and extracts the optimal solution. The search results are then provided to the user in an optimized form.

[1383] Step 6:

[1384] When a user enters the details of treatment and costs into the smartphone app, the information is sent to a server. The server analyzes this information and uses generative AI to propose the optimal payment plan. Proposed plans include installment payments, loans, and changes to insurance plans.

[1385] Step 7:

[1386] The server generates payment plan proposals and provides them to the user via a smartphone app, who can then select the plan that best suits their financial situation.

[1387] Step 8:

[1388] When a user agrees to use the chat function, the device sends the consent information to the server, which then searches the database for other users with similar circumstances and matches them. A chat room is then created, allowing users to share information with other users.

[1389] Step 9:

[1390] In the chat room, users exchange experiences and advice about failed cases, which allows users to receive psychological support and deepen their knowledge about better treatments and payment methods.

[1391] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1392] This invention is an integrated system that combines an emotion engine with a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The emotion engine recognizes the user's emotional state, provides optimal information, and optimizes the interface, improving the user experience.

[1393] Data Collection Module Embodiments

[1394] Entering information

[1395] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface will be designed to be intuitive and easy to use so that users do not feel stressed.

[1396] Sending and Receiving Information

[1397] The terminal formats the entered information and transmits it over the Internet to a server.

[1398] The server receives the transmitted information and stores it in the appropriate database, where it performs some initial evaluation and checks to ensure the information is consistent and accurate.

[1399] Embodiment using emotion engine

[1400] Emotion recognition

[1401] The server recognizes emotions in real time from the content and actions entered by the user into the device, using natural language processing and image analysis technologies.

[1402] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[1403] Interface optimization

[1404] Emotion-based information provision

[1405] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is under a lot of stress, it will prioritize displaying encouraging words and success stories.

[1406] The terminal displays the information received from the server in an appropriate format for the user.

[1407] Database Construction Module Embodiments

[1408] Data Acquisition and Optimization

[1409] The server periodically retrieves all data stored in the database.

[1410] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[1411] Saving optimization data

[1412] The optimized data is then stored in the database again and used when the user searches later.

[1413] Case Search Module Embodiments

[1414] Enter your medical history and concerns

[1415] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[1416] Submitting and Retrieving Information

[1417] The terminal transmits the input information to the server.

[1418] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[1419] Providing search results

[1420] The server generates search results and sends them to the terminal.

[1421] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[1422] Chat Function Module Embodiment

[1423] Obtaining User Consent

[1424] The user will be asked to confirm consent to use of the chat feature on their device.

[1425] Sending and matching consent information

[1426] The terminal transmits the consent information to the server.

[1427] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[1428] Creating a chat room

[1429] The server creates a chat room for the matched users.

[1430] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[1431] Sentiment Analysis and Support

[1432] Within the chat room, an emotion engine analyzes users' emotions and provides appropriate support and advice, promoting a sense of psychological security.

[1433] Specific examples

[1434] Example 1: When a user enters information and searches for similar cases

[1435] The user inputs details about their failed surgery into the terminal, and the emotion engine recognizes the user's emotions from the input.

[1436] The device sends the information to the server, which then searches a database for similar cases, taking into account emotional data and providing appropriate information preferentially.

[1437] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[1438] Example 2: When users share information through chat

[1439] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[1440] The server generates a chat room and notifies the user through the terminal.

[1441] Users share information with other users in chat rooms, and the emotion engine analyzes the emotions expressed during the conversation to provide appropriate support and advice.

[1442] In this way, the present invention, which combines an emotion engine, provides optimal information and support according to the user's psychological needs, providing an environment in which both doctors and patients can proceed with treatment with peace of mind.

[1443] The processing flow will be explained below.

[1444] Data collection module processing flow

[1445] Step 1:

[1446] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[1447] Step 2:

[1448] The terminal formats the entered information and transmits it over the Internet to a server.

[1449] Step 3:

[1450] The server receives the transmitted information.

[1451] Step 4:

[1452] The server initially verifies the information for accuracy and consistency and stores it in the appropriate database.

[1453] Embodiment using emotion engine

[1454] Step 1:

[1455] While the user is inputting information into the device, the emotion engine recognizes the user's emotions in real time, using natural language processing and image analysis technologies.

[1456] Step 2:

[1457] The recognized emotion data is sent to a server and stored in a database.

[1458] Interface optimization

[1459] Step 1:

[1460] The server selects appropriate information based on the user's emotional data. For example, if the user is feeling stressed, it will prioritize relaxing information and encouraging messages.

[1461] Step 2:

[1462] The server transmits the selected information to the terminal.

[1463] Step 3:

[1464] The terminal displays the received information to the user in an appropriate format.

[1465] Database construction module processing flow

[1466] Step 1:

[1467] The server periodically retrieves all data stored in the database.

[1468] Step 2:

[1469] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[1470] Step 3:

[1471] The server saves the optimized data back into the database.

[1472] Case search module processing flow

[1473] Step 1:

[1474] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[1475] Step 2:

[1476] The terminal transmits the input information to the server.

[1477] Step 3:

[1478] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[1479] Step 4:

[1480] The server generates search results and sends them to the terminal.

[1481] Step 5:

[1482] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[1483] Chat function module processing flow

[1484] Step 1:

[1485] The user will be asked to confirm consent to use of the chat feature on their device.

[1486] Step 2:

[1487] The terminal transmits the consent information to the server.

[1488] Step 3:

[1489] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[1490] Step 4:

[1491] The server creates a chat room for the matched users.

[1492] Step 5:

[1493] The terminal notifies the user of the chat room information.

[1494] Step 6:

[1495] Users participate in chat rooms and share information with other users.

[1496] Step 7:

[1497] Within the chat room, the emotion engine analyzes the user's emotions and provides appropriate support and advice, giving the user a sense of psychological security.

[1498] Example 2

[1499] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1500] Conventional medical information provision systems do not adequately collect and classify information on failed or difficult-to-treat cases, making it difficult to quickly provide users with the optimal information they need. Furthermore, information provided is not tailored to the user's emotional state, resulting in a lack of improvement in the user experience. To solve these problems, an integrated system equipped with an emotion engine is needed.

[1501] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1502] In this invention, the server includes means for inputting information about failed cases, means for receiving the input information and storing it in a database, means for optimizing the stored information using a generation AI, means for receiving the medical history and concerns from the user and searching for similar cases in the database, means for providing the search results to the user, means for connecting users in similar situations through chat, means for recognizing the user's emotional state in real time and generating emotional data, and means for optimizing information provision and interface based on the emotional state. This enables optimal information and support to be provided in accordance with the user's psychological needs, improving the user experience.

[1503] A "failed case" is one in which the treatment or surgery did not produce the expected results, and the patient's physical condition or symptoms did not improve or worsened.

[1504] The "means for inputting information" refers to an interface that allows users to intuitively and easily input information about failed cases or difficult-to-treat cases using a terminal.

[1505] "Means for receiving information and storing it in a database" refers to a system whereby the server receives the information sent from the terminal, checks it for consistency and accuracy, and then stores it in a designated database.

[1506] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs optimization and classification. In this invention, it refers to a model for performing precise analysis and processing of information.

[1507] "Optimization" refers to the process of using generative AI to analyze and classify stored information, remove incomplete or duplicate data, and transform it into more accurate and useful information.

[1508] "Means for receiving medical history and concerns" refers to a function that allows a user to input their medical history and current concerns into a terminal and send that data to a server.

[1509] The "means for searching for similar cases" refers to a system that searches for similar cases from a database based on the information received by the server and extracts information that will be useful to the user.

[1510] "Means for providing search results" refers to the method by which the server displays and provides the results to the user in the most appropriate format based on the information searched.

[1511] "A means for users in similar situations to connect through chat" refers to a function that matches consenting users, creates chat rooms, and allows them to communicate in real time.

[1512] "Means for recognizing emotional states" refers to a system that uses natural language processing and image analysis technology to grasp the emotions of a user in real time from the text, image, and audio data entered by the user.

