system

Abstract

An object of the system according to the embodiment is to quickly and appropriately deal with simple cases such as skin inflammation and insect bites.SOLUTION: A system according to an embodiment includes an image acquiring unit, a generation and AI unit, a guiding unit, and a guiding unit. The image acquisition unit acquires an image of an affected part from a user. The generation and AI unit analyzes the image of the affected part acquired by the image acquiring unit. The guidance unit guides the user on the cause of the case analyzed by the generation and AI unit and the coping method. The guiding unit guides the user to the EC sales site of the prescription drug or the online medical care based on the coping method guided by the guiding 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 techniques have had the problem of making it difficult to quickly and appropriately treat minor cases such as skin inflammation and insect bites.

[0005] The system according to the embodiment aims to quickly and appropriately treat minor cases such as skin irritation and insect bites. [Means for solving the problem]

[0006] The system according to the embodiment includes an image acquisition unit, a generation AI unit, a guidance unit, and a guiding unit. The image acquisition unit acquires an image of the affected area from the user. The generation AI unit analyzes the image of the affected area acquired by the image acquisition unit. The guiding unit informs the user of the cause and treatment of the case analyzed by the generation AI unit. The guiding unit guides the user to an e-commerce site for prescription drugs or online medical consultation based on the treatment provided by the guidance unit. [Effects of the Invention]

[0007] The system according to the embodiment can quickly and appropriately treat simple cases such as skin irritation and insect bites. [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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[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 system according to the embodiment of the present invention uses generative AI to quickly identify simple cases such as skin irritation and insect bites, and recommend appropriate treatments. This allows the system to provide consistent service to users and quickly recommend appropriate treatments.

[0029] The system according to the embodiment includes an image acquisition unit, a generation AI unit, a guidance unit, and a guidance unit. The image acquisition unit acquires images of the affected area from a user. For example, the user may upload images taken with a smartphone. The image acquisition unit can also acquire images in real time using a webcam. The image acquisition unit can also acquire images from an existing image database. The generation AI unit analyzes the images of the affected area acquired by the image acquisition unit. For example, the generation AI unit may analyze the images using deep learning to identify the cause of the condition. The generation AI unit can also analyze the images using a convolutional neural network (CNN) to determine a treatment. The generation AI unit can also extract image features and identify patterns of the condition. The guidance unit guides the user to the cause and treatment of the condition analyzed by the generation AI unit. For example, the guidance unit may present specific treatment methods, such as, "This is a skin inflammation, and cooling and the use of anti-inflammatory medication are recommended." The guidance unit can also explain the treatment steps to the user. Furthermore, the guidance unit can provide video tutorials or infographics on treatment methods. The guidance unit guides the user to an online prescription drug sales site or online medical consultation based on the treatment methods provided by the guidance unit. For example, the guidance unit can easily enable the user to purchase prescription drugs by displaying a message such as, "You need an antihistamine. You can purchase it from this link." The guidance unit can also guide the user to online medical consultations by displaying a message such as, "If you need further explanation, please receive an online medical consultation from this link." Furthermore, the guidance unit can suggest the most appropriate prescription drug or specialist by referring to the user's past purchase history and medical history. This allows the system according to the embodiment to provide consistent services to users and guide them to prompt and appropriate treatment methods. For example, the system allows users to quickly treat conditions such as skin irritations and insect bites. Furthermore, the user can easily purchase the necessary prescription drug and receive a diagnosis from a specialist. This improves user convenience and allows them to treat their condition with peace of mind.

[0030] The generation AI unit can make more accurate judgments by referencing the user's past medical history and allergy information. For example, the generation AI unit retrieves the user's past medical history from a database and makes judgments taking allergy information and previous illnesses into consideration. For example, if a user has previously been diagnosed with allergic dermatitis, the generation AI unit will highly evaluate the possibility of an allergy based on that information. In addition, when a user uploads an image, the generation AI unit provides a form for entering past medical history and allergy information and uses that information for analysis. For example, by entering allergy information, the generation AI unit makes judgments taking into account the possibility of an allergic reaction. The generation AI unit also references the user's past medical history and allergy information in real time and reflects this in the judgment results. For example, if a user has had an allergic reaction to a specific medication in the past, the generation AI unit will advise them to avoid that medication. This enables more accurate judgments by taking into account the user's past medical history and allergy information.

[0031] The generation AI unit can integrate and analyze multiple images taken under different lighting conditions and angles to enable more accurate diagnoses. For example, the generation AI unit allows users to upload multiple images taken under different lighting conditions and angles, and integrates and analyzes those images. For example, integrating and analyzing images taken during the day and at night can enable more accurate diagnoses. The generation AI unit can also analyze multiple images taken from different angles and generate a 3D model to grasp the detailed condition of the affected area. For example, analyzing the three-dimensional shape and depth of the affected area can enable more accurate diagnoses. Furthermore, when users upload images taken under different lighting conditions and angles, the generation AI unit automatically corrects, integrates, and analyzes the images. For example, it corrects for light reflections and shadows to enable more accurate diagnoses. This allows for more accurate diagnoses by integrating multiple images taken under different lighting conditions and angles.

[0032] The generation AI unit adds a function that allows users to describe their symptoms using voice input, and can acquire information from both images and voice. For example, when a user uploads an image of an affected area, the generation AI unit provides a function for describing symptoms using voice input and uses the voice information for analysis. For example, if a user describes "it's itchy" by voice, the generation AI unit takes that information into consideration when making a judgment. The generation AI unit also analyzes the voice input, acquires details of the symptoms described by the user as text data, and integrates this with image analysis to make a judgment. For example, if a user describes "the redness is spreading," the generation AI unit takes that information into consideration when making a judgment. The generation AI unit also provides a function for users to describe symptoms using voice input when uploading an image of an affected area, and analyzes the voice information in real time to make a judgment. For example, if a user describes "it's painful," the generation AI unit takes that information into consideration when making a judgment. This allows users to describe their symptoms using voice input and acquire more detailed information, enabling more accurate judgments.

[0033] The generation AI unit can provide customized advice based on the user's age and gender when outputting the analysis results. For example, when outputting the results of analyzing an image of an affected area, the generation AI unit provides customized advice based on the user's age and gender. For example, in the case of a child, advice for parents is included. The generation AI unit also provides a form for the user to enter their age and gender when uploading an image, and provides customized advice based on that information. For example, in the case of elderly people, precautions regarding the use of certain medications are included. The generation AI unit also builds a system that provides customized advice based on the user's age and gender when outputting the analysis results. For example, in the case of women, advice regarding specific hormone balances is included. This allows for customized advice based on the user's age and gender, leading to more appropriate treatment methods.

[0034] The guidance unit can provide individually optimized solutions by taking into account the user's lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. For example, when the generation AI provides guidance on the cause of a case and how to deal with it, the guidance unit provides a form for the user to enter lifestyle and environmental information and provides individually optimized solutions based on that information. For example, if the user is a smoker, the guidance unit recommends that the user quit smoking. The guidance unit also builds a system that provides individually optimized solutions by taking into account lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. For example, if the user has allergies, the guidance unit provides advice on avoiding allergens. The guidance unit also acquires the user's lifestyle and environmental information in real time when the generation AI provides guidance on the cause of a case and how to deal with it, and provides individually optimized solutions based on that information. For example, if the user has a pet, the guidance unit provides advice on pet allergies. This allows individually optimized solutions to be provided by taking into account the user's lifestyle and environmental information.

[0035] When providing solutions, the guidance unit can refer to past user feedback and prioritize presenting solutions that were highly effective. For example, when the generation AI provides solutions, the guidance unit retrieves past user feedback from a database and prioritizes presenting solutions that were highly effective. For example, the guidance unit recommends solutions that many users have found effective. Furthermore, the guidance unit builds a system that, when providing solutions to users, refers to past feedback and prioritizes presenting solutions that were highly effective. For example, solutions that have received high user ratings are displayed preferentially. Furthermore, when the generation AI provides solutions, the guidance unit refers to past user feedback in real time and prioritizes presenting solutions that were highly effective. For example, the guidance unit creates a ranking of solutions based on user feedback and recommends the top solutions. In this way, by referring to past user feedback, it is possible to prioritize presenting solutions that were highly effective.

[0036] The guidance unit can provide guidance on countermeasures in a visually easy-to-understand format using video tutorials and infographics. For example, when the generation AI provides guidance on countermeasures, the guidance unit provides video tutorials so that the user can learn the countermeasures in a visually easy-to-understand format. For example, it uses videos to explain how to apply medicine and how to cool the area. The guidance unit also builds a system that provides guidance on countermeasures to the user in a visually easy-to-understand format using infographics. For example, it shows the steps of the countermeasures in diagrams. The guidance unit also builds a system that provides guidance on countermeasures to the user in a visually easy-to-understand format using video tutorials and infographics. For example, it explains the steps of the countermeasures using videos and diagrams. In this way, by using video tutorials and infographics, the countermeasures can be provided in a visually easy-to-understand format.

