System

Abstract

An object of a system according to an embodiment is to promote use of online medical care by allowing a user to determine an appropriate medical department for his / her symptoms.SOLUTION: A system according to an embodiment includes a symptom input unit, a medical department suggestion unit, an online medical care guidance unit, and a subscription promotion unit. The symptom input unit allows the user to input his / her own symptom. The department proposal unit analyzes the symptom input by the symptom input unit and proposes an appropriate department. The online medical care guidance unit guides online medical care based on the medical department proposed by the medical department proposal unit. The subscription promotion unit promotes use of the online medical care guided by the online medical care guidance unit.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] Conventional technology has made it difficult for users to determine the appropriate medical department for their symptoms, and there has been an issue of not promoting the use of online medical care sufficiently.

[0005] The system according to the embodiment aims to enable users to determine the appropriate medical department for their symptoms and promote the use of online medical care. [Means for solving the problem]

[0006] The system according to the embodiment comprises a symptom input unit, a medical department suggestion unit, an online medical consultation guide unit, and a subscription promotion unit. The symptom input unit allows a user to input their own symptoms. The medical department suggestion unit analyzes the symptoms input by the symptom input unit and suggests an appropriate medical department. The online medical consultation guide unit provides information about online medical consultations based on the medical department suggested by the medical department suggestion unit. The subscription promotion unit promotes the use of online medical consultations recommended by the online medical consultation guide unit. [Effects of the Invention]

[0007] The system according to the embodiment allows users to determine the appropriate medical department for their symptoms, thereby promoting the use of online medical care. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The department selection app according to an embodiment of the present invention is a system in which users input their symptoms, a generation AI summarizes them, and suggests an appropriate department, providing the convenience of online medical care. As a result, the department selection app allows users to receive medical care easily, saving them the trouble of going to the hospital. It also increases the number of subscribers to the HELPO app and expands the number of users of the company's services.

[0029] The medical department determination app according to the embodiment includes a symptom input unit, a medical department suggestion unit, an online medical consultation guide unit, and a subscription promotion unit. The symptom input unit allows a user to input their symptoms. For example, the user inputs symptoms into the app via text. The symptom input unit can also input symptoms via voice. For example, if a user inputs "I have a persistent headache," the generation AI analyzes the voice data and suggests an appropriate medical department. The medical department suggestion unit analyzes the symptoms input by the symptom input unit and suggests an appropriate medical department. For example, the generation AI suggests "neurology" or "internal medicine." The medical department suggestion unit can also refer to past medical history to suggest a more accurate medical department. For example, if a user has previously visited a "neurology" department for a "headache," the system will suggest "neurology" again. The online medical consultation guide unit provides online medical consultation information based on the medical department suggested by the medical department suggestion unit. For example, it displays a message such as, "You can continue with an online consultation and receive a prescription." The online medical consultation information unit can also refer to a user's past online medical consultation history to suggest the most appropriate medical plan. For example, if a user has previously received online medical consultation for a headache, it can suggest another online consultation with a neurologist. The subscription promotion unit encourages users to use the online medical consultations recommended by the online medical consultation information unit. For example, it displays a message such as, "By subscribing to the HELPO app, you can receive online medical consultations." The subscription promotion unit can also suggest customized subscription plans based on the user's health condition and lifestyle. For example, if the user is a smoker, the generation AI would suggest a subscription plan that includes a smoking cessation program. This allows the department selection app to save users the trouble of going to the hospital and make it easier to receive medical treatment. It can also increase the number of HELPO app subscribers and expand the users of the company's services.

[0030] The symptom input unit uses voice input, and the generation AI can analyze the voice data and suggest a medical specialty. For example, when a user voice-inputs their symptoms into the app, the generation AI analyzes the voice data and suggests an appropriate medical specialty. For example, if a user voice-inputs "I've had a persistent headache," the generation AI uses voice recognition technology to suggest "neurology" or "internal medicine." Voice input also allows users to input symptoms without using their hands. For example, even while driving or with their hands full, they can input symptoms by voice, and the generation AI analyzes the voice data to suggest a medical specialty. Voice input also allows users to communicate their symptoms in a more natural way. For example, if a user voice-inputs "I've been having trouble sleeping lately," the generation AI analyzes the voice data and suggests "neurology" or "internal medicine." This allows users to input symptoms without using their hands.

[0031] The symptom input unit can refer to past medical history to suggest a more accurate medical specialty. For example, when a user inputs symptoms into the app, the symptom input unit uses the generation AI to refer to past medical history to suggest a more accurate medical specialty. For example, if the user has previously visited a neurologist for a headache, the AI ​​will again suggest neurologist. By referring to past medical history, the AI ​​can comprehensively assess the user's health condition and suggest an appropriate medical specialty. For example, if the user has previously visited an internal medicine specialist for high blood pressure, the AI ​​will suggest internal medicine based on the user's current symptoms. By referring to past medical history, the AI ​​can improve the accuracy of suggesting medical specialty options for the user's symptoms. For example, if the user has previously visited a dermatologist for allergies, the AI ​​will suggest dermatology based on the user's current symptoms. In this way, the AI ​​can comprehensively assess the user's health condition and suggest an appropriate medical specialty by referring to past medical history.

[0032] The symptom input section adds a function that allows users to upload images and videos, allowing the generation AI to analyze the visual information and suggest a medical specialty. For example, when a user enters symptoms into the app, the symptom input section adds a function that allows users to upload images and videos, and the generation AI analyzes the visual information and suggests a medical specialty. For example, if an image of a skin rash is uploaded, the generation AI will suggest "dermatology." Uploading images and videos also allows users to communicate more specific symptoms. For example, if a video of a cough is uploaded, the generation AI will analyze the video and suggest "respiratory medicine." Analyzing visual information also allows the generation AI to suggest more accurate medical specialty suggestions. For example, if an image of bloodshot eyes is uploaded, the generation AI will analyze the image and suggest "ophthalmology." This allows users to communicate more specific symptoms by uploading images and videos.

[0033] The symptom input unit can display similar cases of other users for reference. For example, when a user inputs symptoms into the app, the symptom input unit allows the generation AI to display similar cases of other users for reference. For example, if the user inputs "persistent headache," other users' cases of "headache" will be displayed. By displaying similar cases, the user can deepen their understanding of their own symptoms. For example, if the user inputs "persistent stomachache," other users' cases of "stomachache" will be displayed for reference. By displaying similar cases of other users, the user can learn how to deal with their own symptoms. For example, if the user inputs "uncontrollable cough," other users' cases of "cough" will be displayed for reference. In this way, by displaying similar cases of other users, the user can deepen their understanding of their own symptoms.

[0034] The medical specialty suggestion unit can provide health information and preventive measures related to symptoms in addition to the medical specialty suggested by the generation AI. For example, if a user inputs "I have persistent headaches," the generation AI would suggest "neurology" and further provide "headache prevention measures" and "stress management methods." Providing health information related to symptoms also allows users to gain a deeper understanding of their own health condition. For example, if a user inputs "I have persistent stomach pain," the generation AI would suggest "internal medicine" and further provide "causes of stomach pain" and "dietary precautions." Providing preventive measures related to symptoms also allows users to learn specific methods for maintaining their health. For example, if a user inputs "I have a persistent cough," the generation AI would suggest "respiratory medicine" and further provide "cough prevention measures" and "throat care methods." Providing health information and preventive measures related to symptoms allows users to gain a deeper understanding of their own health condition.

[0035] The medical specialty suggestion unit can provide an interactive function that allows the user to input additional questions for the medical specialty suggested by the generation AI. The medical specialty suggestion unit provides, for example, an interactive function that allows the user to input additional questions for the medical specialty suggested by the generation AI. For example, if "neurology" is suggested, the user can ask, "What kind of treatment will be available?" By providing an interactive function, the user can clear up any doubts they may have about the medical specialty. For example, if "internal medicine" is suggested, the user can ask, "What kind of tests will be required?" By providing a function that allows the user to input additional questions, the user can deepen their understanding of the medical specialty. For example, if "dermatology" is suggested, the user can ask, "What kind of medication will be prescribed?" By providing an interactive function that allows the user to input additional questions for the medical specialty suggested by the generation AI, the user can clear up any doubts they may have about the medical specialty.