[1513] The "means for generating emotion data" refers to a function that generates the recognized emotion of the user as data and stores it in a database.

[1514] "Means for optimizing information provision and interfaces based on emotional state" refers to a process for improving the user experience by providing optimal information and interfaces according to the user's current emotional state.

[1515] This invention is an integrated system that combines an emotion engine with a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. Specifically, it is composed of the following modules: a data collection module, an emotion engine, an interface optimization module, a database construction module, a case search module, and a chat function module.

[1516] Data Collection Module

[1517] A user uses a terminal to input information about failed or difficult-to-treat cases. The input interface should be designed to be intuitive and easy to use. The terminal formats the input information and sends it to a server via the internet. The server receives the transmitted information and stores it in an appropriate database. When storing the information, an initial evaluation and check is performed to ensure consistency and accuracy. A database management system (e.g., MySQL, PostgreSQL) is used for this process.

[1518] Emotion Engine

[1519] The server recognizes emotions in real time from the user's input and actions. This emotion recognition uses natural language processing technology (e.g., the BERT model) and image analysis technology (e.g., OpenCV, TensorFlow). The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[1520] Interface Optimization Module

[1521] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is highly stressed, it will prioritize displaying encouraging words and success stories. The device then displays this information to the user in an appropriate format that is easy for the user to view and understand. This process uses information search technology (e.g., Elasticsearch).

[1522] Database construction module

[1523] The server periodically retrieves all data stored in the database and analyzes and classifies it using a generation AI (e.g., GPT-3, BERT). The generation AI removes incomplete and duplicate data and processes it to make it more accurate and useful information, and the optimized data is then stored back in the database.

[1524] Case Search Module

[1525] The user inputs their current medical history and concerns into the device. The input information is sent to the server, which analyzes the received information and searches for similar cases in the database. This process uses machine learning algorithms (e.g., k-NN, SVM). The server generates search results and sends them to the device, which then displays them to the user.

[1526] Chat Function Module

[1527] The user agrees to use the chat function and sends the consent information from the device to the server. The server uses the consent information to search for users in the same situation in its database and matches them. The server creates a chat room for the matched user, and the device notifies the user of the chat room information. The user joins the chat room and shares information with other users, and the emotion engine analyzes the conversation content in real time to provide appropriate support and advice.

[1528] Specific examples

[1529] Example 1: When a user enters information and searches for similar cases

[1530] The user enters details about their own failed surgery into the device. The emotion engine then recognizes the user's emotions from the input. The device then sends the information to the server, which then searches the database for similar cases. Emotional data is also taken into consideration, and appropriate information is provided preferentially. Search results provide details of follow-up treatments and prognoses for past cases of similar failed surgery.

[1531] Example 2: When users share information through chat

[1532] Users agree to use the chat function, and the server matches them with other users in the same situation. The server creates a chat room and notifies the user via their device. The user joins the chat room and shares information with other users. The emotion engine analyzes the content of the conversation and provides appropriate support and advice.

[1533] This system provides optimal information and support according to the user's psychological needs, creating an environment in which both doctors and patients can proceed with treatment with peace of mind.

[1534] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1535] Step 1: Enter your information

[1536] The user uses the terminal to input detailed information about failed or difficult-to-treat cases (such as progress, treatment, case details, and how to explain the case to the family).

[1537] Input: Case data (text, images, etc.)

[1538] Specific operation: The terminal temporarily stores the entered data in memory and checks the format. If there is an error in the entered data, the user is prompted to re-enter it.

[1539] Step 2: Submit your information

[1540] The terminal transmits the input information to the server.

[1541] Input: User-entered case data

[1542] Output: Formatted case data sent to the server

[1543] Specific operation: The terminal converts the case data into an appropriate format (JSON, XML, etc.), encrypts it using SSL / TLS, and sends it to the server.

[1544] Step 3: Receiving and storing information

[1545] The server receives the information sent from the terminal and stores it in a database.

[1546] Input: Encrypted case data

[1547] Output: Case data stored in a database

[1548] What it does: The server decrypts the data it receives and stores the information using a database management system (e.g., MySQL, PostgreSQL). It checks for consistency and accuracy.

[1549] Step 4: Recognize emotions

[1550] The server recognizes emotions in real time from the user's input and actions.

[1551] Input: User input and behavioral data (text, images, audio)

[1552] Output: Emotion data

[1553] Specific operation: Using natural language processing technology (BERT model) and image analysis technology (OpenCV, TensorFlow), the system analyzes user emotions, generates emotion data, and stores it.

[1554] Step 5: Storing and using emotion data

[1555] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[1556] Input: Emotion data

[1557] Output: Emotion data stored in a database

[1558] Specific operation: The server stores the generated emotion data in a database, making it available for searches and information provision.

[1559] Step 6: Regularly collect and optimize information

[1560] The server periodically retrieves all data stored in the database and optimizes it using generative AI.

[1561] Input: Case data and emotion data stored in the database

[1562] Output: Optimized data

[1563] Specific operation: The server periodically imports data and uses generative AI (GPT-3, BERT) to analyze, classify, and optimize the information, removing incomplete and duplicate data.

[1564] Step 7: Restoring the optimized data

[1565] The optimized data is then saved back into the database.

[1566] Input: Optimized data

[1567] Output: Data resaved to the database

[1568] Specific operation: The data optimized by the generative AI is stored back in the database, making it available for future searches and information provision.

[1569] Step 8: Enter your medical history and concerns

[1570] The user inputs their current medical history and concerns into the terminal.

[1571] Input: Current medical history and concerns

[1572] Output: Entered medical history and problem data

[1573] Specific operation: The device receives this data, checks the format again, and then saves it.

[1574] Step 9: Submit and retrieve information

[1575] The terminal sends the input information to the server, which analyzes the received information and searches the database for similar cases.

[1576] Input: Medical history and problem data

[1577] Output: Search results for similar cases

[1578] Specific operation: The server uses machine learning algorithms (k-NN, SVM) to search for similar cases and generate search results.

[1579] Step 10: Serving search results

[1580] The server transmits the generated search results to the terminal, which displays the results to the user.

[1581] Input: Search results for similar cases

[1582] Output: Search results displayed to the user

[1583] Specific operation: The server sends the search results to the terminal, and the terminal displays the results in an easy-to-read format for the user.

[1584] Step 11: Gather consent and match for chat features

[1585] Users agree to use the chat function, and the server matches users with similar circumstances based on the consent information.

[1586] Input: consent information

[1587] Output: Chat partner matching information

[1588] Specific operation: The server records the consent information in a database and uses similarity calculations (e.g., Jaccard coefficient) to match users with the same concerns or symptoms.

[1589] Step 12: Create and notify chat rooms

[1590] The server creates a chat room for the matched user, and the terminal sends a notification to the user to join the chat room.

[1591] Input: Matching information

[1592] Output: Generated chat room information

[1593] Specific operation: The server creates a chat room and sends the information to the device. The user is notified and can join the chat room.

[1594] Step 13: Chat sentiment analysis and support

[1595] The server uses an emotion engine in the chat room to analyze the user's emotions in real time and provide appropriate support.

[1596] Input: Chat content

[1597] Output: Sentiment analysis results and supporting information

[1598] Specific operation: The server analyzes chat content, generates emotional data, and provides appropriate advice and support information based on the analysis results.

[1599] (Application example 2)

[1600] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1601] Conventional medical information systems lack the ability to collect and analyze information on failed or difficult-to-treat cases, and are often unable to provide optimal information tailored to the user's emotional state. Furthermore, there are issues with utilizing information in physical stores that sell health-related products, making it difficult to receive effective support.

[1602] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1603] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generation AI to optimize the stored information, a means for receiving the medical history and concerns from the user and searching for similar cases from the database, a means for providing the search results to the user, a means for connecting users with similar circumstances through chat, a means for performing emotion recognition and providing information according to the user's emotional state, and a means for use in physical stores that handle health-related products. This enables the provision of optimal information and support tailored to the user's emotional state, improving the quality of medical services in physical stores.