[0037] When the guidance unit provides guidance on a countermeasure, it can add a reminder function for the user to execute the countermeasure and notify the user at the appropriate time. For example, when the generation AI provides guidance on a countermeasure, the guidance unit provides a reminder function for the user to execute the countermeasure and notifies the user at the appropriate time. For example, it notifies the user when to take medicine or when to apply ice. The guidance unit also adds a reminder function for the user to execute the countermeasure, building a system in which the generation AI notifies the user at the appropriate time. For example, it sends a reminder at a time set by the user. The guidance unit also uses the reminder function to notify the user when to execute the countermeasure when the generation AI provides guidance on a countermeasure. For example, it notifies the user when to apply ice or medicine. In this way, by adding the reminder function, the user can execute the countermeasure at the appropriate time.

[0038] The guidance unit can suggest the most appropriate prescription drug based on the solution determined by the generation AI and by referring to the user's past purchase history. For example, the guidance unit retrieves the user's past purchase history from a database and suggests the most appropriate prescription drug based on the solution determined by the generation AI. For example, the suggestion takes into account the effects of drugs purchased in the past. The guidance unit also builds a system that suggests the most appropriate prescription drug by referring to the user's past purchase history when guiding the user to a solution. For example, it prioritizes suggesting drugs that have been effective in the past. The guidance unit also suggests the most appropriate prescription drug by referring to the user's past purchase history in real time based on the solution determined by the generation AI. For example, it suggests avoiding drugs that have caused allergic reactions in the past. In this way, the most appropriate prescription drug can be suggested by referring to the user's past purchase history.

[0039] The guidance unit can select safe medications by taking into account the user's allergy information and drug interactions when the generation AI suggests prescription medications. For example, when the generation AI suggests prescription medications, the guidance unit retrieves the user's allergy information from a database and selects safe medications to avoid allergic reactions. For example, if the user is allergic to a specific ingredient, the guidance unit will suggest medications that do not contain that ingredient. The guidance unit also builds a system that selects safe medications by taking into account drug interactions when suggesting prescription medications to the user. For example, it checks for interactions with medications currently being taken and suggests safe medications. The guidance unit also selects safe medications by taking into account the user's allergy information and drug interactions in real time when the generation AI suggests prescription medications. For example, it filters the list of medications based on allergy information and suggests safe medications. This allows safe medications to be selected by taking into account the user's allergy information and drug interactions.

[0040] The guidance unit can provide coupons and discount information for the user to purchase the medicine when the generation AI suggests a prescription drug. For example, the guidance unit provides coupons and discount information for the user to purchase the medicine when the generation AI suggests a prescription drug. For example, it displays discount coupons for specific drugs. The guidance unit also builds a system that provides coupons and discount information when the user purchases prescription drugs. For example, it displays applicable discount information based on purchase history. The guidance unit also provides coupons and discount information for the user to purchase the medicine in real time when the generation AI suggests a prescription drug. For example, it displays discount information that is applicable during a specific campaign period. In this way, by providing coupons and discount information for the user to purchase the medicine, it is possible to increase the user's motivation to purchase.

[0041] The guidance unit can suggest subscription services for the user to purchase medications when the generation AI suggests prescription medications. For example, when the generation AI suggests prescription medications, the guidance unit suggests subscription services for the user to purchase medications on a regular basis. For example, it provides a service that delivers medications on a regular monthly basis. The guidance unit also builds a system that suggests subscription services when the user purchases prescription medications. For example, it displays the benefits of regular purchases and discount information. The guidance unit also suggests subscription services for the user to purchase medications in real time when the generation AI suggests prescription medications. For example, it suggests the optimal subscription plan based on the user's purchase history. This makes it possible to increase user convenience by suggesting subscription services for the user to purchase medications on a regular basis.

[0042] When the generation AI suggests an online medical consultation, the guidance unit can recommend the most appropriate specialist by referring to the user's past medical history. For example, when the generation AI suggests an online medical consultation, the guidance unit retrieves the user's past medical history from a database and recommends the most appropriate specialist. For example, a dermatologist is recommended for a user who has previously received dermatology treatment. The guidance unit also builds a system that, when a user receives an online medical consultation, refers to the user's past medical history and recommends the most appropriate specialist. For example, a specialist is recommended based on the content of the past medical treatment. Furthermore, when the generation AI suggests an online medical consultation, the guidance unit refers to the user's past medical history in real time and recommends the most appropriate specialist. For example, a specialist who is familiar with that symptom is recommended for a user who has previously received treatment for a specific symptom. In this way, the most appropriate specialist can be recommended by referring to the user's past medical history.

[0043] The guidance unit can automatically schedule the optimal consultation time for the user's symptoms when the generation AI suggests online medical consultation. For example, when the generation AI suggests online medical consultation, the guidance unit automatically schedules the optimal consultation time for the user's symptoms. For example, in the case of acute symptoms, the schedule is adjusted so that the user can receive medical treatment as soon as possible. The guidance unit also builds a system that automatically schedules the optimal consultation time for the user's symptoms when the user receives online medical consultation. For example, the guidance unit adjusts the consultation time to suit the user's convenience. The guidance unit also schedules the optimal consultation time for the user's symptoms in real time when the generation AI suggests online medical consultation. For example, the guidance unit adjusts the consultation time according to the urgency of the symptoms. This enables prompt medical treatment by automatically scheduling the optimal consultation time for the user's symptoms.

[0044] The guidance unit can provide the user with a preparation guide for receiving medical treatment when the generation AI suggests online medical treatment. For example, the guidance unit provides the user with a preparation guide for receiving medical treatment when the generation AI suggests online medical treatment. For example, it lists the documents and information required before the medical treatment and notifies the user. The guidance unit also builds a system that provides a preparation guide when the user receives online medical treatment. For example, it displays the preparation items required before the medical treatment in checklist format. The guidance unit also provides the user with a preparation guide for receiving medical treatment in real time when the generation AI suggests online medical treatment. For example, it provides step-by-step guidance on the information and procedures required before the medical treatment. In this way, by providing the user with a preparation guide for receiving medical treatment, they can smoothly prepare for the medical treatment.

[0045] The guidance unit can automatically collect documents and information necessary for the user to receive medical treatment when the generation AI suggests online medical treatment. For example, the guidance unit automatically collects documents and information necessary for the user to receive medical treatment when the generation AI suggests online medical treatment. For example, it obtains past medical records and allergy information from a database. The guidance unit also builds a system that automatically collects documents and information necessary when the user receives online medical treatment. For example, it obtains necessary information from a medical institution with the user's consent. The guidance unit also collects documents and information necessary for the user to receive medical treatment in real time when the generation AI suggests online medical treatment. For example, it automatically generates necessary documents based on information entered by the user. This allows the user to smoothly prepare for medical treatment by automatically collecting necessary documents and information necessary for receiving medical treatment.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] The generation AI unit can make more accurate judgments by referencing the user's past medical history and allergy information. For example, it can retrieve the user's past medical history from a database and make judgments taking into account allergy information and previous illnesses. For a user who has previously been diagnosed with allergic dermatitis, the generation AI unit can highly evaluate the possibility of an allergy based on that information. In addition, when the user uploads an image, the generation AI unit provides a form for entering past medical history and allergy information, and uses that information for analysis. By entering allergy information, the generation AI unit makes judgments taking into account the possibility of an allergic reaction. Furthermore, the generation AI unit references the user's past medical history and allergy information in real time and reflects this in the judgment results. For users who have had an allergic reaction to a specific medication in the past, it can advise them to avoid that medication. This allows for more accurate judgments by taking into account the user's past medical history and allergy information.

[0048] The generative AI unit can integrate and analyze multiple images taken under different lighting conditions and angles to enable more accurate diagnoses. For example, users can upload multiple images taken under different lighting conditions and angles, and these images are integrated and analyzed. Integrating and analyzing images taken during the day and at night enables more accurate diagnoses. The generative AI unit also analyzes multiple images taken from different angles to generate a 3D model to grasp the detailed condition of the affected area. Analyzing the three-dimensional shape and depth of the affected area enables more accurate diagnoses. Furthermore, when users upload images taken under different lighting conditions and angles, the generative AI unit automatically corrects, integrates, and analyzes the images. Light reflections and shadows are corrected to enable more accurate diagnoses. This allows for more accurate diagnoses by integrating multiple images taken under different lighting conditions and angles.

[0049] The generation AI unit adds a function that allows users to describe their symptoms using voice input, and can obtain information from both images and voice. For example, when a user uploads an image of an affected area, a function is provided to describe symptoms using voice input, and the voice information is used for analysis. When a user describes "it's itchy" in voice, the generation AI unit takes that information into account when making a judgment. The generation AI unit also analyzes the voice input, obtains the details of the symptoms described by the user as text data, and integrates this with image analysis to make a judgment. When a user describes "the redness is spreading," the generation AI unit takes that information into account when making a judgment. Furthermore, when a user uploads an image of an affected area, the generation AI unit provides a function to describe symptoms using voice input, and analyzes the voice information in real time to make a judgment. When a user describes "it's painful," the generation AI unit takes that information into account when making a judgment. This allows users to describe their symptoms using voice input, obtaining more detailed information and enabling more accurate judgments.