[0036] The medical department suggestion unit can display the latest research papers and news articles related to the medical department suggested by the generation AI. The medical department suggestion unit, for example, displays the latest research papers and news articles related to the medical department suggested by the generation AI. For example, if "neurology" is suggested, the latest research papers and news articles related to that medical department are displayed. In addition, by displaying the latest research papers and news articles, the user can obtain the latest information on the medical department. For example, if "internal medicine" is suggested, the latest research papers and news articles related to that medical department are displayed. In addition, by providing the latest information related to the medical department suggested by the generation AI, the user can deepen their understanding of the medical department. For example, if "dermatology" is suggested, the latest research papers and news articles related to that medical department are displayed. In this way, by displaying the latest research papers and news articles related to the medical department suggested by the generation AI, the user can obtain the latest information on the medical department.

[0037] The online medical consultation guide unit can refer to the user's past online medical consultation history and propose an optimal medical consultation plan. The online medical consultation guide unit, for example, refers to the user's past online medical consultation history and proposes an optimal medical consultation plan. For example, if the user has previously received online medical consultation for "headache," the online medical consultation with "neurology" is proposed again. Furthermore, by referring to the past online medical consultation history, the unit comprehensively assesses the user's health condition and proposes an optimal medical consultation plan. For example, if the user has previously received online medical consultation for "high blood pressure," the unit proposes an online medical consultation with "internal medicine" based on the user's current symptoms. Furthermore, by referring to the past online medical consultation history, the unit improves the accuracy of proposals for medical consultation plans for the user's symptoms. For example, if the user has previously received online medical consultation for "allergies," the unit proposes an online medical consultation with "dermatology" based on the user's current symptoms. In this way, the unit comprehensively assesses the user's health condition and proposes an optimal medical consultation plan by referring to the past online medical consultation history.

[0038] The online medical consultation information unit can provide a customized medical plan that takes into account the user's lifestyle and environmental information. The online medical consultation information unit provides a customized medical plan that takes into account the user's lifestyle and environmental information, for example. For example, if the user is a "smoker," the generation AI suggests an online medical consultation with a "respiratory medicine" specialist. By taking lifestyle and environmental information into consideration, the optimal medical plan for the user is provided. For example, if the user lives a "desk-centered" lifestyle, the generation AI suggests an online medical consultation with an "orthopedic" specialist. By providing a customized medical plan based on the user's lifestyle and environmental information, more effective medical treatment is achieved. For example, if the user works in a "high-stress environment," the generation AI suggests an online medical consultation with a "psychosomatic medicine" specialist. In this way, the optimal medical plan for the user is provided by taking into account the user's lifestyle and environmental information.

[0039] The online medical consultation unit can provide a function that allows a user to chat directly with a specialist in a medical department selected by the user. The online medical consultation unit provides, for example, a function that allows a user to chat directly with a specialist in a medical department selected by the user. For example, a user who selects "neurology" can consult with a specialist in that department via chat. Furthermore, by providing a function that allows a user to chat directly with a specialist, the user can resolve any doubts about the medical department. For example, a user who selects "internal medicine" can consult with a specialist in that department via chat. Furthermore, by providing a function that allows a user to chat directly with a specialist in the medical department selected by the user, the user can deepen their understanding of the medical department. For example, a user who selects "dermatology" can consult with a specialist in that department via chat. Thus, by providing a function that allows a user to chat directly with a specialist in the medical department selected by the user, the user can resolve any doubts about the medical department.

[0040] The online medical consultation information unit can use video to explain the procedures and preparations required for a user to receive medical treatment. The online medical consultation information unit, for example, uses video to explain the procedures and preparations required for a user to receive medical treatment. For example, the "flow of online medical treatment" is visually explained using video. Furthermore, by using video, the user can intuitively understand the procedures and preparations required for receiving medical treatment. For example, the "preparation items for online medical treatment" is explained using video. Furthermore, by explaining the procedures and preparations required for receiving medical treatment using video, anxiety about online medical treatment is reduced. For example, the "procedures for online medical treatment" is explained using video, allowing the user to receive medical treatment with peace of mind. In this way, by using video, the user can intuitively understand the procedures and preparations required for receiving medical treatment.

[0041] The subscription promotion unit can propose a customized subscription plan based on the user's health condition and lifestyle habits. The subscription promotion unit proposes, for example, a customized subscription plan based on the user's health condition and lifestyle habits. For example, if the user is a "smoker," the generation AI proposes a subscription plan that includes a "smoking cessation program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, the optimal plan for the user is provided. For example, if the user lives a "desk-based" lifestyle, the generation AI proposes a subscription plan that includes an "exercise program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved. For example, if the user works in a "high-stress environment," the generation AI proposes a subscription plan that includes a "stress management program." In this way, by proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved.

[0042] The subscription promotion unit can refer to the user's past medical history and provide the optimal subscription plan. The subscription promotion unit, for example, refers to the user's past medical history and provides the optimal subscription plan. For example, if there is a history of medical treatment for "headache" in the past, the generation AI proposes a subscription plan that includes a "headache management program." Also, by referring to the past medical history, the optimal subscription plan is provided to the user. For example, if there is a history of medical treatment for "high blood pressure" in the past, the generation AI proposes a subscription plan that includes a "high blood pressure management program." Also, by referring to the past medical history, the generation AI provides a subscription plan that suits the user's health condition. For example, if there is a history of medical treatment for "allergies" in the past, the generation AI proposes a subscription plan that includes an "allergy management program." In this way, by referring to the past medical history, the optimal subscription plan is provided to the user.

[0043] The enrollment promotion unit can display, in a simulation, specific benefits that the user will gain by joining. The enrollment promotion unit, for example, displays, in a simulation, specific benefits that the user will gain by joining. For example, it visually displays, in a simulation, a "health management plan after joining." Furthermore, by using a simulation, the user can intuitively understand the benefits that the user will gain by joining. For example, it displays, in a simulation, the "effect of medical expenses savings after joining." Furthermore, by displaying, in a simulation, specific benefits that the user will gain by joining, the enrollment is promoted. For example, it displays, in a simulation, the "effect of improved health status after joining." In this way, by using the simulation, the user can intuitively understand the benefits that the user will gain by joining.

[0044] The enrollment promotion unit can display success stories and testimonials of other users. The enrollment promotion unit displays, for example, success stories and testimonials of other users. For example, it displays "testimonials of users who improved their health by using the HELPO app." By displaying success stories and testimonials, users can specifically understand the benefits of enrolling. For example, it displays "success stories of users who saved on medical expenses by using the HELPO app." By displaying success stories and testimonials of other users, enrollment is promoted. For example, it displays "testimonials of users who were able to detect illness early by using the HELPO app." In this way, by displaying success stories and testimonials of other users, enrollment is promoted.

[0045] The online medical consultation guidance unit can refer to the user's past medical history and present specific advantages of online medical consultation. The online medical consultation guidance unit, for example, refers to the user's past medical history and presents specific advantages of online medical consultation. For example, if there is a history of receiving online medical consultation in the past for "headache," the advantages of that consultation are presented. Furthermore, by referring to the past medical history, specific advantages of online medical consultation are presented to the user. For example, if there is a history of receiving online medical consultation in the past for "high blood pressure," the advantages of that consultation are presented. Furthermore, by referring to the past medical history, the user can specifically understand the advantages of online medical consultation. For example, if there is a history of receiving online medical consultation in the past for "allergies," the advantages of that consultation are presented. In this way, by referring to the past medical history, specific advantages of online medical consultation are presented to the user.