[1604] "Failed cases" are cases in which treatment or surgery did not produce the expected results.

[1605] "Means for inputting information" refers to an interface or device that allows a user to input information into the system.

[1606] "Means for receiving information and storing it in a database" refers to the technical means for receiving input information and storing it in a database.

[1607] "Generative AI" is an artificial intelligence technique used to analyze, optimize, and classify large amounts of data.

[1608] The "means for receiving medical history and concerns from the user" refers to an interface or device that allows the user to input their current medical history and concerns.

[1609] The "means for searching for similar cases" refers to a technical means for searching for similar cases from a database based on user input.

[1610] The "means for providing search results to the user" refers to an interface or device for displaying and providing the searched information to the user.

[1611] "A means for users in similar circumstances to connect through chat" is a technology that matches users with similar medical histories and concerns, allowing them to exchange information through chat.

[1612] "Means for emotion recognition" refers to technology for analyzing and recognizing emotions from user input and behavior.

[1613] "Means for providing information according to the user's emotional state" refers to technology that provides optimal information and advice to the user based on the results of emotion recognition.

[1614] A "brick and mortar store" is a physical store that sells health-related products.

[1615] In order to implement the present invention, it is important to link various hardware and software components. The specific configurations and operation methods of each component will be described below.

[1616] Enter and submit information

[1617] Users use devices such as smartphones or tablets to input information about failed or difficult-to-treat cases (e.g., progression of symptoms, treatment, case details, how to explain to family members, etc.). The input interface is designed to be intuitive and easy to use. The input information is sent from the device to the server.

[1618] Receiving and storing information

[1619] The server stores the received information in a database in an appropriate format, with some initial evaluation and consistency checks to ensure the information is consistent and accurate. This process is carried out using a database management system (DBMS).

[1620] emotion recognition

[1621] The server recognizes emotions in real time from the content and actions the user inputs into the device. This emotion recognition uses natural language processing and image analysis technologies. Specifically, it uses the Hugging Face transformers library to analyze emotions from the user's input text. This emotional data is used to provide subsequent information and optimize the interface.

[1622] Information optimization and classification

[1623] The server analyzes and optimizes all stored data using a generative AI model. Specifically, it combines natural language processing and topic modeling (e.g., using TfidfVectorizer and NMF) to classify and organize the input information. The optimized data is then re-stored in the database.

[1624] Search and Information

[1625] When a user enters their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in its database. The search results, including information on the case's treatment, prognosis, and explanation method, are provided to the user's device from the server.

[1626] Chat feature

[1627] When a user agrees to use the chat function, the server searches the database for other users in the same situation and matches them. The server then creates a chat room so that matched users can share information through chat. Within this chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[1628] Use in physical stores

[1629] In physical stores, patients and medical staff can collect and share case information using smartphones or tablets. For example, pharmacies and medical equipment stores can provide advice and product information based on past treatment failures or difficult cases. An emotion engine can also simultaneously provide information to reduce users' stress and anxiety.

[1630] Examples of concrete examples and prompts

[1631] A concrete example is a smartphone application for pharmacies. When a patient purchases medicine at the pharmacy, the application searches for information on past treatment failures or difficult cases and provides the most appropriate advice and product information. In addition, an emotion engine detects the patient's anxiety or stress and provides encouraging messages and self-care information.

[1632] Example prompt sentence:

[1633] "I would like to gather detailed information about a recent treatment failure for patient XYZ and recommend the best course of action to remedy this."

[1634] In this way, the present invention can provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[1635] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1636] Step 1:

[1637] Entering information

[1638] Users use the input interface on their smartphone or tablet to input information about failed or difficult-to-treat cases, such as the progression of symptoms, treatment, case details, and how to explain the case to family members. This information is then stored on the device.

[1639] Input and Output:

[1640] Input: Detailed information about failed or difficult cases

[1641] Output: Information stored on the device

[1642] Step 2:

[1643] Sending information

[1644] The device formats the information entered by the user and transmits it over the Internet to a server, ensuring the data remains consistent and accurate.

[1645] Input and Output:

[1646] Input: Information stored on your device

[1647] Output: Formatted information is sent to the server

[1648] Step 3:

[1649] Receiving and storing information

[1650] The server receives the information sent from the device and stores it in a database in an appropriate format, with an initial evaluation and consistency check of the information before storing it.

[1651] Input and Output:

[1652] Input: Formatted information

[1653] Output: Information stored in the database

[1654] Step 4:

[1655] emotion recognition

[1656] The server analyzes the input and actions of the user on the device and performs emotion recognition. This emotion recognition uses the Hugging Face transformers library for text analysis. The recognized emotion data is stored in a database.

[1657] Input and Output:

[1658] Input: User-entered text and action data

[1659] Output: Analyzed sentiment data

[1660] Step 5:

[1661] Information optimization and classification

[1662] The server analyzes the information stored in the database using a generative AI model to optimize and classify the information. Topic modeling using TfidfVectorizer and NMF is performed here. The optimized data is then stored back in the database.

[1663] Input and Output:

[1664] Input: Information stored in a database

[1665] Output: Optimized information data

[1666] Step 6:

[1667] Search and Information

[1668] When a user inputs their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in the database and selects the most appropriate information. The selected information is then provided to the user's device from the server.

[1669] Input and Output:

[1670] Input: User-entered medical history and problem information

[1671] Output: Information on similar cases is provided to the user's device.

[1672] Step 7:

[1673] Chat feature

[1674] When a user agrees to use the chat function, the server searches for other users in the same situation and matches them. The server then creates a chat room so that matched users can exchange information through chat. Within the chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[1675] Input and Output:

[1676] Input: User information that you have agreed to use

[1677] Output: Matched chat room information

[1678] Step 8:

[1679] Use in physical stores

[1680] In physical stores, patients and medical staff can use smartphones and tablets to collect and share case information. For example, advice and product information based on past treatment failures or difficult cases can be provided. An emotion engine also provides information to reduce users' stress and anxiety.

[1681] Input and Output:

[1682] Input: Case information and emotion data

[1683] Output: In-store advice and product information

[1684] This allows the system to provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[1685] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1686] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1687] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1688] [Fourth embodiment]

[1689] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1690] 7, a 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.

[1691] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1692] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1693] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1694] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1695] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1696] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1697] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1698] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1699] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1700] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1701] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1702] This invention is a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The system aims to provide a forum for sharing information that is beneficial for both doctors and patients.

[1703] Data Collection Module Embodiments

[1704] Entering information

[1705] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface must be designed to be intuitive and easy to use.

[1706] Users can add more detailed information as needed and even upload related documents and reports.

[1707] Sending and Receiving Information

[1708] The terminal formats the information entered by the user and transmits it over the Internet to a server.

[1709] The server receives the submitted information and stores it in the appropriate database, performing some initial evaluation and checks to ensure the information is consistent and accurate.

[1710] Database Construction Module Embodiments

[1711] Data Acquisition and Optimization

[1712] The server periodically retrieves information on all failed and difficult-to-treat cases stored in the database.

[1713] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[1714] Saving optimization data

[1715] The optimized data is then stored in the database again and used when the user searches later.

[1716] Case Search Module Embodiments

[1717] Enter your medical history and concerns

[1718] Users input their current medical history and concerns into the device, including details of symptoms and past treatment history.

[1719] Submitting and Retrieving Information

[1720] The terminal transmits the input information to the server.

[1721] The server analyzes the received information and searches the database for similar cases, taking into account the treatment, prognosis, and explanation of the case.

[1722] Providing search results

[1723] The server generates information about the searched similar cases and transmits it to the terminal.

[1724] The terminal displays the received search results to the user, who can then plan the next course of treatment based on the provided information.

[1725] Chat Function Module Embodiment

[1726] Obtaining User Consent

[1727] The user confirms on the device that they agree to use the chat function.