[0050] When outputting the analysis results, the generation AI unit can provide customized advice based on the user's age and gender. For example, when outputting the results of analyzing an image of an affected area, it provides customized advice based on the user's age and gender. In the case of children, advice for parents is included. In addition, when the user uploads an image, the generation AI unit provides a form for entering age and gender, and provides customized advice based on that information. In the case of elderly people, precautions regarding the use of specific medications are included. Furthermore, the generation AI unit builds a system that provides customized advice based on the user's age and gender when outputting the analysis results. In the case of women, advice regarding specific hormone balances is included. This allows for customized advice based on the user's age and gender, leading to more appropriate treatment methods.

[0051] The guidance unit can provide individually optimized solutions by taking into account the user's lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. For example, when the generation AI provides guidance on the cause of a case and how to deal with it, it provides a form for the user to enter lifestyle and environmental information, and provides individually optimized solutions based on that information. If the user is a smoker, it recommends that the user quit smoking. Furthermore, the guidance unit builds a system that provides individually optimized solutions by taking into account lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. If the user has allergies, it provides advice on avoiding allergens. Furthermore, when the generation AI provides guidance on the cause of a case and how to deal with it, the guidance unit obtains the user's lifestyle and environmental information in real time and provides individually optimized solutions based on that information. If the user has a pet, it provides advice on pet allergies. This allows individually optimized solutions to be provided by taking into account the user's lifestyle and environmental information.

[0052] When providing solutions, the guidance unit can refer to past user feedback and prioritize presenting solutions that were highly effective. For example, when the generation AI provides solutions, it retrieves past user feedback from a database and prioritizes presenting solutions that were highly effective. Solutions that many users have found effective are recommended. In addition, the guidance unit builds a system that, when providing solutions to users, refers to past feedback and prioritizes presenting solutions that were highly effective. Solutions that have received high user ratings are displayed preferentially. Furthermore, when the generation AI provides solutions, the guidance unit refers to past user feedback in real time and prioritizes presenting solutions that were highly effective. A ranking of solutions is created based on user feedback, and the top solutions are recommended. In this way, by referring to past user feedback, it is possible to prioritize presenting solutions that were highly effective.

[0053] When guiding users on how to deal with the problem, the guidance unit can use video tutorials or infographics to provide guidance that is visually easy to understand. For example, when the generation AI provides guidance on how to deal with the problem, it can provide a video tutorial so that the user can learn the method in a visually easy-to-understand manner. Videos can be used to explain how to apply medicine and how to cool the area. In addition, the guidance unit can build a system that uses infographics to provide guidance on how to deal with the problem to the user in a visually easy-to-understand manner. The steps of the method are illustrated. Furthermore, when the generation AI provides guidance on how to deal with the problem, the guidance unit can use video tutorials or infographics to provide guidance that is visually easy to understand. The steps of the method are explained using videos or diagrams. In this way, by using video tutorials or infographics, the method can be provided in a visually easy-to-understand manner.

[0054] When guiding a countermeasure, the guidance unit can add a reminder function for the user to execute the countermeasure and notify the user at the appropriate time. For example, when the generation AI is guiding a countermeasure, it can provide a reminder function for the user to execute the countermeasure and notify the user at the appropriate time. It notifies the user when to take medicine or when to cool the area. Furthermore, the guidance unit adds a reminder function for the user to execute the countermeasure, and a system is constructed in which the generation AI notifies the user at the appropriate time. It sends reminders at times set by the user. Furthermore, when the generation AI is guiding a countermeasure, the guidance unit uses the reminder function to notify the user when to execute the countermeasure. It notifies the user when to cool the area or when to apply medicine. In this way, by adding the reminder function, the user can execute the countermeasure at the appropriate time.

[0055] The guidance unit can suggest the most appropriate prescription drug based on the solution determined by the generation AI and by referring to the user's past purchase history. For example, based on the solution determined by the generation AI, the guidance unit retrieves the user's past purchase history from a database and suggests the most appropriate prescription drug. The suggestions are made taking into account the effects of drugs purchased in the past. The guidance unit also builds a system that suggests the most appropriate prescription drug by referring to the user's past purchase history when guiding the user to a solution. Drugs that have been effective in the past are given priority in suggesting the most appropriate prescription drug. Furthermore, the guidance unit suggests the most appropriate prescription drug by referring to the user's past purchase history in real time based on the solution determined by the generation AI. It suggests avoiding drugs that have caused allergic reactions in the past. In this way, the guidance unit can suggest the most appropriate prescription drug by referring to the user's past purchase history.

[0056] The guidance unit takes into account the user's allergy information and drug interactions when the generation AI suggests prescription drugs, allowing it to select safe drugs. For example, when the generation AI suggests prescription drugs, it retrieves the user's allergy information from a database and selects safe drugs to avoid allergic reactions. If the user is allergic to a specific ingredient, it will suggest drugs that do not contain that ingredient. The guidance unit also builds a system that takes drug interactions into consideration when suggesting prescription drugs to the user and selects safe drugs. It checks interactions with drugs currently being taken and suggests safe drugs. Furthermore, when the generation AI suggests prescription drugs, the guidance unit takes into account the user's allergy information and drug interactions in real time to select safe drugs. It filters the drug list based on allergy information and suggests safe drugs. This allows safe drugs to be selected by taking the user's allergy information and drug interactions into consideration.

[0057] The guidance unit can provide coupons and discount information for users to purchase drugs when the generation AI suggests prescription drugs. For example, when the generation AI suggests prescription drugs, it provides coupons and discount information for users to purchase drugs. Discount coupons for specific drugs are displayed. The guidance unit also builds a system that provides coupons and discount information when users purchase prescription drugs. It displays applicable discount information based on purchase history. Furthermore, when the generation AI suggests prescription drugs, the guidance unit provides coupons and discount information for users to purchase drugs in real time. It displays discount information that is applicable during a specific campaign period. In this way, by providing coupons and discount information for users to purchase drugs, it is possible to increase users' motivation to purchase.

[0058] When the generation AI suggests prescription drugs, the guidance unit can suggest a subscription service for the user to purchase the drugs. For example, when the generation AI suggests prescription drugs, it suggests a subscription service for the user to purchase drugs on a regular basis. It provides a service that delivers drugs on a regular monthly basis. The guidance unit also builds a system that suggests subscription services when the user purchases prescription drugs. It displays the benefits of regular purchases and discount information. Furthermore, when the generation AI suggests prescription drugs, the guidance unit suggests subscription services for the user to purchase drugs in real time. It suggests the optimal subscription plan based on the user's purchase history. This increases user convenience by suggesting subscription services for the user to purchase drugs on a regular basis.

[0059] When the generating AI suggests an online medical consultation, the guidance unit can recommend the most appropriate specialist by referring to the user's past medical history. For example, when the generating AI suggests an online medical consultation, it retrieves the user's past medical history from a database and recommends the most appropriate specialist. For a user who has previously received dermatology treatment, a dermatologist is recommended. The guidance unit also builds a system that, when a user receives an online medical consultation, refers to the user's past medical history and recommends the most appropriate specialist. A specialist is recommended based on the content of the past medical treatment. Furthermore, when the generating AI suggests an online medical consultation, the guidance unit refers to the user's past medical history in real time and recommends the most appropriate specialist. For a user who has previously received treatment for a specific symptom, a specialist who is familiar with that symptom is recommended. In this way, the most appropriate specialist can be recommended by referring to the user's past medical history.

[0060] The guidance unit can automatically schedule the optimal consultation time for the user's symptoms when the generation AI suggests online medical consultation. For example, when the generation AI suggests online medical consultation, it automatically schedules the optimal consultation time for the user's symptoms. In the case of acute symptoms, it adjusts the schedule so that the user can receive medical treatment as soon as possible. The guidance unit also builds a system that automatically schedules the optimal consultation time for the user's symptoms when the user receives online medical consultation. It adjusts the consultation time to suit the user's convenience. Furthermore, when the generation AI suggests online medical consultation, the guidance unit schedules the optimal consultation time for the user's symptoms in real time. It adjusts the consultation time according to the urgency of the symptoms. This enables rapid medical treatment by automatically scheduling the optimal consultation time for the user's symptoms.

[0061] The guidance unit can provide the user with a preparation guide for receiving medical treatment when the generating AI suggests online medical treatment. For example, when the generating AI suggests online medical treatment, it provides the user with a preparation guide for receiving medical treatment. It lists the documents and information required before the treatment and notifies the user. The guidance unit also builds a system that provides a preparation guide when the user receives online medical treatment. It displays the preparations required before the treatment in checklist format. Furthermore, when the generating AI suggests online medical treatment, the guidance unit provides the user with a preparation guide in real time for receiving medical treatment. It provides step-by-step instructions on the information and procedures required before the treatment. This allows the user to smoothly prepare for the treatment by providing a preparation guide for receiving medical treatment.