[0046] The online medical consultation information unit can provide customized benefits that take into account the user's lifestyle and environmental information. The online medical consultation information unit provides customized benefits that take into account the user's lifestyle and environmental information, for example. For example, if the user is a "smoker," the generating AI presents benefits including a "smoking cessation program." Furthermore, by taking into account lifestyle and environmental information, the optimal online medical consultation benefits are provided to the user. For example, if the user lives a "desk-based" lifestyle, the generating AI presents benefits including an "exercise program." Furthermore, by providing customized online medical consultation benefits based on the user's lifestyle and environmental information, more effective appeal is achieved. For example, if the user works in a "high-stress environment," the generating AI presents benefits including a "stress management program." In this way, the optimal online medical consultation benefits are provided to the user by taking into account the user's lifestyle and environmental information.

[0047] The online medical consultation information unit can display success stories and testimonials of other users. The online medical consultation information unit displays, for example, success stories and testimonials of other users. For example, it displays "testimonials of users who improved their health by using online medical consultations." Furthermore, by displaying success stories and testimonials, users can concretely understand the convenience of online medical consultations. For example, it displays "success stories of users who were able to save on medical expenses by using online medical consultations." Furthermore, by displaying success stories and testimonials of other users, the convenience of online medical consultations is promoted. For example, it displays "testimonials of users who were able to detect illness early by using online medical consultations." In this way, by displaying success stories and testimonials of other users, the convenience of online medical consultations is promoted.

[0048] The subscription promotion unit can propose a customized subscription plan based on the user's health condition and lifestyle habits. The subscription promotion unit proposes, for example, a customized subscription plan based on the user's health condition and lifestyle habits. For example, if the user is a "smoker," the generation AI proposes a subscription plan that includes a "smoking cessation program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, the optimal plan for the user is provided. For example, if the user lives a "desk-based" lifestyle, the generation AI proposes a subscription plan that includes an "exercise program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved. For example, if the user works in a "high-stress environment," the generation AI proposes a subscription plan that includes a "stress management program." In this way, by proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved.

[0049] The subscription promotion unit can refer to the user's past medical history and provide the optimal subscription plan. The subscription promotion unit, for example, refers to the user's past medical history and provides the optimal subscription plan. For example, if there is a history of medical treatment for "headache" in the past, the generation AI proposes a subscription plan that includes a "headache management program." Also, by referring to the past medical history, the optimal subscription plan is provided to the user. For example, if there is a history of medical treatment for "high blood pressure" in the past, the generation AI proposes a subscription plan that includes a "high blood pressure management program." Also, by referring to the past medical history, the generation AI provides a subscription plan that suits the user's health condition. For example, if there is a history of medical treatment for "allergies" in the past, the generation AI proposes a subscription plan that includes an "allergy management program." In this way, by referring to the past medical history, the optimal subscription plan is provided to the user.

[0050] The enrollment promotion unit can display, in a simulation, specific benefits that the user will gain by joining. The enrollment promotion unit, for example, displays, in a simulation, specific benefits that the user will gain by joining. For example, it visually displays, in a simulation, a "health management plan after joining." Furthermore, by using a simulation, the user can intuitively understand the benefits that the user will gain by joining. For example, it displays, in a simulation, the "effect of medical expenses savings after joining." Furthermore, by displaying, in a simulation, specific benefits that the user will gain by joining, the enrollment is promoted. For example, it displays, in a simulation, the "effect of improved health status after joining." In this way, by using the simulation, the user can intuitively understand the benefits that the user will gain by joining.

[0051] The enrollment promotion unit can display success stories and testimonials of other users. The enrollment promotion unit displays, for example, success stories and testimonials of other users. For example, it displays "testimonials of users who improved their health by using the HELPO app." By displaying success stories and testimonials, users can specifically understand the benefits of enrolling. For example, it displays "success stories of users who saved on medical expenses by using the HELPO app." By displaying success stories and testimonials of other users, enrollment is promoted. For example, it displays "testimonials of users who were able to detect illness early by using the HELPO app." In this way, by displaying success stories and testimonials of other users, enrollment is promoted.

[0052] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0053] The symptom input unit can be equipped with a function to evaluate the severity of symptoms when the user inputs them. For example, if the user inputs "persistent headache," the generation AI will evaluate the severity of the symptom and provide an evaluation such as "mild headache" or "severe headache." It can also suggest an appropriate medical specialty depending on the severity of the symptom. For example, for a "mild headache," it would suggest "internal medicine," and for a "severe headache," it would suggest "neurology." Furthermore, by evaluating the severity of symptoms, the user can understand the seriousness of their symptoms and take appropriate measures. For example, for "mild abdominal pain," it would suggest "rest at home," and for "severe abdominal pain," it would suggest "visit an emergency room." This allows the user to understand the seriousness of their symptoms and take appropriate measures.

[0054] The medical department suggestion unit can suggest the need for vaccinations or health checkups based on the symptoms entered by the user. For example, if a user enters "persistent cough," the generation AI will suggest "influenza vaccination." It can also suggest appropriate health checkups based on the user's age and gender. For example, it will suggest "regular health checkups" for users over 40 years old. By suggesting vaccinations and health checkups, users can also learn specific methods for maintaining their own health. For example, it will suggest "blood pressure measurement" for a user diagnosed with "high blood pressure risk." In this way, by suggesting vaccinations and health checkups, users can learn specific methods for maintaining their own health.

[0055] The online medical consultation information unit can provide a function to shorten the waiting time when a user receives medical treatment. For example, when a user makes an appointment for online medical treatment, the waiting time for the consultation is displayed in real time. In addition, it can prioritize suggestions for medical departments with short waiting times. For example, if the waiting time for "internal medicine" is short, the generation AI will prioritize suggesting "internal medicine." In addition, by providing a function to shorten waiting times, users can receive medical treatment smoothly. For example, it can suggest avoiding times when medical appointments are crowded. In this way, by providing a function to shorten waiting times, users can receive medical treatment smoothly.

[0056] The enrollment promotion unit can display, in a simulation, the specific benefits that the user will gain by enrolling. For example, a "health management plan after enrollment" is visually displayed in a simulation. Furthermore, by using a simulation, the user can intuitively understand the benefits that the user will gain by enrolling. For example, a simulation of the "effect of medical expenses savings after enrollment" is displayed. Furthermore, enrollment is promoted by displaying, in a simulation, the specific benefits that the user will gain by enrolling. For example, a simulation of the "effect of improved health status after enrollment." In this way, by using a simulation, the user can intuitively understand the benefits that the user will gain by enrolling.

[0057] The medical department suggestion unit can display the latest research papers and news articles related to the medical department suggested by the generation AI. For example, if "neurology" is suggested, the latest research papers and news articles related to that medical department will be displayed. In addition, by displaying the latest research papers and news articles, the user can obtain the latest information on the medical department. For example, if "internal medicine" is suggested, the latest research papers and news articles related to that medical department will be displayed. In addition, by providing the latest information related to the medical department suggested by the generation AI, the user can deepen their understanding of the medical department. For example, if "dermatology" is suggested, the latest research papers and news articles related to that medical department will be displayed. In this way, by displaying the latest research papers and news articles related to the medical department suggested by the generation AI, the user can obtain the latest information on the medical department.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: The symptom input unit allows the user to input their symptoms. For example, the user inputs symptoms into the app as text. The symptom input unit can also input symptoms using voice input. For example, if the user inputs "I have a persistent headache," the generation AI analyzes the voice data and suggests an appropriate medical department. Step 2: The medical department suggestion unit analyzes the symptoms entered by the symptom input unit and suggests an appropriate medical department. For example, the generation AI might suggest "neurology" or "internal medicine." The medical department suggestion unit can also refer to past medical history to suggest a more accurate medical department. For example, if there is a history of a patient visiting a "neurology" department for a "headache," it will again suggest "neurology." Step 3: The online medical consultation guidance unit provides online medical consultation guidance based on the medical department proposed by the medical department suggestion unit. For example, it displays a message such as "You can continue with the online medical consultation and receive a prescription for medication." The online medical consultation guidance unit can also refer to the user's past online medical consultation history to suggest the optimal medical treatment plan. For example, if the user has previously received online medical consultation for "headache," it will again suggest online medical consultation with "neurology." Step 4: The subscription promotion unit promotes the use of online medical consultations recommended by the online medical consultation information unit. For example, it displays a message such as, "By subscribing to the HELPO app, you can receive online medical consultations." The subscription promotion unit can also suggest customized subscription plans based on the user's health condition and lifestyle habits. For example, if the user is a "smoker," the generation AI would suggest a subscription plan that includes a "smoking cessation program."