[1728] Sending and matching consent information

[1729] The terminal transmits the consent information to the server.

[1730] The server searches the database for users in the same situation based on the consent information and performs matching.

[1731] Creating a chat room

[1732] The server creates a chat room for the matched users.

[1733] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[1734] Information sharing and support

[1735] In the chat room, users can share information and experiences about failed cases, which gives users a sense of psychological security.

[1736] Specific examples

[1737] Example 1: When a user enters information and searches for similar cases

[1738] The user enters details about their failed surgery into the terminal.

[1739] The terminal sends the information to the server, which then searches the database for similar cases.

[1740] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[1741] Example 2: When users share information through chat

[1742] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[1743] The server generates a chat room and notifies the user through the terminal.

[1744] Users share information, experiences and advice with other users in chat rooms.

[1745] This invention is a system that contributes to solving problems in the medical field by effectively collecting and optimizing information on failed cases and providing it to users, allowing both medical professionals and patients to proceed with treatment with peace of mind.

[1746] The processing flow will be explained below.

[1747] Data collection module processing flow

[1748] Step 1:

[1749] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[1750] Step 2:

[1751] The terminal formats the entered information and sends it to the server.

[1752] Step 3:

[1753] The server performs an initial evaluation of the information received to check for accuracy and consistency.

[1754] Step 4:

[1755] The server stores the information that passes the initial evaluation in a database.

[1756] Database construction module processing flow

[1757] Step 1:

[1758] The server periodically retrieves all data stored in the database.

[1759] Step 2:

[1760] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[1761] Step 3:

[1762] The server saves the optimized data back into the database.

[1763] Case search module processing flow

[1764] Step 1:

[1765] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[1766] Step 2:

[1767] The terminal transmits the input information to the server.

[1768] Step 3:

[1769] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[1770] Step 4:

[1771] The server generates search results and sends them to the terminal.

[1772] Step 5:

[1773] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[1774] Chat function module processing flow

[1775] Step 1:

[1776] The user will be asked to confirm consent to use of the chat feature on their device.

[1777] Step 2:

[1778] The terminal transmits the consent information to the server.

[1779] Step 3:

[1780] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[1781] Step 4:

[1782] The server creates a chat room for the matched users.

[1783] Step 5:

[1784] The terminal notifies the user of the chat room information.

[1785] Step 6:

[1786] Users can join chat rooms and share information with other users, which gives them a sense of psychological security.

[1787] Example 1

[1788] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1789] In the current medical field, information about failed or difficult-to-treat cases is not effectively shared, making it difficult for doctors and patients to find the optimal treatment. Furthermore, there are few forums for users in the same situation to share information, making it difficult to obtain psychological support. To improve this situation, a system is needed that collects, optimizes, and shares reliable information among users.

[1790] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1791] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in an information storage device, a means for using a generative AI model to optimize the stored information, a means for receiving medical history and concerns from the user and searching for similar cases from the information storage device, a means for providing the search results to the user, and a means for connecting users in similar situations through chat. This makes it possible to collect, optimize, and provide highly reliable information. Users can also share information and receive psychological support.

[1792] A "failure case" is a medical case in which a treatment did not achieve the intended result.

[1793] "Information storage device" refers to equipment or systems for storing and managing data and information.

[1794] A "generative AI model" is an artificial intelligence model that analyzes large amounts of data and generates an output that is optimal for a specific task.

[1795] "Medical history" refers to information that records a patient's past illnesses and treatment history.

[1796] "Worries" refer to health-related problems or anxieties that the user currently has.

[1797] A "similar case" is a case in which the current case and a past case share similarities.

[1798] "Chat" is a form of communication in which users exchange messages in real time.

[1799] "Matching" is the process of connecting users with similar circumstances and needs.

[1800] A "chat room" is a virtual space where specific users can converse and exchange information.

[1801] This invention is a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using a generative AI model, and provides it to users. This system promotes information sharing in medical settings and makes it easier for users to exchange information.

[1802] Hardware and software used

[1803] server

[1804] The server uses a common cloud computing platform (e.g., a cloud service provider's infrastructure).

[1805] MySQL is used for database management.

[1806] A large-scale language model is used as the generative AI model.

[1807] Terminal

[1808] A terminal is a device used by a user, such as a computer or smartphone, that provides an input interface.

[1809] The front end uses an interactive web application (e.g., a JavaScript framework) that runs in a web browser.

[1810] It uses Node.js for the backend.

[1811] Program processing explanation

[1812] Data collection

[1813] The user uses the terminal to input information about failed or difficult cases (such as progress, treatment, details, and how to explain the procedure to the family). The terminal converts this information into JSON format and sends it to the server via an HTTP POST request. The server analyzes the received data and stores it in a MySQL database.

[1814] Data Optimization

[1815] The server periodically retrieves information on failed or difficult-to-treat cases from the database, analyzes and classifies the data using a generative AI model, and optimizes it by removing incomplete and duplicate data.

[1816] Case Search

[1817] The user inputs their current medical history and concerns into the device. The device sends this information to the server, which then uses a generative AI model to search for similar cases. The server generates search results and sends them to the device. The user then decides on the next course of treatment based on this information.

[1818] Chat feature

[1819] The user agrees to use the chat function, and the device sends the consent information to the server. The server searches the database for users with similar circumstances and matches them. A chat room is created for the matched user, and the user joins the chat room through the device.

[1820] Specific examples

[1821] Example 1: User inputs information to search for similar cases

[1822] The user enters details about a failed surgery last year into the terminal, including detailed information about the patient's infection outbreak and treatment protocol.

[1823] The device converts this data into JSON format and sends it to the server.

[1824] The server inputs this information into a generative AI model and searches a database for similar cases.

[1825] Treatment and prognosis information for similar cases, such as "cases where similar surgical failures have occurred in the past," will be provided to the terminal.

[1826] Example 2: When users share information through chat

[1827] The user agrees to use the chat function and enters consent information on the device.

[1828] The terminal sends the consent information to the server, and the server searches for users in similar situations.

[1829] The server creates a chat room for the matched users and notifies the terminal.

[1830] Users join chat rooms and share information about "experiences of failed surgery" and "how to explain to family members."

[1831] Prompt Sentence Examples

[1832] An example of a prompt that the user might enter is:

[1833] "Please provide details of any infections that occurred during the patient's surgical course. Upload any relevant documentation as needed."

[1834] This system allows reliable information to be collected and optimized in the medical field, and enables users to share information effectively with each other.

[1835] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1836] Step 1:

[1837] The user uses the input interface on the terminal to input information about failed or difficult-to-treat cases (such as progress, treatment, details, and how to explain to the family).

[1838] Input: Text information and related materials (e.g. PDF files) on failed or difficult-to-treat cases

[1839] What happens: A user fills in a form with details about a "failed surgery due to infection" and uploads a PDF file of the associated treatment protocol.

[1840] Step 2:

[1841] The device converts the input information into JSON format and sends it to the server via an HTTP POST request.

[1842] Input: User-entered text information and uploaded files

[1843] Output: Data converted to JSON format

[1844] Specific operation: The device generates a JSON object containing details of "surgery failed due to infection" and related protocols and sends it to the server.

[1845] Step 3:

[1846] The server analyzes the received data and stores it in a MySQL database.

[1847] Input: JSON format data

[1848] Output: Information stored in the database

[1849] Specific operation: The server parses the JSON data and stores the data "Surgery failed due to infection" in the database.

[1850] Step 4:

[1851] The server periodically retrieves information on failed or difficult-to-treat cases from the database and analyzes and classifies the data using a generative AI model.

[1852] Input: Information on failed cases in the database

[1853] Output: Optimized data

[1854] How it works: The server runs a scheduled task at night, extracting new data from the database and inputting it into the generative AI model to generate optimized data.

[1855] Step 5:

[1856] The server removes incomplete and duplicate data and stores the optimized data back into the database.

[1857] Input: Data analyzed and optimized by the generative AI model

[1858] Output: Optimized data stored in the database

[1859] Specific operation: The server deletes duplicate and incomplete data and stores it in the database as clean data.