[0062] The guidance unit can automatically collect the documents and information necessary for the user to receive medical treatment when the generation AI suggests online medical treatment. For example, when the generation AI suggests online medical treatment, it automatically collects the documents and information necessary for the user to receive medical treatment. Past medical records and allergy information are obtained from a database. The guidance unit also builds a system that automatically collects the documents and information necessary when the user receives online medical treatment. With the user's consent, it obtains the necessary information from medical institutions. Furthermore, when the generation AI suggests online medical treatment, the guidance unit collects the documents and information necessary for the user to receive medical treatment in real time. The necessary documents are automatically generated based on the information entered by the user. This allows the user to smoothly prepare for medical treatment by automatically collecting the documents and information necessary for receiving medical treatment.

[0063] The processing flow of the first embodiment will be briefly explained below.

[0064] Step 1: The image acquisition unit acquires images of the affected area from the user. For example, the user may upload images taken with a smartphone. The image acquisition unit can also acquire images in real time using a webcam. Furthermore, the image acquisition unit can also acquire images from an existing image database. Step 2: The generation AI unit analyzes the image of the affected area acquired by the image acquisition unit. For example, the generation AI unit analyzes the image using deep learning to identify the cause of the case. The generation AI unit can also analyze the image using a convolutional neural network (CNN) to determine how to treat it. Furthermore, the generation AI unit can extract image features and identify case patterns. Step 3: The guidance unit guides the user through the causes and treatments of the cases analyzed by the generation AI unit. For example, the guidance unit may suggest specific treatment methods such as, "This case is a skin inflammation, and cooling and the use of anti-inflammatory medication are recommended." The guidance unit can also explain the steps of the treatment to the user. Furthermore, the guidance unit can provide video tutorials and infographics on the treatment methods. Step 4: The guidance unit guides the user to an online prescription drug sales site or online medical consultation based on the solution provided by the guidance unit. For example, the guidance unit may enable the user to easily purchase prescription drugs by saying, "You need an antihistamine. You can purchase it from this link." The guidance unit may also guide the user to online medical consultation by saying, "If you need further explanation, please receive an online medical consultation from this link." Furthermore, the guidance unit may refer to the user's past purchase history and medical history to suggest the most appropriate prescription drug or specialist.

[0065] (Example 2) The system according to the embodiment of the present invention uses generative AI to quickly identify simple cases such as skin irritation and insect bites, and recommend appropriate treatments. This allows the system to provide consistent service to users and quickly recommend appropriate treatments.

[0066] The system according to the embodiment includes an image acquisition unit, a generation AI unit, a guidance unit, and a guidance unit. The image acquisition unit acquires images of the affected area from a user. For example, the user may upload images taken with a smartphone. The image acquisition unit can also acquire images in real time using a webcam. The image acquisition unit can also acquire images from an existing image database. The generation AI unit analyzes the images of the affected area acquired by the image acquisition unit. For example, the generation AI unit may analyze the images using deep learning to identify the cause of the condition. The generation AI unit can also analyze the images using a convolutional neural network (CNN) to determine a treatment. The generation AI unit can also extract image features and identify patterns of the condition. The guidance unit guides the user to the cause and treatment of the condition analyzed by the generation AI unit. For example, the guidance unit may present specific treatment methods, such as, "This is a skin inflammation, and cooling and the use of anti-inflammatory medication are recommended." The guidance unit can also explain the treatment steps to the user. Furthermore, the guidance unit can provide video tutorials or infographics on treatment methods. The guidance unit guides the user to an online prescription drug sales site or online medical consultation based on the treatment methods provided by the guidance unit. For example, the guidance unit can easily enable the user to purchase prescription drugs by displaying a message such as, "You need an antihistamine. You can purchase it from this link." The guidance unit can also guide the user to online medical consultations by displaying a message such as, "If you need further explanation, please receive an online medical consultation from this link." Furthermore, the guidance unit can suggest the most appropriate prescription drug or specialist by referring to the user's past purchase history and medical history. This allows the system according to the embodiment to provide consistent services to users and guide them to prompt and appropriate treatment methods. For example, the system allows users to quickly treat conditions such as skin irritations and insect bites. Furthermore, the user can easily purchase the necessary prescription drug and receive a diagnosis from a specialist. This improves user convenience and allows them to treat their condition with peace of mind.

[0067] The generation AI unit can make more accurate judgments by referencing the user's past medical history and allergy information. For example, the generation AI unit retrieves the user's past medical history from a database and makes judgments taking allergy information and previous illnesses into consideration. For example, if a user has previously been diagnosed with allergic dermatitis, the generation AI unit will highly evaluate the possibility of an allergy based on that information. In addition, when a user uploads an image, the generation AI unit provides a form for entering past medical history and allergy information and uses that information for analysis. For example, by entering allergy information, the generation AI unit makes judgments taking into account the possibility of an allergic reaction. The generation AI unit also references the user's past medical history and allergy information in real time and reflects this in the judgment results. For example, if a user has had an allergic reaction to a specific medication in the past, the generation AI unit will advise them to avoid that medication. This enables more accurate judgments by taking into account the user's past medical history and allergy information.

[0068] The generation AI unit can integrate and analyze multiple images taken under different lighting conditions and angles to enable more accurate diagnoses. For example, the generation AI unit allows users to upload multiple images taken under different lighting conditions and angles, and integrates and analyzes those images. For example, integrating and analyzing images taken during the day and at night can enable more accurate diagnoses. The generation AI unit can also analyze multiple images taken from different angles and generate a 3D model to grasp the detailed condition of the affected area. For example, analyzing the three-dimensional shape and depth of the affected area can enable more accurate diagnoses. Furthermore, when users upload images taken under different lighting conditions and angles, the generation AI unit automatically corrects, integrates, and analyzes the images. For example, it corrects for light reflections and shadows to enable more accurate diagnoses. This allows for more accurate diagnoses by integrating multiple images taken under different lighting conditions and angles.

[0069] The generation AI unit uses the emotion estimation function to analyze the emotions a user expresses when uploading an image, and can provide relaxation advice if stress or anxiety levels are high. The generation AI unit, for example, analyzes the user's facial expressions and voice to estimate the emotions they express when uploading an image. For example, if the user looks anxious, it can provide relaxation advice. The generation AI unit also uses the emotion estimation function to measure the user's stress or anxiety level when uploading an image, and provides relaxation advice based on the results. For example, it can suggest deep breathing or playing relaxing music. The generation AI unit also uses the emotion estimation function to monitor the user's emotions in real time when uploading an image, and provides relaxation advice if stress or anxiety levels are high. For example, it can suggest simple relaxation exercises. In this way, the generation AI unit analyzes the user's emotions and provides relaxation advice, thereby reducing the user's stress and anxiety.

[0070] The generation AI unit adds a function that allows users to describe their symptoms using voice input, and can acquire information from both images and voice. For example, when a user uploads an image of an affected area, the generation AI unit provides a function for describing symptoms using voice input and uses the voice information for analysis. For example, if a user describes "it's itchy" by voice, the generation AI unit takes that information into consideration when making a judgment. The generation AI unit also analyzes the voice input, acquires details of the symptoms described by the user as text data, and integrates this with image analysis to make a judgment. For example, if a user describes "the redness is spreading," the generation AI unit takes that information into consideration when making a judgment. The generation AI unit also provides a function for users to describe symptoms using voice input when uploading an image of an affected area, and analyzes the voice information in real time to make a judgment. For example, if a user describes "it's painful," the generation AI unit takes that information into consideration when making a judgment. This allows users to describe their symptoms using voice input and acquire more detailed information, enabling more accurate judgments.

[0071] The generation AI unit can provide customized advice based on the user's age and gender when outputting the analysis results. For example, when outputting the results of analyzing an image of an affected area, the generation AI unit provides customized advice based on the user's age and gender. For example, in the case of a child, advice for parents is included. The generation AI unit also provides a form for the user to enter their age and gender when uploading an image, and provides customized advice based on that information. For example, in the case of elderly people, precautions regarding the use of certain medications are included. The generation AI unit also builds a system that provides customized advice based on the user's age and gender when outputting the analysis results. For example, in the case of women, advice regarding specific hormone balances is included. This allows for customized advice based on the user's age and gender, leading to more appropriate treatment methods.

[0072] The generation AI unit uses the emotion estimation function to monitor the emotions of users when uploading images in real time and provide positive feedback, thereby increasing the user's sense of security. The generation AI unit, for example, uses the emotion estimation function to monitor the emotions of users when uploading images in real time and provide positive feedback. For example, if the user looks anxious, an encouraging message is displayed. The generation AI unit also uses the emotion estimation function to build a system that monitors the emotions of users when uploading images in real time and provides positive feedback. For example, if the user is feeling stressed, the system provides advice on how to relax. The generation AI unit also uses the emotion estimation function to monitor the emotions of users when uploading images in real time and provides positive feedback, thereby increasing the user's sense of security. For example, if the user is feeling anxious, a reassuring message is displayed. In this way, the user's emotions can be monitored in real time and positive feedback can be provided, thereby increasing the user's sense of security.