[0060] (Example 2) The department selection app according to an embodiment of the present invention is a system in which users input their symptoms, a generation AI summarizes them, and suggests an appropriate department, providing the convenience of online medical care. As a result, the department selection app allows users to receive medical care easily, saving them the trouble of going to the hospital. It also increases the number of subscribers to the HELPO app and expands the number of users of the company's services.

[0061] The medical department determination app according to the embodiment includes a symptom input unit, a medical department suggestion unit, an online medical consultation guide unit, and a subscription promotion unit. The symptom input unit allows a user to input their symptoms. For example, the user inputs symptoms into the app via text. The symptom input unit can also input symptoms via voice. For example, if a user inputs "I have a persistent headache," the generation AI analyzes the voice data and suggests an appropriate medical department. The medical department suggestion unit analyzes the symptoms input by the symptom input unit and suggests an appropriate medical department. For example, the generation AI suggests "neurology" or "internal medicine." The medical department suggestion unit can also refer to past medical history to suggest a more accurate medical department. For example, if a user has previously visited a "neurology" department for a "headache," the system will suggest "neurology" again. The online medical consultation guide unit provides online medical consultation information based on the medical department suggested by the medical department suggestion unit. For example, it displays a message such as, "You can continue with an online consultation and receive a prescription." The online medical consultation information unit can also refer to a user's past online medical consultation history to suggest the most appropriate medical plan. For example, if a user has previously received online medical consultation for a headache, it can suggest another online consultation with a neurologist. The subscription promotion unit encourages users to use the online medical consultations recommended by the online medical consultation information unit. For example, it displays a message such as, "By subscribing to the HELPO app, you can receive online medical consultations." The subscription promotion unit can also suggest customized subscription plans based on the user's health condition and lifestyle. For example, if the user is a smoker, the generation AI would suggest a subscription plan that includes a smoking cessation program. This allows the department selection app to save users the trouble of going to the hospital and make it easier to receive medical treatment. It can also increase the number of HELPO app subscribers and expand the users of the company's services.

[0062] The symptom input unit uses voice input, and the generation AI can analyze the voice data and suggest a medical specialty. For example, when a user voice-inputs their symptoms into the app, the generation AI analyzes the voice data and suggests an appropriate medical specialty. For example, if a user voice-inputs "I've had a persistent headache," the generation AI uses voice recognition technology to suggest "neurology" or "internal medicine." Voice input also allows users to input symptoms without using their hands. For example, even while driving or with their hands full, they can input symptoms by voice, and the generation AI analyzes the voice data to suggest a medical specialty. Voice input also allows users to communicate their symptoms in a more natural way. For example, if a user voice-inputs "I've been having trouble sleeping lately," the generation AI analyzes the voice data and suggests "neurology" or "internal medicine." This allows users to input symptoms without using their hands.

[0063] The symptom input unit can refer to past medical history to suggest a more accurate medical specialty. For example, when a user inputs symptoms into the app, the symptom input unit uses the generation AI to refer to past medical history to suggest a more accurate medical specialty. For example, if the user has previously visited a neurologist for a headache, the AI ​​will again suggest neurologist. By referring to past medical history, the AI ​​can comprehensively assess the user's health condition and suggest an appropriate medical specialty. For example, if the user has previously visited an internal medicine specialist for high blood pressure, the AI ​​will suggest internal medicine based on the user's current symptoms. By referring to past medical history, the AI ​​can improve the accuracy of suggesting medical specialty options for the user's symptoms. For example, if the user has previously visited a dermatologist for allergies, the AI ​​will suggest dermatology based on the user's current symptoms. In this way, the AI ​​can comprehensively assess the user's health condition and suggest an appropriate medical specialty by referring to past medical history.

[0064] The symptom input unit can use the emotion estimation function to analyze the user's emotions when entering symptoms and provide advice to reduce stress and anxiety. For example, when a user enters symptoms into the app, the symptom input unit uses the emotion estimation function to analyze the user's emotions and provide advice to reduce stress and anxiety. For example, if the user enters "I've been having trouble sleeping lately and I'm feeling anxious," the generation AI will suggest "ways to relax." The emotion estimation function also provides advice based on the user's emotional state. For example, if the user enters "I've been having trouble sleeping lately and I'm feeling irritated," the generation AI will suggest "music to help me relax." The emotion estimation function also provides specific advice to reduce the user's stress and anxiety. For example, if the user enters "I have a stomachache because of work stress," the generation AI will suggest "ways to manage stress." In this way, advice based on the user's emotional state is provided, reducing stress and anxiety.

[0065] The symptom input section adds a function that allows users to upload images and videos, allowing the generation AI to analyze the visual information and suggest a medical specialty. For example, when a user enters symptoms into the app, the symptom input section adds a function that allows users to upload images and videos, and the generation AI analyzes the visual information and suggests a medical specialty. For example, if an image of a skin rash is uploaded, the generation AI will suggest "dermatology." Uploading images and videos also allows users to communicate more specific symptoms. For example, if a video of a cough is uploaded, the generation AI will analyze the video and suggest "respiratory medicine." Analyzing visual information also allows the generation AI to suggest more accurate medical specialty suggestions. For example, if an image of bloodshot eyes is uploaded, the generation AI will analyze the image and suggest "ophthalmology." This allows users to communicate more specific symptoms by uploading images and videos.

[0066] The symptom input unit can display similar cases of other users for reference. For example, when a user inputs symptoms into the app, the symptom input unit allows the generation AI to display similar cases of other users for reference. For example, if the user inputs "persistent headache," other users' cases of "headache" will be displayed. By displaying similar cases, the user can deepen their understanding of their own symptoms. For example, if the user inputs "persistent stomachache," other users' cases of "stomachache" will be displayed for reference. By displaying similar cases of other users, the user can learn how to deal with their own symptoms. For example, if the user inputs "uncontrollable cough," other users' cases of "cough" will be displayed for reference. In this way, by displaying similar cases of other users, the user can deepen their understanding of their own symptoms.

[0067] The symptom input unit can use the emotion estimation function to analyze the emotions associated with the symptoms entered by the user in real time and provide positive feedback. For example, when a user enters symptoms into the app, the symptom input unit uses the emotion estimation function to analyze the emotions associated with the symptoms in real time and provide positive feedback. For example, if a user enters "I'm worried because I've had a persistent headache," the generation AI displays a message such as "It's okay, we'll suggest an appropriate medical specialty." The emotion estimation function also provides positive feedback according to the user's emotional state. For example, if a user enters "I've been having trouble sleeping lately and I'm feeling irritated," the generation AI displays a message such as "We'll suggest ways to relax." The emotion estimation function also provides positive feedback to reduce the user's anxiety and stress. For example, if a user enters "I have a stomachache due to work stress," the generation AI displays a message such as "We'll suggest ways to manage stress." In this way, the user's anxiety and stress are reduced by providing positive feedback according to their emotional state.

[0068] The medical specialty suggestion unit can provide health information and preventive measures related to symptoms in addition to the medical specialty suggested by the generation AI. For example, if a user inputs "I have persistent headaches," the generation AI would suggest "neurology" and further provide "headache prevention measures" and "stress management methods." Providing health information related to symptoms also allows users to gain a deeper understanding of their own health condition. For example, if a user inputs "I have persistent stomach pain," the generation AI would suggest "internal medicine" and further provide "causes of stomach pain" and "dietary precautions." Providing preventive measures related to symptoms also allows users to learn specific methods for maintaining their health. For example, if a user inputs "I have a persistent cough," the generation AI would suggest "respiratory medicine" and further provide "cough prevention measures" and "throat care methods." Providing health information and preventive measures related to symptoms allows users to gain a deeper understanding of their own health condition.