[1860] Step 6:

[1861] The user inputs their current medical history and concerns into the terminal.

[1862] Input: Information about the user's medical history and concerns

[1863] Output: Data sent to the server as an HTTP request

[1864] Specific operation: The user inputs "chest pain" and "recent medical history."

[1865] Step 7:

[1866] The device sends the input information to the server, which then uses the generated AI model to search for similar cases in the database.

[1867] Input: Information about the user's medical history and concerns

[1868] Output: Search results for similar cases

[1869] Specific operation: The server inputs prompts into the generative AI model and retrieves relevant cases from the database.

[1870] Step 8:

[1871] The server generates search results and sends them to the terminal, which displays them to the user.

[1872] Input: Search result data

[1873] Output: Similar case information provided to the user

[1874] Specific operation: The server collects data on "cases of similar chest pain in the past" and sends it to the terminal, which then displays it to the user.

[1875] Step 9:

[1876] The user agrees to use the chat function, and the device sends the consent information to the server.

[1877] Input: Chat function usage consent information

[1878] Output: The consent information sent to the server

[1879] Specific operation: The user clicks the "Agree to Terms of Use for Chat Function" button. The device sends a request to the server.

[1880] Step 10:

[1881] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[1882] Input: consent information

[1883] Output: Matched user information

[1884] What happens: The server searches its database for other consenting users and finds the best match.

[1885] Step 11:

[1886] The server creates a chat room for the matched users and notifies the terminal.

[1887] Input: Matched user information

[1888] Output: Chat room creation and notification

[1889] Specific operation: The server sends a "matching completion notification" to the terminal and provides the user with a link to the chat room.

[1890] Step 12:

[1891] The user receives a notification and joins the chat room.

[1892] Input: Chat room link

[1893] Output: Conversations in participating chat rooms

[1894] What happens: A user clicks on a chat room link, accesses the chat room, and shares information with other users.

[1895] (Application example 1)

[1896] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1897] Conventional medical information systems do not adequately manage or share information about failed or difficult-to-treat cases, making it difficult for both doctors and patients to select effective treatments. Furthermore, there is a lack of information about treatment costs and optimal payment methods, which can place a heavy financial burden on patients. Furthermore, there are limited opportunities for patients in the same situation to share information, and psychological support is also insufficient.

[1898] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1899] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generating AI to optimize the stored information, a means for receiving the user's medical history and concerns and searching the database for similar cases, a means for providing the user with the search results, a means for users with similar circumstances to connect via chat, and a means for users to select the optimal payment plan based on the treatment content and costs. This allows doctors and patients to effectively share information, enabling more appropriate treatment options, and patients to reduce their financial burden by selecting the optimal payment plan. Furthermore, patients with similar circumstances can share information and receive psychological support.

[1900] "Failure cases" refer to cases in which treatment did not go as expected and resulted in unexpected outcomes.

[1901] "Means for inputting information" refers to a device or interface that allows a user to input information about a failure case.

[1902] "Means for receiving information and storing it in a database" refers to a device or system that allows the server to receive input information and store it in a database.

[1903] "Generative AI instruments" refers to instruments that use artificial intelligence technology to analyze, optimize, and classify information.

[1904] "Means for receiving medical history and concerns and searching for similar cases from a database" refers to a device or system that receives a user's medical history and concerns as input and searches for similar cases from a database based on that information.

[1905] The term "means for providing search results to the user" refers to a device or system that outputs information on searched similar cases to the user.

[1906] "A means for users in similar circumstances to connect through chat" refers to a device or system that has the functionality to enable users with similar conditions to communicate through chat.

[1907] The "means for selecting a payment plan" refers to a device or system that allows a user to select the optimal payment method based on the treatment content and treatment costs.

[1908] A "database" refers to a system or device that stores information in an organized manner so that it can be retrieved or accessed later.

[1909] "Financial burden" refers to the financial costs incurred by the user in relation to the cost of treatment.

[1910] System Overview

[1911] This invention is a system that integrates medical information management and the proposal of optimal payment plans. The system inputs, stores, optimizes, searches, and proposes information about failed cases, and then provides users with optimal payment plans based on that information. The system can use a smartphone application and operates in conjunction with a cloud-based server. Its main components include a database, a generative AI model, and a user interface.

[1912] Data collection and storage

[1913] Users enter detailed information about their failed cases through a smartphone app. This information includes the course of treatment, the treatment methods used, case details, and a breakdown of treatment costs. The entered information is sent to a server via the Internet and stored in a database. The input interface is designed to be intuitive and easy to use during this process.

[1914] Data Optimization

[1915] The server periodically retrieves the information stored in the database and uses a generative AI model (e.g., GPT-3) to analyze, optimize, and classify the information. During this process, incomplete and duplicate data is removed and processed to produce accurate and useful information. The optimized data is then used for user searches and suggestions.

[1916] Case search and suggestions

[1917] When a user enters their current medical history and concerns into the app, that information is sent to the server, which then searches the database for similar cases and uses generative AI to suggest appropriate treatments, prognoses, and necessary explanations. This information is displayed intuitively to the user.

[1918] Payment plan proposal

[1919] Furthermore, when users input the details of treatment and costs, the AI ​​generator will use that information to suggest the optimal payment plan, which may include installment payments, loans, or changing insurance plans, allowing users to choose the plan that best suits their financial situation.

[1920] Chat feature

[1921] It also provides a chat function for users to share information and support each other. If a user agrees, the server searches the database for other users in the same situation, matches them, and creates a chat room. In the chat room, users can exchange experiences and advice about treatment.

[1922] Hardware and software used

[1923] The main hardware includes smartphones (iOS, Android), cloud-based servers (AWS, Google Cloud), and software using generative AI models (GPT-3) and database management systems (SQL, NoSQL).

[1924] Prompt Sentence Examples

[1925] Examples of prompts used in this system are as follows:

[1926] "If a patient undergoing diabetes treatment has an annual treatment cost of 500,000 yen, of which 70% is covered by insurance, how would generative AI optimize the payment plan?"

[1927] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1928] Step 1:

[1929] Users enter information about failed cases through a smartphone app, including the treatment progress, treatment methods used, case details, and a breakdown of treatment costs. The information is then sent to the device via an input interface.

[1930] Step 2:

[1931] The device formats the information it receives and sends it over the Internet to a server, which stores the data and performs an initial evaluation and validation check. Correct data is then stored in a database.

[1932] Step 3:

[1933] The server periodically retrieves the information stored in the database and optimizes the data using a generative AI model (e.g., GPT-3). Specifically, the generative AI removes incomplete and duplicate data and converts it into accurate and useful information. This is where the data is optimized.

[1934] Step 4:

[1935] The user enters their current medical history and concerns into a smartphone app. This information includes details of symptoms and past treatment history. The entered information is then sent back to the server via the device.

[1936] Step 5:

[1937] The server analyzes the received patient information and searches the database for similar cases. During this process, the generative AI searches for relevant data, including treatment, prognosis, and explanation methods, and extracts the optimal solution. The search results are then provided to the user in an optimized form.

[1938] Step 6:

[1939] When a user enters the details of treatment and costs into the smartphone app, the information is sent to a server. The server analyzes this information and uses generative AI to propose the optimal payment plan. Proposed plans include installment payments, loans, and changes to insurance plans.

[1940] Step 7:

[1941] The server generates payment plan proposals and provides them to the user via a smartphone app, who can then select the plan that best suits their financial situation.

[1942] Step 8:

[1943] When a user agrees to use the chat function, the device sends the consent information to the server, which then searches the database for other users with similar circumstances and matches them. A chat room is then created, allowing users to share information with other users.

[1944] Step 9:

[1945] In the chat room, users exchange experiences and advice about failed cases, which allows users to receive psychological support and deepen their knowledge about better treatments and payment methods.