[0073] The guidance unit can provide individually optimized solutions by taking into account the user's lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. For example, when the generation AI provides guidance on the cause of a case and how to deal with it, the guidance unit provides a form for the user to enter lifestyle and environmental information and provides individually optimized solutions based on that information. For example, if the user is a smoker, the guidance unit recommends that the user quit smoking. The guidance unit also builds a system that provides individually optimized solutions by taking into account lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. For example, if the user has allergies, the guidance unit provides advice on avoiding allergens. The guidance unit also acquires the user's lifestyle and environmental information in real time when the generation AI provides guidance on the cause of a case and how to deal with it, and provides individually optimized solutions based on that information. For example, if the user has a pet, the guidance unit provides advice on pet allergies. This allows individually optimized solutions to be provided by taking into account the user's lifestyle and environmental information.

[0074] When providing solutions, the guidance unit can refer to past user feedback and prioritize presenting solutions that were highly effective. For example, when the generation AI provides solutions, the guidance unit retrieves past user feedback from a database and prioritizes presenting solutions that were highly effective. For example, the guidance unit recommends solutions that many users have found effective. Furthermore, the guidance unit builds a system that, when providing solutions to users, refers to past feedback and prioritizes presenting solutions that were highly effective. For example, solutions that have received high user ratings are displayed preferentially. Furthermore, when the generation AI provides solutions, the guidance unit refers to past user feedback in real time and prioritizes presenting solutions that were highly effective. For example, the guidance unit creates a ranking of solutions based on user feedback and recommends the top solutions. In this way, by referring to past user feedback, it is possible to prioritize presenting solutions that were highly effective.

[0075] The guidance unit can use the emotion estimation function to analyze the emotions of the user when accepting a coping method and suggest an approach to elicit positive emotions. The guidance unit, for example, uses the emotion estimation function to analyze the emotions of the user when accepting a coping method and suggest an approach to elicit positive emotions. For example, if the user is feeling anxious, it displays a message that gives a sense of security. The guidance unit also builds a system that uses the emotion estimation function to analyze the emotions of the user when accepting a coping method and suggest an approach to elicit positive emotions. For example, if the user is feeling stressed, it provides advice on how to relax. The guidance unit also uses the emotion estimation function to analyze the emotions of the user when accepting a coping method in real time and suggest an approach to elicit positive emotions. For example, if the user is feeling anxious, it displays an encouraging message. In this way, by analyzing the user's emotions and suggesting an approach to elicit positive emotions, it is possible to promote acceptance of the coping method.

[0076] The guidance unit can provide guidance on countermeasures in a visually easy-to-understand format using video tutorials and infographics. For example, when the generation AI provides guidance on countermeasures, the guidance unit provides video tutorials so that the user can learn the countermeasures in a visually easy-to-understand format. For example, it uses videos to explain how to apply medicine and how to cool the area. The guidance unit also builds a system that provides guidance on countermeasures to the user in a visually easy-to-understand format using infographics. For example, it shows the steps of the countermeasures in diagrams. The guidance unit also builds a system that provides guidance on countermeasures to the user in a visually easy-to-understand format using video tutorials and infographics. For example, it explains the steps of the countermeasures using videos and diagrams. In this way, by using video tutorials and infographics, the countermeasures can be provided in a visually easy-to-understand format.

[0077] When the guidance unit provides guidance on a countermeasure, it can add a reminder function for the user to execute the countermeasure and notify the user at the appropriate time. For example, when the generation AI provides guidance on a countermeasure, the guidance unit provides a reminder function for the user to execute the countermeasure and notifies the user at the appropriate time. For example, it notifies the user when to take medicine or when to apply ice. The guidance unit also adds a reminder function for the user to execute the countermeasure, building a system in which the generation AI notifies the user at the appropriate time. For example, it sends a reminder at a time set by the user. The guidance unit also uses the reminder function to notify the user when to execute the countermeasure when the generation AI provides guidance on a countermeasure. For example, it notifies the user when to apply ice or medicine. In this way, by adding the reminder function, the user can execute the countermeasure at the appropriate time.

[0078] The guidance unit can use the emotion estimation function to monitor the emotions of the user when implementing a coping method in real time and send an encouraging message as needed. The guidance unit, for example, uses the emotion estimation function to monitor the emotions of the user when implementing a coping method in real time and send an encouraging message as needed. For example, if the user is feeling anxious, an encouraging message is displayed. The guidance unit also uses the emotion estimation function to monitor the emotions of the user when implementing a coping method in real time and send an encouraging message as needed. For example, if the user is feeling stressed, advice on how to relax is provided. The guidance unit also uses the emotion estimation function to monitor the emotions of the user when implementing a coping method in real time and send an encouraging message as needed, thereby increasing the user's sense of security. For example, if the user is feeling anxious, a message that gives a sense of security is displayed. In this way, the user's sense of security can be increased by monitoring the user's emotions in real time and sending an encouraging message as needed.

[0079] The guidance unit can suggest the most appropriate prescription drug based on the solution determined by the generation AI and by referring to the user's past purchase history. For example, the guidance unit retrieves the user's past purchase history from a database and suggests the most appropriate prescription drug based on the solution determined by the generation AI. For example, the suggestion takes into account the effects of drugs purchased in the past. The guidance unit also builds a system that suggests the most appropriate prescription drug by referring to the user's past purchase history when guiding the user to a solution. For example, it prioritizes suggesting drugs that have been effective in the past. The guidance unit also suggests the most appropriate prescription drug by referring to the user's past purchase history in real time based on the solution determined by the generation AI. For example, it suggests avoiding drugs that have caused allergic reactions in the past. In this way, the most appropriate prescription drug can be suggested by referring to the user's past purchase history.

[0080] The guidance unit can select safe medications by taking into account the user's allergy information and drug interactions when the generation AI suggests prescription medications. For example, when the generation AI suggests prescription medications, the guidance unit retrieves the user's allergy information from a database and selects safe medications to avoid allergic reactions. For example, if the user is allergic to a specific ingredient, the guidance unit will suggest medications that do not contain that ingredient. The guidance unit also builds a system that selects safe medications by taking into account drug interactions when suggesting prescription medications to the user. For example, it checks for interactions with medications currently being taken and suggests safe medications. The guidance unit also selects safe medications by taking into account the user's allergy information and drug interactions in real time when the generation AI suggests prescription medications. For example, it filters the list of medications based on allergy information and suggests safe medications. This allows safe medications to be selected by taking into account the user's allergy information and drug interactions.

[0081] The guidance unit can use the emotion estimation function to analyze the emotion of a user when purchasing a prescription drug and provide information to reduce anxiety about the purchase. The guidance unit, for example, uses the emotion estimation function to analyze the emotion of a user when purchasing a prescription drug and provide information to reduce anxiety about the purchase. For example, if the user feels anxious, detailed information about the effects and side effects of the drug is provided. The guidance unit also uses the emotion estimation function to analyze the emotion of a user when purchasing a prescription drug and builds a system to provide information to reduce anxiety. For example, if the user feels stressed, advice on how to relax is provided. The guidance unit also uses the emotion estimation function to analyze the emotion of a user when purchasing a prescription drug in real time and provide information to reduce anxiety. For example, if the user feels anxious, a message that gives a sense of security is displayed. In this way, the user's emotion is analyzed and information to reduce anxiety about the purchase is provided, thereby increasing the user's sense of security.

[0082] The guidance unit can provide coupons and discount information for the user to purchase the medicine when the generation AI suggests a prescription drug. For example, the guidance unit provides coupons and discount information for the user to purchase the medicine when the generation AI suggests a prescription drug. For example, it displays discount coupons for specific drugs. The guidance unit also builds a system that provides coupons and discount information when the user purchases prescription drugs. For example, it displays applicable discount information based on purchase history. The guidance unit also provides coupons and discount information for the user to purchase the medicine in real time when the generation AI suggests a prescription drug. For example, it displays discount information that is applicable during a specific campaign period. In this way, by providing coupons and discount information for the user to purchase the medicine, it is possible to increase the user's motivation to purchase.

[0083] The guidance unit can suggest subscription services for the user to purchase medications when the generation AI suggests prescription medications. For example, when the generation AI suggests prescription medications, the guidance unit suggests subscription services for the user to purchase medications on a regular basis. For example, it provides a service that delivers medications on a regular monthly basis. The guidance unit also builds a system that suggests subscription services when the user purchases prescription medications. For example, it displays the benefits of regular purchases and discount information. The guidance unit also suggests subscription services for the user to purchase medications in real time when the generation AI suggests prescription medications. For example, it suggests the optimal subscription plan based on the user's purchase history. This makes it possible to increase user convenience by suggesting subscription services for the user to purchase medications on a regular basis.