[0069] The medical department suggestion unit can use the emotion estimation function to suggest a medical department based on the user's emotions, providing a sense of security. The medical department suggestion unit can use the emotion estimation function to suggest a medical department based on the user's emotions, providing a sense of security. For example, if the user inputs, "I'm worried because I have a persistent headache," the generation AI would suggest "neurology" and display a message such as, "Don't worry, this is the right department." Furthermore, by suggesting a medical department based on the user's emotional state, the user can feel at ease when visiting a doctor. For example, if the user inputs, "I'm worried because I have persistent stomach pain," the generation AI would suggest "internal medicine" and display a message such as, "Don't worry, this is the right department." Furthermore, by using the emotion estimation function, the unit can suggest a medical department to reduce the user's anxiety and stress. For example, if the user inputs, "I'm worried because my cough won't stop," the generation AI would suggest "respiratory medicine" and display a message such as, "Don't worry, this is the right department." In this way, by suggesting a medical department based on the user's emotional state, the user can feel at ease when visiting a doctor.

[0070] The medical specialty suggestion unit can provide an interactive function that allows the user to input additional questions for the medical specialty suggested by the generation AI. The medical specialty suggestion unit provides, for example, an interactive function that allows the user to input additional questions for the medical specialty suggested by the generation AI. For example, if "neurology" is suggested, the user can ask, "What kind of treatment will be available?" By providing an interactive function, the user can clear up any doubts they may have about the medical specialty. For example, if "internal medicine" is suggested, the user can ask, "What kind of tests will be required?" By providing a function that allows the user to input additional questions, the user can deepen their understanding of the medical specialty. For example, if "dermatology" is suggested, the user can ask, "What kind of medication will be prescribed?" By providing an interactive function that allows the user to input additional questions for the medical specialty suggested by the generation AI, the user can clear up any doubts they may have about the medical specialty.

[0071] The medical department suggestion unit can display the latest research papers and news articles related to the medical department suggested by the generation AI. The medical department suggestion unit, for example, displays the latest research papers and news articles related to the medical department suggested by the generation AI. For example, if "neurology" is suggested, the latest research papers and news articles related to that medical department are displayed. In addition, by displaying the latest research papers and news articles, the user can obtain the latest information on the medical department. For example, if "internal medicine" is suggested, the latest research papers and news articles related to that medical department are displayed. In addition, by providing the latest information related to the medical department suggested by the generation AI, the user can deepen their understanding of the medical department. For example, if "dermatology" is suggested, the latest research papers and news articles related to that medical department are displayed. In this way, by displaying the latest research papers and news articles related to the medical department suggested by the generation AI, the user can obtain the latest information on the medical department.

[0072] The medical specialty suggestion unit can use the emotion estimation function to analyze the user's emotions toward the proposed medical specialty and provide appropriate follow-up. The medical specialty suggestion unit, for example, uses the emotion estimation function to analyze the user's emotions toward the proposed medical specialty and provide appropriate follow-up. For example, if a user who has been suggested "neurology" feels anxious, the generation AI displays a message such as "Don't worry, this is the right medical specialty." Furthermore, by providing follow-up according to the user's emotional state, the user can feel at ease when visiting the clinic. For example, if a user who has been suggested "internal medicine" feels anxious, the generation AI displays a message such as "Don't worry, this is the right medical specialty." Furthermore, by using the emotion estimation function, follow-up is provided to reduce the user's anxiety and stress. For example, if a user who has been suggested "dermatology" feels anxious, the generation AI displays a message such as "Don't worry, this is the right medical specialty." In this way, the emotion estimation function can be used to analyze the user's emotions toward the proposed medical specialty and provide appropriate follow-up, allowing the user to feel at ease when visiting the clinic.

[0073] The online medical consultation guide unit can refer to the user's past online medical consultation history and propose an optimal medical consultation plan. The online medical consultation guide unit, for example, refers to the user's past online medical consultation history and proposes an optimal medical consultation plan. For example, if the user has previously received online medical consultation for "headache," the online medical consultation with "neurology" is proposed again. Furthermore, by referring to the past online medical consultation history, the unit comprehensively assesses the user's health condition and proposes an optimal medical consultation plan. For example, if the user has previously received online medical consultation for "high blood pressure," the unit proposes an online medical consultation with "internal medicine" based on the user's current symptoms. Furthermore, by referring to the past online medical consultation history, the unit improves the accuracy of proposals for medical consultation plans for the user's symptoms. For example, if the user has previously received online medical consultation for "allergies," the unit proposes an online medical consultation with "dermatology" based on the user's current symptoms. In this way, the unit comprehensively assesses the user's health condition and proposes an optimal medical consultation plan by referring to the past online medical consultation history.

[0074] The online medical consultation information unit can provide a customized medical plan that takes into account the user's lifestyle and environmental information. The online medical consultation information unit provides a customized medical plan that takes into account the user's lifestyle and environmental information, for example. For example, if the user is a "smoker," the generation AI suggests an online medical consultation with a "respiratory medicine" specialist. By taking lifestyle and environmental information into consideration, the optimal medical plan for the user is provided. For example, if the user lives a "desk-centered" lifestyle, the generation AI suggests an online medical consultation with an "orthopedic" specialist. By providing a customized medical plan based on the user's lifestyle and environmental information, more effective medical treatment is achieved. For example, if the user works in a "high-stress environment," the generation AI suggests an online medical consultation with a "psychosomatic medicine" specialist. In this way, the optimal medical plan for the user is provided by taking into account the user's lifestyle and environmental information.

[0075] The online medical consultation guidance unit can use the emotion estimation function to provide information to alleviate any anxieties or questions the user may have about online medical consultations. For example, the online medical consultation guidance unit uses the emotion estimation function to provide information to alleviate any anxieties or questions the user may have about online medical consultations. For example, if the user is feeling anxious about online medical consultations, the generation AI explains the benefits and safety of online medical consultations. Furthermore, by providing information according to the user's emotional state, the anxieties and questions about online medical consultations are alleviated. For example, if the user has questions about the online medical consultation procedure, the generation AI explains the online medical consultation process. Furthermore, by using the emotion estimation function, the generation AI provides specific information to alleviate the user's anxieties and questions. For example, if the user is anxious about the effectiveness of online medical consultations, the generation AI explains the track record of online medical consultations and success stories. In this way, the emotion estimation function can be used to provide information to alleviate any anxieties or questions the user may have about online medical consultations, thereby alleviating the anxieties and questions the user may have about online medical consultations.

[0076] The online medical consultation unit can provide a function that allows a user to chat directly with a specialist in a medical department selected by the user. The online medical consultation unit provides, for example, a function that allows a user to chat directly with a specialist in a medical department selected by the user. For example, a user who selects "neurology" can consult with a specialist in that department via chat. Furthermore, by providing a function that allows a user to chat directly with a specialist, the user can resolve any doubts about the medical department. For example, a user who selects "internal medicine" can consult with a specialist in that department via chat. Furthermore, by providing a function that allows a user to chat directly with a specialist in the medical department selected by the user, the user can deepen their understanding of the medical department. For example, a user who selects "dermatology" can consult with a specialist in that department via chat. Thus, by providing a function that allows a user to chat directly with a specialist in the medical department selected by the user, the user can resolve any doubts about the medical department.

[0077] The online medical consultation information unit can use video to explain the procedures and preparations required for a user to receive medical treatment. The online medical consultation information unit, for example, uses video to explain the procedures and preparations required for a user to receive medical treatment. For example, the "flow of online medical treatment" is visually explained using video. Furthermore, by using video, the user can intuitively understand the procedures and preparations required for receiving medical treatment. For example, the "preparation items for online medical treatment" is explained using video. Furthermore, by explaining the procedures and preparations required for receiving medical treatment using video, anxiety about online medical treatment is reduced. For example, the "procedures for online medical treatment" is explained using video, allowing the user to receive medical treatment with peace of mind. In this way, by using video, the user can intuitively understand the procedures and preparations required for receiving medical treatment.