[1946] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1947] This invention is an integrated system that combines an emotion engine with a system that collects information on failed and difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. The emotion engine recognizes the user's emotional state, provides optimal information, and optimizes the interface, improving the user experience.

[1948] Data Collection Module Embodiments

[1949] Entering information

[1950] Users input information about failed or difficult-to-treat cases (progress, treatment, case details, how to explain to family members, etc.) into the terminal. This input interface will be designed to be intuitive and easy to use so that users do not feel stressed.

[1951] Sending and Receiving Information

[1952] The terminal formats the entered information and transmits it over the Internet to a server.

[1953] The server receives the transmitted information and stores it in the appropriate database, where it performs some initial evaluation and checks to ensure the information is consistent and accurate.

[1954] Embodiment using emotion engine

[1955] Emotion recognition

[1956] The server recognizes emotions in real time from the content and actions entered by the user into the device, using natural language processing and image analysis technologies.

[1957] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[1958] Interface optimization

[1959] Emotion-based information provision

[1960] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is under a lot of stress, it will prioritize displaying encouraging words and success stories.

[1961] The terminal displays the information received from the server in an appropriate format for the user.

[1962] Database Construction Module Embodiments

[1963] Data Acquisition and Optimization

[1964] The server periodically retrieves all data stored in the database.

[1965] The acquired information is analyzed, classified, and optimized by the Generative AI, which removes incomplete and duplicate data and processes it to make the information more accurate and useful.

[1966] Saving optimization data

[1967] The optimized data is then stored in the database again and used when the user searches later.

[1968] Case Search Module Embodiments

[1969] Enter your medical history and concerns

[1970] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[1971] Submitting and Retrieving Information

[1972] The terminal transmits the input information to the server.

[1973] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[1974] Providing search results

[1975] The server generates search results and sends them to the terminal.

[1976] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[1977] Chat Function Module Embodiment

[1978] Obtaining User Consent

[1979] The user will be asked to confirm consent to use of the chat feature on their device.

[1980] Sending and matching consent information

[1981] The terminal transmits the consent information to the server.

[1982] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[1983] Creating a chat room

[1984] The server creates a chat room for the matched users.

[1985] The terminal notifies the user of information about the chat room, allowing the user to participate in the chat room.

[1986] Sentiment Analysis and Support

[1987] Within the chat room, an emotion engine analyzes users' emotions and provides appropriate support and advice, promoting a sense of psychological security.

[1988] Specific examples

[1989] Example 1: When a user enters information and searches for similar cases

[1990] The user inputs details about their failed surgery into the terminal, and the emotion engine recognizes the user's emotions from the input.

[1991] The device sends the information to the server, which then searches a database for similar cases, taking into account emotional data and providing appropriate information preferentially.

[1992] The search results provide details of subsequent treatments and prognoses for previous cases of similar surgical failure.

[1993] Example 2: When users share information through chat

[1994] Users agree to use the chat feature, and the server matches them with other users in the same situation.

[1995] The server generates a chat room and notifies the user through the terminal.

[1996] Users share information with other users in chat rooms, and the emotion engine analyzes the emotions expressed during the conversation to provide appropriate support and advice.

[1997] In this way, the present invention, which combines an emotion engine, provides optimal information and support according to the user's psychological needs, providing an environment in which both doctors and patients can proceed with treatment with peace of mind.

[1998] The processing flow will be explained below.

[1999] Data collection module processing flow

[2000] Step 1:

[2001] The user inputs information about the failed case into the terminal, including the progress, treatment, case details, and how to explain the case to the family.

[2002] Step 2:

[2003] The terminal formats the entered information and transmits it over the Internet to a server.

[2004] Step 3:

[2005] The server receives the transmitted information.

[2006] Step 4:

[2007] The server initially verifies the information for accuracy and consistency and stores it in the appropriate database.

[2008] Embodiment using emotion engine

[2009] Step 1:

[2010] While the user is inputting information into the device, the emotion engine recognizes the user's emotions in real time, using natural language processing and image analysis technologies.

[2011] Step 2:

[2012] The recognized emotion data is sent to a server and stored in a database.

[2013] Interface optimization

[2014] Step 1:

[2015] The server selects appropriate information based on the user's emotional data. For example, if the user is feeling stressed, it will prioritize relaxing information and encouraging messages.

[2016] Step 2:

[2017] The server transmits the selected information to the terminal.

[2018] Step 3:

[2019] The terminal displays the received information to the user in an appropriate format.

[2020] Database construction module processing flow

[2021] Step 1:

[2022] The server periodically retrieves all data stored in the database.

[2023] Step 2:

[2024] The server passes the acquired information to the generation AI, which then performs data optimization processing, removing incomplete and duplicate data.

[2025] Step 3:

[2026] The server saves the optimized data back into the database.

[2027] Case search module processing flow

[2028] Step 1:

[2029] The user inputs their current medical history and concerns into the device, including details of symptoms and past treatment history.

[2030] Step 2:

[2031] The terminal transmits the input information to the server.

[2032] Step 3:

[2033] The server analyzes the received information and searches the database for similar cases, taking into account the case's treatment, prognosis, explanation, etc.

[2034] Step 4:

[2035] The server generates search results and sends them to the terminal.

[2036] Step 5:

[2037] The terminal displays the search results to the user, who then decides on the next course of treatment based on the information provided.

[2038] Chat function module processing flow

[2039] Step 1:

[2040] The user will be asked to confirm consent to use of the chat feature on their device.

[2041] Step 2:

[2042] The terminal transmits the consent information to the server.

[2043] Step 3:

[2044] The server searches the database for users with similar circumstances based on the consent information and performs matching.

[2045] Step 4:

[2046] The server creates a chat room for the matched users.

[2047] Step 5:

[2048] The terminal notifies the user of the chat room information.

[2049] Step 6:

[2050] Users participate in chat rooms and share information with other users.

[2051] Step 7:

[2052] Within the chat room, the emotion engine analyzes the user's emotions and provides appropriate support and advice, giving the user a sense of psychological security.

[2053] Example 2

[2054] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2055] Conventional medical information provision systems do not adequately collect and classify information on failed or difficult-to-treat cases, making it difficult to quickly provide users with the optimal information they need. Furthermore, information provided is not tailored to the user's emotional state, resulting in a lack of improvement in the user experience. To solve these problems, an integrated system equipped with an emotion engine is needed.

[2056] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2057] In this invention, the server includes means for inputting information about failed cases, means for receiving the input information and storing it in a database, means for optimizing the stored information using a generation AI, means for receiving the medical history and concerns from the user and searching for similar cases in the database, means for providing the search results to the user, means for connecting users in similar situations through chat, means for recognizing the user's emotional state in real time and generating emotional data, and means for optimizing information provision and interface based on the emotional state. This enables optimal information and support to be provided in accordance with the user's psychological needs, improving the user experience.

[2058] A "failed case" is one in which the treatment or surgery did not produce the expected results, and the patient's physical condition or symptoms did not improve or worsened.

[2059] The "means for inputting information" refers to an interface that allows users to intuitively and easily input information about failed cases or difficult-to-treat cases using a terminal.

[2060] "Means for receiving information and storing it in a database" refers to a system whereby the server receives the information sent from the terminal, checks it for consistency and accuracy, and then stores it in a designated database.

[2061] "Generative AI" is an artificial intelligence technology that analyzes large amounts of data and performs optimization and classification. In this invention, it refers to a model for performing precise analysis and processing of information.

[2062] "Optimization" refers to the process of using generative AI to analyze and classify stored information, remove incomplete or duplicate data, and transform it into more accurate and useful information.

[2063] "Means for receiving medical history and concerns" refers to a function that allows a user to input their medical history and current concerns into a terminal and send that data to a server.

[2064] The "means for searching for similar cases" refers to a system that searches for similar cases from a database based on the information received by the server and extracts information that will be useful to the user.

[2065] "Means for providing search results" refers to the method by which the server displays and provides the results to the user in the most appropriate format based on the information searched.