[0084] The guiding unit can use the emotion estimation function to monitor the user's emotion when purchasing prescription drugs in real time and provide positive feedback. For example, the guiding unit can use the emotion estimation function to monitor the user's emotion when purchasing prescription drugs in real time and provide positive feedback. For example, if the user is feeling anxious, an encouraging message is displayed. The guiding unit also uses the emotion estimation function to build a system that monitors the user's emotion when purchasing prescription drugs in real time and provides positive feedback. For example, if the user is feeling stressed, advice on how to relax is provided. The guiding unit also uses the emotion estimation function to monitor the user's emotion when purchasing prescription drugs in real time and provides positive feedback, thereby increasing the user's sense of security. For example, if the user is feeling anxious, a message that gives a sense of security is displayed. In this way, the user's emotion can be monitored in real time and positive feedback can be provided, thereby increasing the user's sense of security.

[0085] When the generation AI suggests an online medical consultation, the guidance unit can recommend the most appropriate specialist by referring to the user's past medical history. For example, when the generation AI suggests an online medical consultation, the guidance unit retrieves the user's past medical history from a database and recommends the most appropriate specialist. For example, a dermatologist is recommended for a user who has previously received dermatology treatment. The guidance unit also builds a system that, when a user receives an online medical consultation, refers to the user's past medical history and recommends the most appropriate specialist. For example, a specialist is recommended based on the content of the past medical treatment. Furthermore, when the generation AI suggests an online medical consultation, the guidance unit refers to the user's past medical history in real time and recommends the most appropriate specialist. For example, a specialist who is familiar with that symptom is recommended for a user who has previously received treatment for a specific symptom. In this way, the most appropriate specialist can be recommended by referring to the user's past medical history.

[0086] The guidance unit can automatically schedule the optimal consultation time for the user's symptoms when the generation AI suggests online medical consultation. For example, when the generation AI suggests online medical consultation, the guidance unit automatically schedules the optimal consultation time for the user's symptoms. For example, in the case of acute symptoms, the schedule is adjusted so that the user can receive medical treatment as soon as possible. The guidance unit also builds a system that automatically schedules the optimal consultation time for the user's symptoms when the user receives online medical consultation. For example, the guidance unit adjusts the consultation time to suit the user's convenience. The guidance unit also schedules the optimal consultation time for the user's symptoms in real time when the generation AI suggests online medical consultation. For example, the guidance unit adjusts the consultation time according to the urgency of the symptoms. This enables prompt medical treatment by automatically scheduling the optimal consultation time for the user's symptoms.

[0087] The guiding unit can use the emotion estimation function to analyze the emotion of the user when receiving online medical care and provide advice for relaxation. The guiding unit, for example, uses the emotion estimation function to analyze the emotion of the user when receiving online medical care and provide advice for relaxation. For example, if the user is feeling anxious, the guiding unit suggests breathing techniques for relaxation. The guiding unit also builds a system that uses the emotion estimation function to analyze the emotion of the user when receiving online medical care and provide advice for relaxation. For example, if the user is feeling stressed, the guiding unit plays music for relaxation. The guiding unit also uses the emotion estimation function to analyze the emotion of the user when receiving online medical care in real time and provide advice for relaxation. For example, if the user is feeling anxious, a message that gives a sense of security is displayed. In this way, the user's emotion is analyzed and advice for relaxation is provided, thereby increasing the user's sense of security.

[0088] The guidance unit can provide the user with a preparation guide for receiving medical treatment when the generation AI suggests online medical treatment. For example, the guidance unit provides the user with a preparation guide for receiving medical treatment when the generation AI suggests online medical treatment. For example, it lists the documents and information required before the medical treatment and notifies the user. The guidance unit also builds a system that provides a preparation guide when the user receives online medical treatment. For example, it displays the preparation items required before the medical treatment in checklist format. The guidance unit also provides the user with a preparation guide for receiving medical treatment in real time when the generation AI suggests online medical treatment. For example, it provides step-by-step guidance on the information and procedures required before the medical treatment. In this way, by providing the user with a preparation guide for receiving medical treatment, they can smoothly prepare for the medical treatment.

[0089] The guidance unit can automatically collect documents and information necessary for the user to receive medical treatment when the generation AI suggests online medical treatment. For example, the guidance unit automatically collects documents and information necessary for the user to receive medical treatment when the generation AI suggests online medical treatment. For example, it obtains past medical records and allergy information from a database. The guidance unit also builds a system that automatically collects documents and information necessary when the user receives online medical treatment. For example, it obtains necessary information from a medical institution with the user's consent. The guidance unit also collects documents and information necessary for the user to receive medical treatment in real time when the generation AI suggests online medical treatment. For example, it automatically generates necessary documents based on information entered by the user. This allows the user to smoothly prepare for medical treatment by automatically collecting necessary documents and information necessary for receiving medical treatment.

[0090] The guiding unit can use the emotion estimation function to monitor the user's emotions in real time when receiving online medical care and provide positive feedback. For example, the guiding unit can use the emotion estimation function to monitor the user's emotions in real time when receiving online medical care and provide positive feedback. For example, if the user is feeling anxious, an encouraging message can be displayed. The guiding unit also uses the emotion estimation function to build a system that monitors the user's emotions in real time when receiving online medical care and provides positive feedback. For example, if the user is feeling stressed, the guiding unit can provide advice on how to relax. The guiding unit can also use the emotion estimation function to monitor the user's emotions in real time when receiving online medical care and provide positive feedback, thereby increasing the user's sense of security. For example, if the user is feeling anxious, a message that gives a sense of security can be displayed. In this way, the user's emotions can be monitored in real time and positive feedback can be provided, thereby increasing the user's sense of security.

[0091] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0092] The generation AI unit can make more accurate judgments by referencing the user's past medical history and allergy information. For example, it can retrieve the user's past medical history from a database and make judgments taking into account allergy information and previous illnesses. For a user who has previously been diagnosed with allergic dermatitis, the generation AI unit can highly evaluate the possibility of an allergy based on that information. In addition, when the user uploads an image, the generation AI unit provides a form for entering past medical history and allergy information, and uses that information for analysis. By entering allergy information, the generation AI unit makes judgments taking into account the possibility of an allergic reaction. Furthermore, the generation AI unit references the user's past medical history and allergy information in real time and reflects this in the judgment results. For users who have had an allergic reaction to a specific medication in the past, it can advise them to avoid that medication. This allows for more accurate judgments by taking into account the user's past medical history and allergy information.

[0093] The generative AI unit can integrate and analyze multiple images taken under different lighting conditions and angles to enable more accurate diagnoses. For example, users can upload multiple images taken under different lighting conditions and angles, and these images are integrated and analyzed. Integrating and analyzing images taken during the day and at night enables more accurate diagnoses. The generative AI unit also analyzes multiple images taken from different angles to generate a 3D model to grasp the detailed condition of the affected area. Analyzing the three-dimensional shape and depth of the affected area enables more accurate diagnoses. Furthermore, when users upload images taken under different lighting conditions and angles, the generative AI unit automatically corrects, integrates, and analyzes the images. Light reflections and shadows are corrected to enable more accurate diagnoses. This allows for more accurate diagnoses by integrating multiple images taken under different lighting conditions and angles.

[0094] The generation AI unit uses its emotion estimation function to analyze the emotions a user expresses when uploading an image, and if stress or anxiety is high, it can provide relaxation advice. For example, it analyzes the user's facial expressions and voice to estimate the emotion they express when uploading an image. If the user looks anxious, it provides relaxation advice. The generation AI unit also uses its emotion estimation function to measure the user's stress or anxiety level when uploading an image, and provides relaxation advice based on the results. It suggests deep breathing or playing relaxing music. Furthermore, the generation AI unit uses its emotion estimation function to monitor the user's emotions in real time when uploading an image, and if stress or anxiety is high, it provides relaxation advice. It suggests simple relaxation exercises. In this way, by analyzing the user's emotions and providing relaxation advice, the system reduces the user's stress and anxiety.

[0095] The generation AI unit adds a function that allows users to describe their symptoms using voice input, and can obtain information from both images and voice. For example, when a user uploads an image of an affected area, a function is provided to describe symptoms using voice input, and the voice information is used for analysis. When a user describes "it's itchy" in voice, the generation AI unit takes that information into account when making a judgment. The generation AI unit also analyzes the voice input, obtains the details of the symptoms described by the user as text data, and integrates this with image analysis to make a judgment. When a user describes "the redness is spreading," the generation AI unit takes that information into account when making a judgment. Furthermore, when a user uploads an image of an affected area, the generation AI unit provides a function to describe symptoms using voice input, and analyzes the voice information in real time to make a judgment. When a user describes "it's painful," the generation AI unit takes that information into account when making a judgment. This allows users to describe their symptoms using voice input, obtaining more detailed information and enabling more accurate judgments.

[0096] When outputting the analysis results, the generation AI unit can provide customized advice based on the user's age and gender. For example, when outputting the results of analyzing an image of an affected area, it provides customized advice based on the user's age and gender. In the case of children, advice for parents is included. In addition, when the user uploads an image, the generation AI unit provides a form for entering age and gender, and provides customized advice based on that information. In the case of elderly people, precautions regarding the use of specific medications are included. Furthermore, the generation AI unit builds a system that provides customized advice based on the user's age and gender when outputting the analysis results. In the case of women, advice regarding specific hormone balances is included. This allows for customized advice based on the user's age and gender, leading to more appropriate treatment methods.