[0078] The subscription promotion unit can propose a customized subscription plan based on the user's health condition and lifestyle habits. The subscription promotion unit proposes, for example, a customized subscription plan based on the user's health condition and lifestyle habits. For example, if the user is a "smoker," the generation AI proposes a subscription plan that includes a "smoking cessation program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, the optimal plan for the user is provided. For example, if the user lives a "desk-based" lifestyle, the generation AI proposes a subscription plan that includes an "exercise program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved. For example, if the user works in a "high-stress environment," the generation AI proposes a subscription plan that includes a "stress management program." In this way, by proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved.

[0079] The subscription promotion unit can refer to the user's past medical history and provide the optimal subscription plan. The subscription promotion unit, for example, refers to the user's past medical history and provides the optimal subscription plan. For example, if there is a history of medical treatment for "headache" in the past, the generation AI proposes a subscription plan that includes a "headache management program." Also, by referring to the past medical history, the optimal subscription plan is provided to the user. For example, if there is a history of medical treatment for "high blood pressure" in the past, the generation AI proposes a subscription plan that includes a "high blood pressure management program." Also, by referring to the past medical history, the generation AI provides a subscription plan that suits the user's health condition. For example, if there is a history of medical treatment for "allergies" in the past, the generation AI proposes a subscription plan that includes an "allergy management program." In this way, by referring to the past medical history, the optimal subscription plan is provided to the user.

[0080] The enrollment promotion unit can use the emotion estimation function to analyze the user's emotions when signing up for the HELPO app and provide a positive message to encourage enrollment. For example, the enrollment promotion unit can use the emotion estimation function to analyze the user's emotions when signing up for the HELPO app and provide a positive message to encourage enrollment. For example, if the user is feeling anxious about signing up, the generation AI displays a message such as, "Don't worry, the HELPO app is used by many users." Furthermore, by providing a positive message according to the user's emotional state, enrollment is encouraged. For example, if the user has doubts about the benefits of signing up, the generation AI explains the advantages of the HELPO app. Furthermore, by using the emotion estimation function, a positive message is provided to alleviate the user's anxieties and doubts. For example, if the user is anxious about the enrollment procedure, the generation AI explains the simple procedure. In this way, the emotion estimation function can be used to analyze the user's emotions when signing up for the HELPO app and provide a positive message to encourage enrollment, thereby encouraging enrollment.

[0081] The enrollment promotion unit can display, in a simulation, specific benefits that the user will gain by joining. The enrollment promotion unit, for example, displays, in a simulation, specific benefits that the user will gain by joining. For example, it visually displays, in a simulation, a "health management plan after joining." Furthermore, by using a simulation, the user can intuitively understand the benefits that the user will gain by joining. For example, it displays, in a simulation, the "effect of medical expenses savings after joining." Furthermore, by displaying, in a simulation, specific benefits that the user will gain by joining, the enrollment is promoted. For example, it displays, in a simulation, the "effect of improved health status after joining." In this way, by using the simulation, the user can intuitively understand the benefits that the user will gain by joining.

[0082] The enrollment promotion unit can display success stories and testimonials of other users. The enrollment promotion unit displays, for example, success stories and testimonials of other users. For example, it displays "testimonials of users who improved their health by using the HELPO app." By displaying success stories and testimonials, users can specifically understand the benefits of enrolling. For example, it displays "success stories of users who saved on medical expenses by using the HELPO app." By displaying success stories and testimonials of other users, enrollment is promoted. For example, it displays "testimonials of users who were able to detect illness early by using the HELPO app." In this way, by displaying success stories and testimonials of other users, enrollment is promoted.

[0083] The subscription promotion unit can use the emotion estimation function to analyze the user's emotions in real time when subscribing to the HELPO app and propose the optimal subscription plan. For example, the subscription promotion unit can use the emotion estimation function to analyze the user's emotions in real time when subscribing to the HELPO app and propose the optimal subscription plan. For example, if the user feels "anxious about subscribing," the generation AI proposes a "reassuring plan." Subscription is also promoted by proposing the optimal subscription plan according to the user's emotional state. For example, if the user has doubts about the "benefits of subscribing," the generation AI proposes a "plan that includes specific benefits." The emotion estimation function can also be used to propose the optimal subscription plan to alleviate the user's concerns and questions. For example, if the user feels anxious about the "subscription procedure," the generation AI proposes a "plan that includes a simple procedure." In this way, the subscription promotion unit can use the emotion estimation function to analyze the user's emotions in real time when subscribing to the HELPO app and propose the optimal subscription plan, thereby promoting subscription.

[0084] The online medical consultation guidance unit can refer to the user's past medical history and present specific advantages of online medical consultation. The online medical consultation guidance unit, for example, refers to the user's past medical history and presents specific advantages of online medical consultation. For example, if there is a history of receiving online medical consultation in the past for "headache," the advantages of that consultation are presented. Furthermore, by referring to the past medical history, specific advantages of online medical consultation are presented to the user. For example, if there is a history of receiving online medical consultation in the past for "high blood pressure," the advantages of that consultation are presented. Furthermore, by referring to the past medical history, the user can specifically understand the advantages of online medical consultation. For example, if there is a history of receiving online medical consultation in the past for "allergies," the advantages of that consultation are presented. In this way, by referring to the past medical history, specific advantages of online medical consultation are presented to the user.

[0085] The online medical consultation information unit can provide customized benefits that take into account the user's lifestyle and environmental information. The online medical consultation information unit provides customized benefits that take into account the user's lifestyle and environmental information, for example. For example, if the user is a "smoker," the generating AI presents benefits including a "smoking cessation program." Furthermore, by taking into account lifestyle and environmental information, the optimal online medical consultation benefits are provided to the user. For example, if the user lives a "desk-based" lifestyle, the generating AI presents benefits including an "exercise program." Furthermore, by providing customized online medical consultation benefits based on the user's lifestyle and environmental information, more effective appeal is achieved. For example, if the user works in a "high-stress environment," the generating AI presents benefits including a "stress management program." In this way, the optimal online medical consultation benefits are provided to the user by taking into account the user's lifestyle and environmental information.

[0086] The online medical consultation guidance unit can use the emotion estimation function to provide positive messages to help users understand the convenience of online medical consultations. For example, if a user is feeling anxious about online medical consultations, the generation AI displays a message such as "Don't worry, online medical consultations are safe." Providing positive messages according to the user's emotional state also helps users understand the convenience of online medical consultations. For example, if a user is anxious about the online medical consultation procedure, the generation AI carefully explains the online medical consultation process. The emotion estimation function also provides positive messages to reduce the user's anxiety and stress. For example, if a user is anxious about the effectiveness of online medical consultations, the generation AI introduces online medical consultation track records and success stories. In this way, the emotion estimation function provides positive messages to help users understand the convenience of online medical consultations, helping them understand the convenience of online medical consultations.

[0087] The online medical consultation information unit can display success stories and testimonials of other users. The online medical consultation information unit displays, for example, success stories and testimonials of other users. For example, it displays "testimonials of users who improved their health by using online medical consultations." Furthermore, by displaying success stories and testimonials, users can concretely understand the convenience of online medical consultations. For example, it displays "success stories of users who were able to save on medical expenses by using online medical consultations." Furthermore, by displaying success stories and testimonials of other users, the convenience of online medical consultations is promoted. For example, it displays "testimonials of users who were able to detect illness early by using online medical consultations." In this way, by displaying success stories and testimonials of other users, the convenience of online medical consultations is promoted.

[0088] The online medical consultation guidance unit can use the emotion estimation function to provide a positive experience that helps users understand the convenience of online medical consultations. For example, if a user feels anxious about online medical consultations, the generation AI displays a message such as, "Don't worry, online medical consultations are safe." Furthermore, by providing a positive experience tailored to the user's emotional state, the unit helps the user understand the convenience of online medical consultations. For example, if a user feels anxious about the online medical consultation procedure, the generation AI carefully explains the online medical consultation process. Furthermore, by using the emotion estimation function, the unit provides a positive experience that helps reduce the user's anxiety and stress. For example, if a user feels anxious about the effectiveness of online medical consultations, the generation AI introduces the results of online medical consultations and success stories. In this way, the emotion estimation function provides a positive experience that helps the user understand the convenience of online medical consultations.