[2066] "A means for users in similar situations to connect through chat" refers to a function that matches consenting users, creates chat rooms, and allows them to communicate in real time.

[2067] "Means for recognizing emotional states" refers to a system that uses natural language processing and image analysis technology to grasp the emotions of a user in real time from the text, image, and audio data entered by the user.

[2068] The "means for generating emotion data" refers to a function that generates the recognized emotion of the user as data and stores it in a database.

[2069] "Means for optimizing information provision and interfaces based on emotional state" refers to a process for improving the user experience by providing optimal information and interfaces according to the user's current emotional state.

[2070] This invention is an integrated system that combines an emotion engine with a system that collects information on failed or difficult-to-treat cases, optimizes and classifies it using generative AI, and provides it to users. Specifically, it is composed of the following modules: a data collection module, an emotion engine, an interface optimization module, a database construction module, a case search module, and a chat function module.

[2071] Data Collection Module

[2072] A user uses a terminal to input information about failed or difficult-to-treat cases. The input interface should be designed to be intuitive and easy to use. The terminal formats the input information and sends it to a server via the internet. The server receives the transmitted information and stores it in an appropriate database. When storing the information, an initial evaluation and check is performed to ensure consistency and accuracy. A database management system (e.g., MySQL, PostgreSQL) is used for this process.

[2073] Emotion Engine

[2074] The server recognizes emotions in real time from the user's input and actions. This emotion recognition uses natural language processing technology (e.g., the BERT model) and image analysis technology (e.g., OpenCV, TensorFlow). The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[2075] Interface Optimization Module

[2076] The server searches for and provides the most appropriate information depending on the user's emotional state. For example, if the user is highly stressed, it will prioritize displaying encouraging words and success stories. The device then displays this information to the user in an appropriate format that is easy for the user to view and understand. This process uses information search technology (e.g., Elasticsearch).

[2077] Database construction module

[2078] The server periodically retrieves all data stored in the database and analyzes and classifies it using a generation AI (e.g., GPT-3, BERT). The generation AI removes incomplete and duplicate data and processes it to make it more accurate and useful information, and the optimized data is then stored back in the database.

[2079] Case Search Module

[2080] The user inputs their current medical history and concerns into the device. The input information is sent to the server, which analyzes the received information and searches for similar cases in the database. This process uses machine learning algorithms (e.g., k-NN, SVM). The server generates search results and sends them to the device, which then displays them to the user.

[2081] Chat Function Module

[2082] The user agrees to use the chat function and sends the consent information from the device to the server. The server uses the consent information to search for users in the same situation in its database and matches them. The server creates a chat room for the matched user, and the device notifies the user of the chat room information. The user joins the chat room and shares information with other users, and the emotion engine analyzes the conversation content in real time to provide appropriate support and advice.

[2083] Specific examples

[2084] Example 1: When a user enters information and searches for similar cases

[2085] The user enters details about their own failed surgery into the device. The emotion engine then recognizes the user's emotions from the input. The device then sends the information to the server, which then searches the database for similar cases. Emotional data is also taken into consideration, and appropriate information is provided preferentially. Search results provide details of follow-up treatments and prognoses for past cases of similar failed surgery.

[2086] Example 2: When users share information through chat

[2087] Users agree to use the chat function, and the server matches them with other users in the same situation. The server creates a chat room and notifies the user via their device. The user joins the chat room and shares information with other users. The emotion engine analyzes the content of the conversation and provides appropriate support and advice.

[2088] This system provides optimal information and support according to the user's psychological needs, creating an environment in which both doctors and patients can proceed with treatment with peace of mind.

[2089] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2090] Step 1: Enter your information

[2091] The user uses the terminal to input detailed information about failed or difficult-to-treat cases (such as progress, treatment, case details, and how to explain the case to the family).

[2092] Input: Case data (text, images, etc.)

[2093] Specific operation: The terminal temporarily stores the entered data in memory and checks the format. If there is an error in the entered data, the user is prompted to re-enter it.

[2094] Step 2: Submit your information

[2095] The terminal transmits the input information to the server.

[2096] Input: User-entered case data

[2097] Output: Formatted case data sent to the server

[2098] Specific operation: The terminal converts the case data into an appropriate format (JSON, XML, etc.), encrypts it using SSL / TLS, and sends it to the server.

[2099] Step 3: Receiving and storing information

[2100] The server receives the information sent from the terminal and stores it in a database.

[2101] Input: Encrypted case data

[2102] Output: Case data stored in a database

[2103] What it does: The server decrypts the data it receives and stores the information using a database management system (e.g., MySQL, PostgreSQL). It checks for consistency and accuracy.

[2104] Step 4: Recognize emotions

[2105] The server recognizes emotions in real time from the user's input and actions.

[2106] Input: User input and behavioral data (text, images, audio)

[2107] Output: Emotion data

[2108] Specific operation: Using natural language processing technology (BERT model) and image analysis technology (OpenCV, TensorFlow), the system analyzes user emotions, generates emotion data, and stores it.

[2109] Step 5: Storing and using emotion data

[2110] The recognized emotion data is stored in a database and used for subsequent information provision and interface optimization.

[2111] Input: Emotion data

[2112] Output: Emotion data stored in a database

[2113] Specific operation: The server stores the generated emotion data in a database, making it available for searches and information provision.

[2114] Step 6: Regularly collect and optimize information

[2115] The server periodically retrieves all data stored in the database and optimizes it using generative AI.

[2116] Input: Case data and emotion data stored in the database

[2117] Output: Optimized data

[2118] Specific operation: The server periodically imports data and uses generative AI (GPT-3, BERT) to analyze, classify, and optimize the information, removing incomplete and duplicate data.

[2119] Step 7: Restoring the optimized data

[2120] The optimized data is then saved back into the database.

[2121] Input: Optimized data

[2122] Output: Data resaved to the database

[2123] Specific operation: The data optimized by the generative AI is stored back in the database, making it available for future searches and information provision.

[2124] Step 8: Enter your medical history and concerns

[2125] The user inputs their current medical history and concerns into the terminal.

[2126] Input: Current medical history and concerns

[2127] Output: Entered medical history and problem data

[2128] Specific operation: The device receives this data, checks the format again, and then saves it.

[2129] Step 9: Submit and retrieve information

[2130] The terminal sends the input information to the server, which analyzes the received information and searches the database for similar cases.

[2131] Input: Medical history and problem data

[2132] Output: Search results for similar cases

[2133] Specific operation: The server uses machine learning algorithms (k-NN, SVM) to search for similar cases and generate search results.

[2134] Step 10: Serving search results

[2135] The server transmits the generated search results to the terminal, which displays the results to the user.

[2136] Input: Search results for similar cases

[2137] Output: Search results displayed to the user

[2138] Specific operation: The server sends the search results to the terminal, and the terminal displays the results in an easy-to-read format for the user.

[2139] Step 11: Gather consent and match for chat features

[2140] Users agree to use the chat function, and the server matches users with similar circumstances based on the consent information.

[2141] Input: consent information

[2142] Output: Chat partner matching information

[2143] Specific operation: The server records the consent information in a database and uses similarity calculations (e.g., Jaccard coefficient) to match users with the same concerns or symptoms.

[2144] Step 12: Create and notify chat rooms

[2145] The server creates a chat room for the matched user, and the terminal sends a notification to the user to join the chat room.

[2146] Input: Matching information

[2147] Output: Generated chat room information

[2148] Specific operation: The server creates a chat room and sends the information to the device. The user is notified and can join the chat room.

[2149] Step 13: Chat sentiment analysis and support

[2150] The server uses an emotion engine in the chat room to analyze the user's emotions in real time and provide appropriate support.

[2151] Input: Chat content

[2152] Output: Sentiment analysis results and supporting information

[2153] Specific operation: The server analyzes chat content, generates emotional data, and provides appropriate advice and support information based on the analysis results.