[0097] The generation AI unit uses the emotion estimation function to monitor the emotions of users when uploading images in real time and provide positive feedback, thereby increasing the user's sense of security. For example, the emotion estimation function is used to monitor the emotions of users when uploading images in real time and provide positive feedback. If the user looks anxious, an encouraging message is displayed. The generation AI unit also uses the emotion estimation function to build a system that monitors the emotions of users when uploading images in real time and provides positive feedback. If the user is feeling stressed, it provides advice on how to relax. The generation AI unit also uses the emotion estimation function to monitor the emotions of users when uploading images in real time and provide positive feedback, thereby increasing the user's sense of security. If the user is feeling anxious, a reassuring message is displayed. In this way, the user's emotions can be monitored in real time and positive feedback can be provided, thereby increasing the user's sense of security.

[0098] The guidance unit can provide individually optimized solutions by taking into account the user's lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. For example, when the generation AI provides guidance on the cause of a case and how to deal with it, it provides a form for the user to enter lifestyle and environmental information, and provides individually optimized solutions based on that information. If the user is a smoker, it recommends that the user quit smoking. Furthermore, the guidance unit builds a system that provides individually optimized solutions by taking into account lifestyle and environmental information when providing guidance on the cause of a case and how to deal with it. If the user has allergies, it provides advice on avoiding allergens. Furthermore, when the generation AI provides guidance on the cause of a case and how to deal with it, the guidance unit obtains the user's lifestyle and environmental information in real time and provides individually optimized solutions based on that information. If the user has a pet, it provides advice on pet allergies. This allows individually optimized solutions to be provided by taking into account the user's lifestyle and environmental information.

[0099] When providing solutions, the guidance unit can refer to past user feedback and prioritize presenting solutions that were highly effective. For example, when the generation AI provides solutions, it retrieves past user feedback from a database and prioritizes presenting solutions that were highly effective. Solutions that many users have found effective are recommended. In addition, the guidance unit builds a system that, when providing solutions to users, refers to past feedback and prioritizes presenting solutions that were highly effective. Solutions that have received high user ratings are displayed preferentially. Furthermore, when the generation AI provides solutions, the guidance unit refers to past user feedback in real time and prioritizes presenting solutions that were highly effective. A ranking of solutions is created based on user feedback, and the top solutions are recommended. In this way, by referring to past user feedback, it is possible to prioritize presenting solutions that were highly effective.

[0100] The guidance unit can use the emotion estimation function to analyze the emotions of the user when accepting a coping method and suggest an approach to elicit positive emotions. For example, the emotion estimation function is used to analyze the emotions of the user when accepting a coping method and suggest an approach to elicit positive emotions. If the user is feeling anxious, a message that gives a sense of security is displayed. The guidance unit also builds a system that uses the emotion estimation function to analyze the emotions of the user when accepting a coping method and suggest an approach to elicit positive emotions. If the user is feeling stressed, advice on how to relax is provided. Furthermore, the guidance unit uses the emotion estimation function to analyze the emotions of the user when accepting a coping method in real time and suggest an approach to elicit positive emotions. If the user is feeling anxious, an encouraging message is displayed. In this way, by analyzing the user's emotions and suggesting an approach to elicit positive emotions, it is possible to promote acceptance of the coping method.

[0101] When guiding users on how to deal with the problem, the guidance unit can use video tutorials or infographics to provide guidance that is visually easy to understand. For example, when the generation AI provides guidance on how to deal with the problem, it can provide a video tutorial so that the user can learn the method in a visually easy-to-understand manner. Videos can be used to explain how to apply medicine and how to cool the area. In addition, the guidance unit can build a system that uses infographics to provide guidance on how to deal with the problem to the user in a visually easy-to-understand manner. The steps of the method are illustrated. Furthermore, when the generation AI provides guidance on how to deal with the problem, the guidance unit can use video tutorials or infographics to provide guidance that is visually easy to understand. The steps of the method are explained using videos or diagrams. In this way, by using video tutorials or infographics, the method can be provided in a visually easy-to-understand manner.

[0102] When guiding a countermeasure, the guidance unit can add a reminder function for the user to execute the countermeasure and notify the user at the appropriate time. For example, when the generation AI is guiding a countermeasure, it can provide a reminder function for the user to execute the countermeasure and notify the user at the appropriate time. It notifies the user when to take medicine or when to cool the area. Furthermore, the guidance unit adds a reminder function for the user to execute the countermeasure, and a system is constructed in which the generation AI notifies the user at the appropriate time. It sends reminders at times set by the user. Furthermore, when the generation AI is guiding a countermeasure, the guidance unit uses the reminder function to notify the user when to execute the countermeasure. It notifies the user when to cool the area or when to apply medicine. In this way, by adding the reminder function, the user can execute the countermeasure at the appropriate time.

[0103] The guidance unit can use the emotion estimation function to monitor the user's emotions in real time when the user is implementing a coping method and send an encouraging message as needed. For example, the emotion estimation function can be used to monitor the user's emotions in real time when the user is implementing a coping method and send an encouraging message as needed. If the user is feeling anxious, an encouraging message is displayed. The guidance unit also uses the emotion estimation function to build a system that monitors the user's emotions in real time when the user is implementing a coping method and sends an encouraging message as needed. If the user is feeling stressed, advice on how to relax is provided. Furthermore, the guidance unit uses the emotion estimation function to monitor the user's emotions in real time when the user is implementing a coping method and sends an encouraging message as needed, thereby increasing the user's sense of security. If the user is feeling anxious, a message that gives a sense of security is displayed. In this way, the user's emotions can be monitored in real time and an encouraging message can be sent as needed, thereby increasing the user's sense of security.

[0104] The guidance unit can suggest the most appropriate prescription drug based on the solution determined by the generation AI and by referring to the user's past purchase history. For example, based on the solution determined by the generation AI, the guidance unit retrieves the user's past purchase history from a database and suggests the most appropriate prescription drug. The suggestions are made taking into account the effects of drugs purchased in the past. The guidance unit also builds a system that suggests the most appropriate prescription drug by referring to the user's past purchase history when guiding the user to a solution. Drugs that have been effective in the past are given priority in suggesting the most appropriate prescription drug. Furthermore, the guidance unit suggests the most appropriate prescription drug by referring to the user's past purchase history in real time based on the solution determined by the generation AI. It suggests avoiding drugs that have caused allergic reactions in the past. In this way, the guidance unit can suggest the most appropriate prescription drug by referring to the user's past purchase history.

[0105] The guidance unit takes into account the user's allergy information and drug interactions when the generation AI suggests prescription drugs, allowing it to select safe drugs. For example, when the generation AI suggests prescription drugs, it retrieves the user's allergy information from a database and selects safe drugs to avoid allergic reactions. If the user is allergic to a specific ingredient, it will suggest drugs that do not contain that ingredient. The guidance unit also builds a system that takes drug interactions into consideration when suggesting prescription drugs to the user and selects safe drugs. It checks interactions with drugs currently being taken and suggests safe drugs. Furthermore, when the generation AI suggests prescription drugs, the guidance unit takes into account the user's allergy information and drug interactions in real time to select safe drugs. It filters the drug list based on allergy information and suggests safe drugs. This allows safe drugs to be selected by taking the user's allergy information and drug interactions into consideration.

[0106] The guidance unit can use the emotion estimation function to analyze the emotion of the user when purchasing prescription drugs and provide information to reduce anxiety about the purchase. For example, the emotion estimation function is used to analyze the emotion of the user when purchasing prescription drugs and provide information to reduce anxiety about the purchase. If the user feels anxious, detailed information about the effects and side effects of the drug is provided. Furthermore, the guidance unit uses the emotion estimation function to analyze the emotion of the user when purchasing prescription drugs and builds a system to provide information to reduce anxiety. If the user feels stressed, advice on how to relax is provided. Furthermore, the guidance unit uses the emotion estimation function to analyze the emotion of the user when purchasing prescription drugs in real time and provide information to reduce anxiety. If the user feels anxious, a message that gives a sense of security is displayed. In this way, the user's emotion is analyzed and information to reduce anxiety about the purchase is provided, thereby increasing the user's sense of security.

[0107] The guidance unit can provide coupons and discount information for users to purchase drugs when the generation AI suggests prescription drugs. For example, when the generation AI suggests prescription drugs, it provides coupons and discount information for users to purchase drugs. Discount coupons for specific drugs are displayed. The guidance unit also builds a system that provides coupons and discount information when users purchase prescription drugs. It displays applicable discount information based on purchase history. Furthermore, when the generation AI suggests prescription drugs, the guidance unit provides coupons and discount information for users to purchase drugs in real time. It displays discount information that is applicable during a specific campaign period. In this way, by providing coupons and discount information for users to purchase drugs, it is possible to increase users' motivation to purchase.