[0089] The subscription promotion unit can propose a customized subscription plan based on the user's health condition and lifestyle habits. The subscription promotion unit proposes, for example, a customized subscription plan based on the user's health condition and lifestyle habits. For example, if the user is a "smoker," the generation AI proposes a subscription plan that includes a "smoking cessation program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, the optimal plan for the user is provided. For example, if the user lives a "desk-based" lifestyle, the generation AI proposes a subscription plan that includes an "exercise program." By proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved. For example, if the user works in a "high-stress environment," the generation AI proposes a subscription plan that includes a "stress management program." In this way, by proposing customized subscription plans based on the user's health condition and lifestyle habits, more effective subscription promotion is achieved.

[0090] The subscription promotion unit can refer to the user's past medical history and provide the optimal subscription plan. The subscription promotion unit, for example, refers to the user's past medical history and provides the optimal subscription plan. For example, if there is a history of medical treatment for "headache" in the past, the generation AI proposes a subscription plan that includes a "headache management program." Also, by referring to the past medical history, the optimal subscription plan is provided to the user. For example, if there is a history of medical treatment for "high blood pressure" in the past, the generation AI proposes a subscription plan that includes a "high blood pressure management program." Also, by referring to the past medical history, the generation AI provides a subscription plan that suits the user's health condition. For example, if there is a history of medical treatment for "allergies" in the past, the generation AI proposes a subscription plan that includes an "allergy management program." In this way, by referring to the past medical history, the optimal subscription plan is provided to the user.

[0091] The enrollment promotion unit can use the emotion estimation function to analyze the user's emotions when signing up for the HELPO app and provide a positive message to encourage enrollment. For example, the enrollment promotion unit can use the emotion estimation function to analyze the user's emotions when signing up for the HELPO app and provide a positive message to encourage enrollment. For example, if the user is feeling anxious about signing up, the generation AI displays a message such as, "Don't worry, the HELPO app is used by many users." Furthermore, by providing a positive message according to the user's emotional state, enrollment is encouraged. For example, if the user has doubts about the benefits of signing up, the generation AI explains the advantages of the HELPO app. Furthermore, by using the emotion estimation function, a positive message is provided to alleviate the user's anxieties and doubts. For example, if the user is anxious about the enrollment procedure, the generation AI explains the simple procedure. In this way, the emotion estimation function can be used to analyze the user's emotions when signing up for the HELPO app and provide a positive message to encourage enrollment, thereby encouraging enrollment.

[0092] The enrollment promotion unit can display, in a simulation, specific benefits that the user will gain by joining. The enrollment promotion unit, for example, displays, in a simulation, specific benefits that the user will gain by joining. For example, it visually displays, in a simulation, a "health management plan after joining." Furthermore, by using a simulation, the user can intuitively understand the benefits that the user will gain by joining. For example, it displays, in a simulation, the "effect of medical expenses savings after joining." Furthermore, by displaying, in a simulation, specific benefits that the user will gain by joining, the enrollment is promoted. For example, it displays, in a simulation, the "effect of improved health status after joining." In this way, by using the simulation, the user can intuitively understand the benefits that the user will gain by joining.

[0093] The enrollment promotion unit can display success stories and testimonials of other users. The enrollment promotion unit displays, for example, success stories and testimonials of other users. For example, it displays "testimonials of users who improved their health by using the HELPO app." By displaying success stories and testimonials, users can specifically understand the benefits of enrolling. For example, it displays "success stories of users who saved on medical expenses by using the HELPO app." By displaying success stories and testimonials of other users, enrollment is promoted. For example, it displays "testimonials of users who were able to detect illness early by using the HELPO app." In this way, by displaying success stories and testimonials of other users, enrollment is promoted.

[0094] The subscription promotion unit can use the emotion estimation function to analyze the user's emotions in real time when subscribing to the HELPO app and propose the optimal subscription plan. For example, the subscription promotion unit can use the emotion estimation function to analyze the user's emotions in real time when subscribing to the HELPO app and propose the optimal subscription plan. For example, if the user feels "anxious about subscribing," the generation AI proposes a "reassuring plan." Subscription is also promoted by proposing the optimal subscription plan according to the user's emotional state. For example, if the user has doubts about the "benefits of subscribing," the generation AI proposes a "plan that includes specific benefits." The emotion estimation function can also be used to propose the optimal subscription plan to alleviate the user's concerns and questions. For example, if the user feels anxious about the "subscription procedure," the generation AI proposes a "plan that includes a simple procedure." In this way, the subscription promotion unit can use the emotion estimation function to analyze the user's emotions in real time when subscribing to the HELPO app and propose the optimal subscription plan, thereby promoting subscription.

[0095] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0096] The symptom input unit can be equipped with a function to evaluate the severity of symptoms when the user inputs them. For example, if the user inputs "persistent headache," the generation AI will evaluate the severity of the symptom and provide an evaluation such as "mild headache" or "severe headache." It can also suggest an appropriate medical specialty depending on the severity of the symptom. For example, for a "mild headache," it would suggest "internal medicine," and for a "severe headache," it would suggest "neurology." Furthermore, by evaluating the severity of symptoms, the user can understand the seriousness of their symptoms and take appropriate measures. For example, for "mild abdominal pain," it would suggest "rest at home," and for "severe abdominal pain," it would suggest "visit an emergency room." This allows the user to understand the seriousness of their symptoms and take appropriate measures.

[0097] The medical department suggestion unit can suggest the need for vaccinations or health checkups based on the symptoms entered by the user. For example, if a user enters "persistent cough," the generation AI will suggest "influenza vaccination." It can also suggest appropriate health checkups based on the user's age and gender. For example, it will suggest "regular health checkups" for users over 40 years old. By suggesting vaccinations and health checkups, users can also learn specific methods for maintaining their own health. For example, it will suggest "blood pressure measurement" for a user diagnosed with "high blood pressure risk." In this way, by suggesting vaccinations and health checkups, users can learn specific methods for maintaining their own health.

[0098] The online medical consultation information unit can provide a function to shorten the waiting time when a user receives medical treatment. For example, when a user makes an appointment for online medical treatment, the waiting time for the consultation is displayed in real time. In addition, it can prioritize suggestions for medical departments with short waiting times. For example, if the waiting time for "internal medicine" is short, the generation AI will prioritize suggesting "internal medicine." In addition, by providing a function to shorten waiting times, users can receive medical treatment smoothly. For example, it can suggest avoiding times when medical appointments are crowded. In this way, by providing a function to shorten waiting times, users can receive medical treatment smoothly.

[0099] The enrollment promotion unit can display, in a simulation, the specific benefits that the user will gain by enrolling. For example, a "health management plan after enrollment" is visually displayed in a simulation. Furthermore, by using a simulation, the user can intuitively understand the benefits that the user will gain by enrolling. For example, a simulation of the "effect of medical expenses savings after enrollment" is displayed. Furthermore, enrollment is promoted by displaying, in a simulation, the specific benefits that the user will gain by enrolling. For example, a simulation of the "effect of improved health status after enrollment." In this way, by using a simulation, the user can intuitively understand the benefits that the user will gain by enrolling.

[0100] The medical department suggestion unit can display the latest research papers and news articles related to the medical department suggested by the generation AI. For example, if "neurology" is suggested, the latest research papers and news articles related to that medical department will be displayed. In addition, by displaying the latest research papers and news articles, the user can obtain the latest information on the medical department. For example, if "internal medicine" is suggested, the latest research papers and news articles related to that medical department will be displayed. In addition, by providing the latest information related to the medical department suggested by the generation AI, the user can deepen their understanding of the medical department. For example, if "dermatology" is suggested, the latest research papers and news articles related to that medical department will be displayed. In this way, by displaying the latest research papers and news articles related to the medical department suggested by the generation AI, the user can obtain the latest information on the medical department.