[2154] (Application example 2)

[2155] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2156] Conventional medical information systems lack the ability to collect and analyze information on failed or difficult-to-treat cases, and are often unable to provide optimal information tailored to the user's emotional state. Furthermore, there are issues with utilizing information in physical stores that sell health-related products, making it difficult to receive effective support.

[2157] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2158] In this invention, the server includes a means for inputting information about failed cases, a means for receiving the input information and storing it in a database, a means for using a generation AI to optimize the stored information, a means for receiving the medical history and concerns from the user and searching for similar cases from the database, a means for providing the search results to the user, a means for connecting users with similar circumstances through chat, a means for performing emotion recognition and providing information according to the user's emotional state, and a means for use in physical stores that handle health-related products. This enables the provision of optimal information and support tailored to the user's emotional state, improving the quality of medical services in physical stores.

[2159] "Failed cases" are cases in which treatment or surgery did not produce the expected results.

[2160] "Means for inputting information" refers to an interface or device that allows a user to input information into the system.

[2161] "Means for receiving information and storing it in a database" refers to the technical means for receiving input information and storing it in a database.

[2162] "Generative AI" is an artificial intelligence technique used to analyze, optimize, and classify large amounts of data.

[2163] The "means for receiving medical history and concerns from the user" refers to an interface or device that allows the user to input their current medical history and concerns.

[2164] The "means for searching for similar cases" refers to a technical means for searching for similar cases from a database based on user input.

[2165] The "means for providing search results to the user" refers to an interface or device for displaying and providing the searched information to the user.

[2166] "A means for users in similar circumstances to connect through chat" is a technology that matches users with similar medical histories and concerns, allowing them to exchange information through chat.

[2167] "Means for emotion recognition" refers to technology for analyzing and recognizing emotions from user input and behavior.

[2168] "Means for providing information according to the user's emotional state" refers to technology that provides optimal information and advice to the user based on the results of emotion recognition.

[2169] A "brick and mortar store" is a physical store that sells health-related products.

[2170] In order to implement the present invention, it is important to link various hardware and software components. The specific configurations and operation methods of each component will be described below.

[2171] Enter and submit information

[2172] Users use devices such as smartphones or tablets to input information about failed or difficult-to-treat cases (e.g., progression of symptoms, treatment, case details, how to explain to family members, etc.). The input interface is designed to be intuitive and easy to use. The input information is sent from the device to the server.

[2173] Receiving and storing information

[2174] The server stores the received information in a database in an appropriate format, with some initial evaluation and consistency checks to ensure the information is consistent and accurate. This process is carried out using a database management system (DBMS).

[2175] emotion recognition

[2176] The server recognizes emotions in real time from the content and actions the user inputs into the device. This emotion recognition uses natural language processing and image analysis technologies. Specifically, it uses the Hugging Face transformers library to analyze emotions from the user's input text. This emotional data is used to provide subsequent information and optimize the interface.

[2177] Information optimization and classification

[2178] The server analyzes and optimizes all stored data using a generative AI model. Specifically, it combines natural language processing and topic modeling (e.g., using TfidfVectorizer and NMF) to classify and organize the input information. The optimized data is then re-stored in the database.

[2179] Search and Information

[2180] When a user enters their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in its database. The search results, including information on the case's treatment, prognosis, and explanation method, are provided to the user's device from the server.

[2181] Chat feature

[2182] When a user agrees to use the chat function, the server searches the database for other users in the same situation and matches them. The server then creates a chat room so that matched users can share information through chat. Within this chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[2183] Use in physical stores

[2184] In physical stores, patients and medical staff can collect and share case information using smartphones or tablets. For example, pharmacies and medical equipment stores can provide advice and product information based on past treatment failures or difficult cases. An emotion engine can also simultaneously provide information to reduce users' stress and anxiety.

[2185] Examples of concrete examples and prompts

[2186] A concrete example is a smartphone application for pharmacies. When a patient purchases medicine at the pharmacy, the application searches for information on past treatment failures or difficult cases and provides the most appropriate advice and product information. In addition, an emotion engine detects the patient's anxiety or stress and provides encouraging messages and self-care information.

[2187] Example prompt sentence:

[2188] "I would like to gather detailed information about a recent treatment failure for patient XYZ and recommend the best course of action to remedy this."

[2189] In this way, the present invention can provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[2190] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2191] Step 1:

[2192] Entering information

[2193] Users use the input interface on their smartphone or tablet to input information about failed or difficult-to-treat cases, such as the progression of symptoms, treatment, case details, and how to explain the case to family members. This information is then stored on the device.

[2194] Input and Output:

[2195] Input: Detailed information about failed or difficult cases

[2196] Output: Information stored on the device

[2197] Step 2:

[2198] Sending information

[2199] The device formats the information entered by the user and transmits it over the Internet to a server, ensuring the data remains consistent and accurate.

[2200] Input and Output:

[2201] Input: Information stored on your device

[2202] Output: Formatted information is sent to the server

[2203] Step 3:

[2204] Receiving and storing information

[2205] The server receives the information sent from the device and stores it in a database in an appropriate format, with an initial evaluation and consistency check of the information before storing it.

[2206] Input and Output:

[2207] Input: Formatted information

[2208] Output: Information stored in the database

[2209] Step 4:

[2210] emotion recognition

[2211] The server analyzes the input and actions of the user on the device and performs emotion recognition. This emotion recognition uses the Hugging Face transformers library for text analysis. The recognized emotion data is stored in a database.

[2212] Input and Output:

[2213] Input: User-entered text and action data

[2214] Output: Analyzed sentiment data

[2215] Step 5:

[2216] Information optimization and classification

[2217] The server analyzes the information stored in the database using a generative AI model to optimize and classify the information. Topic modeling using TfidfVectorizer and NMF is performed here. The optimized data is then stored back in the database.

[2218] Input and Output:

[2219] Input: Information stored in a database

[2220] Output: Optimized information data

[2221] Step 6:

[2222] Search and Information

[2223] When a user inputs their medical history and concerns into their device, the information is sent to the server. The server uses this information to search for similar cases in the database and selects the most appropriate information. The selected information is then provided to the user's device from the server.

[2224] Input and Output:

[2225] Input: User-entered medical history and problem information

[2226] Output: Information on similar cases is provided to the user's device.

[2227] Step 7:

[2228] Chat feature

[2229] When a user agrees to use the chat function, the server searches for other users in the same situation and matches them. The server then creates a chat room so that matched users can exchange information through chat. Within the chat room, an emotion engine analyzes the user's emotions and provides appropriate support and advice.

[2230] Input and Output:

[2231] Input: User information that you have agreed to use

[2232] Output: Matched chat room information

[2233] Step 8:

[2234] Use in physical stores

[2235] In physical stores, patients and medical staff can use smartphones and tablets to collect and share case information. For example, advice and product information based on past treatment failures or difficult cases can be provided. An emotion engine also provides information to reduce users' stress and anxiety.

[2236] Input and Output:

[2237] Input: Case information and emotion data

[2238] Output: In-store advice and product information

[2239] This allows the system to provide optimal information and support according to the user's emotional state, improving the quality of medical services in physical stores.

[2240] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2241] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2242] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2243] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2244] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2245] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2246] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2247] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2248] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2249] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2250] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2251] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2252] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2253] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2254] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2255] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2256] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2257] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2258] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2259] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2260] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2261] The following is further disclosed regarding the above embodiment.

[2262] (Claim 1)

[2263] a means for inputting information regarding failure cases;

[2264] means for receiving the...

Claims

1. a means for inputting information regarding failure cases; means for receiving the input information and storing it in a database; A generative AI-based method for optimizing stored information; A means to receive medical history and concerns from users and search for similar cases from the database; a means for providing search results to a user; A way for users in the same situation to connect through chat, A system including:

2. 10. The system of claim 1, further comprising means for providing a database for aggregating information regarding failure cases and maintaining the accuracy and relevance of that information.

3. 2. The system according to claim 1, further comprising means for allowing a user to input his / her current medical history and concerns, and for searching and providing treatments, progress and explanations of similar cases based on the information.

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