[0108] When the generation AI suggests prescription drugs, the guidance unit can suggest a subscription service for the user to purchase the drugs. For example, when the generation AI suggests prescription drugs, it suggests a subscription service for the user to purchase drugs on a regular basis. It provides a service that delivers drugs on a regular monthly basis. The guidance unit also builds a system that suggests subscription services when the user purchases prescription drugs. It displays the benefits of regular purchases and discount information. Furthermore, when the generation AI suggests prescription drugs, the guidance unit suggests subscription services for the user to purchase drugs in real time. It suggests the optimal subscription plan based on the user's purchase history. This increases user convenience by suggesting subscription services for the user to purchase drugs on a regular basis.

[0109] The guidance unit can use the emotion estimation function to monitor the user's emotions in real time when purchasing prescription drugs and provide positive feedback. For example, the emotion estimation function can be used to monitor the user's emotions in real time when purchasing prescription drugs and provide positive feedback. If the user is feeling anxious, an encouraging message can be displayed. The guidance unit also builds a system that uses the emotion estimation function to monitor the user's emotions in real time when purchasing prescription drugs and provide positive feedback. If the user is feeling stressed, advice on how to relax can be provided. The guidance unit also uses the emotion estimation function to monitor the user's emotions in real time when purchasing prescription drugs and provide positive feedback, thereby increasing the user's sense of security. If the user is feeling anxious, a message that gives a sense of security can be displayed. In this way, the user's emotions can be monitored in real time and positive feedback can be provided, thereby increasing the user's sense of security.

[0110] When the generating AI suggests an online medical consultation, the guidance unit can recommend the most appropriate specialist by referring to the user's past medical history. For example, when the generating AI suggests an online medical consultation, it retrieves the user's past medical history from a database and recommends the most appropriate specialist. For a user who has previously received dermatology treatment, a dermatologist is recommended. The guidance unit also builds a system that, when a user receives an online medical consultation, refers to the user's past medical history and recommends the most appropriate specialist. A specialist is recommended based on the content of the past medical treatment. Furthermore, when the generating AI suggests an online medical consultation, the guidance unit refers to the user's past medical history in real time and recommends the most appropriate specialist. For a user who has previously received treatment for a specific symptom, a specialist who is familiar with that symptom is recommended. In this way, the most appropriate specialist can be recommended by referring to the user's past medical history.

[0111] The guidance unit can automatically schedule the optimal consultation time for the user's symptoms when the generation AI suggests online medical consultation. For example, when the generation AI suggests online medical consultation, it automatically schedules the optimal consultation time for the user's symptoms. In the case of acute symptoms, it adjusts the schedule so that the user can receive medical treatment as soon as possible. The guidance unit also builds a system that automatically schedules the optimal consultation time for the user's symptoms when the user receives online medical consultation. It adjusts the consultation time to suit the user's convenience. Furthermore, when the generation AI suggests online medical consultation, the guidance unit schedules the optimal consultation time for the user's symptoms in real time. It adjusts the consultation time according to the urgency of the symptoms. This enables rapid medical treatment by automatically scheduling the optimal consultation time for the user's symptoms.

[0112] The guiding unit can use the emotion estimation function to analyze the emotion of the user when receiving online medical care and provide advice for relaxation. For example, the emotion estimation function is used to analyze the emotion of the user when receiving online medical care and provide advice for relaxation. If the user is feeling anxious, the guiding unit suggests breathing techniques for relaxation. Furthermore, the guiding unit uses the emotion estimation function to build a system that analyzes the emotion of the user when receiving online medical care and provides advice for relaxation. If the user is feeling stressed, music for relaxation is played. Furthermore, the guiding unit uses the emotion estimation function to analyze the emotion of the user when receiving online medical care in real time and provide advice for relaxation. If the user is feeling anxious, a message that gives a sense of security is displayed. In this way, the user's emotion is analyzed and advice for relaxation is provided, thereby increasing the user's sense of security.

[0113] The guidance unit can provide the user with a preparation guide for receiving medical treatment when the generating AI suggests online medical treatment. For example, when the generating AI suggests online medical treatment, it provides the user with a preparation guide for receiving medical treatment. It lists the documents and information required before the treatment and notifies the user. The guidance unit also builds a system that provides a preparation guide when the user receives online medical treatment. It displays the preparations required before the treatment in checklist format. Furthermore, when the generating AI suggests online medical treatment, the guidance unit provides the user with a preparation guide in real time for receiving medical treatment. It provides step-by-step instructions on the information and procedures required before the treatment. This allows the user to smoothly prepare for the treatment by providing a preparation guide for receiving medical treatment.

[0114] The guidance unit can automatically collect the documents and information necessary for the user to receive medical treatment when the generation AI suggests online medical treatment. For example, when the generation AI suggests online medical treatment, it automatically collects the documents and information necessary for the user to receive medical treatment. Past medical records and allergy information are obtained from a database. The guidance unit also builds a system that automatically collects the documents and information necessary when the user receives online medical treatment. With the user's consent, it obtains the necessary information from medical institutions. Furthermore, when the generation AI suggests online medical treatment, the guidance unit collects the documents and information necessary for the user to receive medical treatment in real time. The necessary documents are automatically generated based on the information entered by the user. This allows the user to smoothly prepare for medical treatment by automatically collecting the documents and information necessary for receiving medical treatment.

[0115] The guidance unit can use the emotion estimation function to monitor the user's emotions in real time when receiving online medical care and provide positive feedback. For example, the emotion estimation function can be used to monitor the user's emotions in real time when receiving online medical care and provide positive feedback. If the user is feeling anxious, an encouraging message can be displayed. The guidance unit also builds a system that uses the emotion estimation function to monitor the user's emotions in real time when receiving online medical care and provide positive feedback. If the user is feeling stressed, the guidance unit provides advice on how to relax. Furthermore, the guidance unit uses the emotion estimation function to monitor the user's emotions in real time when receiving online medical care and provide positive feedback, thereby increasing the user's sense of security. If the user is feeling anxious, a reassuring message can be displayed. In this way, the user's emotions can be monitored in real time and positive feedback can be provided, thereby increasing the user's sense of security.

[0116] The processing flow of the second embodiment will be briefly explained below.

[0117] Step 1: The image acquisition unit acquires images of the affected area from the user. For example, the user may upload images taken with a smartphone. The image acquisition unit can also acquire images in real time using a webcam. Furthermore, the image acquisition unit can also acquire images from an existing image database. Step 2: The generation AI unit analyzes the image of the affected area acquired by the image acquisition unit. For example, the generation AI unit analyzes the image using deep learning to identify the cause of the case. The generation AI unit can also analyze the image using a convolutional neural network (CNN) to determine how to treat it. Furthermore, the generation AI unit can extract image features and identify case patterns. Step 3: The guidance unit guides the user through the causes and treatments of the cases analyzed by the generation AI unit. For example, the guidance unit may suggest specific treatment methods such as, "This case is a skin inflammation, and cooling and the use of anti-inflammatory medication are recommended." The guidance unit can also explain the steps of the treatment to the user. Furthermore, the guidance unit can provide video tutorials and infographics on the treatment methods. Step 4: The guidance unit guides the user to an online prescription drug sales site or online medical consultation based on the solution provided by the guidance unit. For example, the guidance unit may enable the user to easily purchase prescription drugs by saying, "You need an antihistamine. You can purchase it from this link." The guidance unit may also guide the user to online medical consultation by saying, "If you need further explanation, please receive an online medical consultation from this link." Furthermore, the guidance unit may refer to the user's past purchase history and medical history to suggest the most appropriate prescription drug or specialist.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0131] 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. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0146] In the headset type terminal 314, 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 headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0152] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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).

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0162] In the robot 414, 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. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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).

[0171] 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.

[0172] 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."

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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.

[0184] 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]

[0185] 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. an image acquisition unit that acquires an image of the affected area from a user; a generation AI unit that analyzes the image of the affected area acquired by the image acquisition unit; a guidance unit that guides a user to the cause and treatment of the case analyzed by the generation AI unit; and a guidance unit that guides the user to an e-commerce sales site for prescription drugs or online medical treatment based on the solution provided by the guidance unit. A system characterized by:

2. The generation AI unit Refer to the user's past medical history and allergy information to make a more accurate judgment.

2. The system of claim 1.

3. The generation AI unit Integrate and analyze multiple images taken under different lighting conditions and angles to make a more accurate diagnosis 2. The system of claim 1.

4. The generation AI unit Analyzing the emotions the user is feeling when uploading the image and providing advice to relax if stress or anxiety is high 2. The system of claim 1.

5. The generation AI unit Adding the ability for the user to describe symptoms using voice input, and capturing information from both the image and the voice 2. The system of claim 1.

6. The generation AI unit When outputting the analysis results, provide customized advice according to the user's age and gender.

2. The system of claim 1.

7. The generation AI unit Monitor the user's emotions in real time as they upload the images and provide positive feedback to increase the user's sense of security.

2. The system of claim 1.

8. The guide unit is When providing guidance on the cause of the symptom and the remedy, the lifestyle habits and environmental information of the user are taken into consideration, and the remedy optimized for each individual is provided.

2. The system of claim 1.

Images