[0101] The symptom input unit can use the emotion estimation function to analyze the user's emotions when entering symptoms and provide advice to reduce stress and anxiety. For example, when a user enters symptoms into the app, the emotion estimation function can be used to analyze the user's emotions and provide advice to reduce stress and anxiety. For example, if the user enters "I've been having trouble sleeping lately and I'm feeling anxious," the generation AI can suggest "ways to relax." The emotion estimation function can also be used to provide advice based on the user's emotional state. For example, if the user enters "I've been having trouble sleeping lately and I'm feeling irritated," the generation AI can suggest "music to help me relax." The emotion estimation function can also be used to provide specific advice to reduce the user's stress and anxiety. For example, if the user enters "I have a stomachache because of work stress," the generation AI can suggest "ways to manage stress." In this way, advice based on the user's emotional state can be provided to reduce stress and anxiety.

[0102] The medical department suggestion unit uses the emotion estimation function to suggest a medical department based on the user's emotions, providing a sense of security. For example, if the user enters "I'm worried because I have a persistent headache," the generation AI will suggest "neurology" and display a message such as "Don't worry, this is the right department for you." Furthermore, by suggesting a medical department based on the user's emotional state, the user can feel at ease when visiting a doctor. For example, if the user enters "I'm worried because I have persistent stomach pain," the generation AI will suggest "internal medicine" and display a message such as "Don't worry, this is the right department for you." Furthermore, by using the emotion estimation function, the unit can suggest a medical department to reduce the user's anxiety and stress. For example, if the user enters "I'm worried because my cough won't stop," the generation AI will suggest "respiratory medicine" and display a message such as "Don't worry, this is the right department for you." This allows the system to suggest a medical department based on the user's emotional state, providing a sense of security when visiting a doctor.

[0103] The enrollment promotion unit uses the emotion estimation function to analyze the user's emotions when signing up for the HELPO app and can provide positive messages to encourage enrollment. For example, if the user is feeling anxious about signing up, the generation AI displays a message such as, "Don't worry, the HELPO app is used by many users." Enrollment is also promoted by providing positive messages that correspond to the user's emotional state. For example, if the user has doubts about the benefits of signing up, the generation AI explains the advantages of the HELPO app. The emotion estimation function also provides positive messages to alleviate the user's anxieties and doubts. For example, if the user is anxious about the enrollment procedure, the generation AI explains the simple procedure. In this way, the emotion estimation function can be used to analyze the user's emotions when signing up for the HELPO app and provide positive messages to encourage enrollment, thereby promoting enrollment.

[0104] The online medical consultation information unit can use the emotion estimation function to provide information to alleviate any anxieties or questions the user may have about online medical consultations. For example, if the user is "anxious about online medical consultations," the generation AI will explain the "benefits of online medical consultations" and "safety." Furthermore, by providing information tailored to the user's emotional state, the generation AI can alleviate any anxieties or questions about online medical consultations. For example, if the user has questions about the "procedures for online medical consultations," the generation AI will explain the "flow of online medical consultations." Furthermore, by using the emotion estimation function, the generation AI can provide specific information to alleviate the user's anxieties or questions. For example, if the user is anxious about the "effectiveness of online medical consultations," the generation AI will explain the "track record of online medical consultations" and "success stories." In this way, the emotion estimation function can be used to provide information to alleviate any anxieties or questions the user may have about online medical consultations, thereby alleviating any anxieties or questions the user may have about online medical consultations.

[0105] The symptom input unit can use the emotion estimation function to analyze the emotions associated with the symptoms entered by the user in real time and provide positive feedback. For example, when a user enters symptoms into the app, the emotion estimation function can be used to analyze the emotions associated with the symptoms in real time and provide positive feedback. For example, if a user enters "I'm worried because I've had a persistent headache," the generation AI will display a message such as "Don't worry, we'll suggest an appropriate medical specialist." The emotion estimation function also provides positive feedback tailored to the user's emotional state. For example, if a user enters "I've been having trouble sleeping lately and I'm feeling irritated," the generation AI will display a message such as "We'll suggest ways to relax." The emotion estimation function also provides positive feedback to reduce the user's anxiety and stress. For example, if a user enters "I have a stomachache due to work stress," the generation AI will display a message such as "We'll suggest ways to manage stress." By providing positive feedback tailored to the user's emotional state, the system reduces the user's anxiety and stress.

[0106] The processing flow of the second embodiment will be briefly explained below.

[0107] Step 1: The symptom input unit allows the user to input their symptoms. For example, the user inputs symptoms into the app as text. The symptom input unit can also input symptoms using voice input. For example, if the user inputs "I have a persistent headache," the generation AI analyzes the voice data and suggests an appropriate medical department. Step 2: The medical department suggestion unit analyzes the symptoms entered by the symptom input unit and suggests an appropriate medical department. For example, the generation AI might suggest "neurology" or "internal medicine." The medical department suggestion unit can also refer to past medical history to suggest a more accurate medical department. For example, if there is a history of a patient visiting a "neurology" department for a "headache," it will again suggest "neurology." Step 3: The online medical consultation guidance unit provides online medical consultation guidance based on the medical department proposed by the medical department suggestion unit. For example, it displays a message such as "You can continue with the online medical consultation and receive a prescription for medication." The online medical consultation guidance unit can also refer to the user's past online medical consultation history to suggest the optimal medical treatment plan. For example, if the user has previously received online medical consultation for "headache," it will again suggest online medical consultation with "neurology." Step 4: The subscription promotion unit promotes the use of online medical consultations recommended by the online medical consultation information unit. For example, it displays a message such as, "By subscribing to the HELPO app, you can receive online medical consultations." The subscription promotion unit can also suggest customized subscription plans based on the user's health condition and lifestyle habits. For example, if the user is a "smoker," the generation AI would suggest a subscription plan that includes a "smoking cessation program."

[0108] 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.

[0109] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0110] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0111] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0112] 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.

[0113] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0114] 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.

[0115] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0116] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0121] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0122] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0123] 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.

[0124] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0125] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0126] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0127] 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.

[0128] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0129] 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.

[0130] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0131] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0136] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0137] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0138] 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.

[0139] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0140] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0141] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0142] 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.

[0143] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0144] 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.

[0145] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0146] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0147] 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.

[0148] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the 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.

[0149] 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.

[0150] 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.

[0151] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0152] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0153] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0154] 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.

[0155] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0156] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0157] 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.

[0158] FIG. 9 illustrates 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 behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0159] 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.

[0160] 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).

[0161] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, 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 expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0162] 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."

[0163] 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.

[0164] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0169] The hardware resource that executes the specific process 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 process may be a single processor.

[0170] 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.

[0171] 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.

[0172] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0173] 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.

[0174] 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. [Explanation of symbols]

[0175] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A system comprising: a symptom input unit in which a user inputs their own symptoms; a medical department suggestion unit that analyzes the symptoms input by the symptom input unit and suggests an appropriate medical department; an online medical consultation guidance unit that provides information about online medical consultations based on the medical department suggested by the medical department suggestion unit; and a subscription promotion unit that promotes the use of the online medical consultations recommended by the online medical consultation guidance unit.

2. The symptom input unit A function has been added that allows users to upload images and videos, and the generative AI analyzes the visual information to suggest the medical department.

2. The system of claim 1.

3. The medical department suggestion unit In addition to the medical department suggested by the generative AI, health information and preventive measures related to the symptoms are provided.

2. The system of claim 1.

4. The online medical consultation information unit Refer to the user's past online medical history and propose the most suitable medical plan 2. The system of claim 1.

5. The subscription promotion department Propose customized subscription plans based on the user's health status and lifestyle habits 2. The system of claim 1.

6. The symptom input unit Analyzing the user's emotions when typing and providing advice to reduce stress and anxiety 2. The system of claim 1.

7. The medical department suggestion unit Proposing the medical department according to the user's feelings, and providing a sense of security 2. The system of claim 1.

8. The online medical consultation information unit Providing information to alleviate any concerns or questions the user may have about the online medical consultation 2. The system of claim 1.

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