System

Abstract

An object of a system according to an embodiment is to provide appropriate medical care even at the time of communication failure and to improve profitability of online medical care.SOLUTION: A system according to an embodiment includes a diagnosis recording unit, a tentative diagnosis unit, a self-care advice unit, an emotion estimation unit, an alternative communication proposal unit, and a communication analysis unit. The medical care recording unit records medical care contents. The tentative diagnosis unit makes a tentative diagnosis based on the medical care content recorded by the medical care recording unit. The self-care advice unit provides a self-care advice to the patient at the time of communication failure. The emotion estimation unit estimates an emotion of the patient at the time of a communication failure and provides a relaxation message. The alternative communication proposal unit proposes an alternative communication means at the time of communication failure. The communication analysis unit analyzes an area or a time zone where a communication failure frequently occurs.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has faced issues such as poor communication, which can lead to medical problems, and lower profitability compared to face-to-face consultations.

[0005] The system according to the embodiment aims to provide appropriate medical care even during poor communication, thereby improving the profitability of online medical care. [Means for solving the problem]

[0006] The system according to the embodiment includes a medical record unit, a provisional diagnosis unit, a self-care advice unit, an emotion estimation unit, an alternative communication suggestion unit, and a communication analysis unit. The medical record unit records medical details. The provisional diagnosis unit makes a provisional diagnosis based on the medical details recorded by the medical record unit. The self-care advice unit provides self-care advice to the patient when communication is poor. The emotion estimation unit estimates the patient's emotion when communication is poor and provides a relaxation message. The alternative communication suggestion unit suggests an alternative communication means when communication is poor. The communication analysis unit analyzes areas and time periods where communication problems occur frequently. [Effects of the Invention]

[0007] The system according to the embodiment can provide appropriate medical care even during poor communication, thereby improving the profitability of online medical care. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

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

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

[0028] (Example 1) The online medical consultation system according to an embodiment of the present invention uses ChatGPT, a generation AI, to solve problems such as medical troubles caused by poor communication, poor profitability compared to face-to-face consultations, and a lack of information necessary for medical treatment. As a result, the online medical consultation system can prevent medical troubles caused by poor communication, improve profitability, and collect necessary information in real time.

[0029] The online medical consultation system according to the embodiment includes a medical record unit, a provisional diagnosis unit, a self-care advice unit, an emotion estimation unit, an alternative communication suggestion unit, and a communication analysis unit. The medical record unit records the details of the medical consultation. For example, the medical record unit records the diagnosis results, treatment plans, and the patient's symptoms. The medical record unit can also automatically record conversations and notes during the consultation. The provisional diagnosis unit makes a provisional diagnosis based on the details of the medical consultation recorded by the medical record unit. For example, the provisional diagnosis unit makes a provisional diagnosis using an algorithm based on the medical history and symptoms. The provisional diagnosis unit can also make a provisional diagnosis based on the patient's past medical history and current symptoms. The self-care advice unit provides self-care advice to the patient when communication is poor. For example, the self-care advice unit suggests first aid and lifestyle improvement methods according to the symptoms. The self-care advice unit can also provide pain relief methods and relaxation techniques. The emotion estimation unit estimates the patient's emotion when communication is poor and provides a relaxation message. For example, the emotion estimation unit estimates the patient's emotion using facial expression recognition, voice analysis, or text analysis. The emotion estimation unit can also provide relaxing music or breathing exercises. The alternative communication suggestion unit can suggest alternative communication methods when a communication failure occurs. For example, the alternative communication suggestion unit can suggest telephone, email, or a messaging app. The alternative communication suggestion unit can also suggest a method of continuing medical treatment using SMS or voice calls. The communication analysis unit analyzes areas and time periods where communication failures frequently occur. For example, the communication analysis unit can identify areas and time periods where communication failures frequently occur using communication log analysis or a geographic information system. The communication analysis unit can also notify patients in advance when a communication failure is predicted. This allows the online medical consultation system according to the embodiment to resolve medical treatment problems caused by communication failures and increase patient peace of mind. For example, when a communication failure occurs, the medical record unit automatically records the medical treatment details and provides information for resuming medical treatment after reconnection. The provisional diagnosis unit makes a provisional diagnosis based on the patient's past medical history and current symptoms, and proposes the diagnosis to the doctor after reconnection. The self-care advice unit provides self-care advice to patients when a communication failure occurs, supporting them until reconnection is achieved.The emotion estimation unit estimates the patient's emotions when communication is poor and provides a relaxation message. The alternative communication suggestion unit suggests alternative communication methods when communication is poor, allowing treatment to continue. The communication analysis unit analyzes areas and time periods where communication problems occur frequently and notifies the patient in advance. This allows patients to receive treatment with peace of mind.

[0030] The provisional diagnosis unit can make a provisional diagnosis based on medical history and symptoms. For example, when communication is interrupted, ChatGPT makes a provisional diagnosis based on the patient's past medical history and current symptoms. For example, it analyzes past medical history and current symptoms to generate a possible diagnosis. In addition, when communication is interrupted, ChatGPT monitors the patient's symptoms in real time and makes a provisional diagnosis. For example, it generates a diagnosis based on symptoms and questions entered by the patient. In addition, when communication is reconnected, ChatGPT proposes the provisional diagnosis result to the doctor, allowing for a smooth resumption of treatment. For example, presenting the provisional diagnosis result to the doctor makes treatment more efficient after reconnection. This allows for a provisional diagnosis to be made even when communication is poor, allowing for a smooth resumption of treatment.

[0031] The self-care advice unit can provide self-care advice to patients when communication is poor. For example, ChatGPT provides self-care advice to patients when communication is poor. For example, it suggests first aid measures and lifestyle improvement methods according to the symptoms. In addition, the self-care advice unit provides real-time self-care advice based on the patient's symptoms when communication is interrupted. For example, it suggests ways to relieve pain or relax. In addition, ChatGPT continues to provide self-care advice to patients until communication is reconnected. For example, it sends periodic check-ins and reminders. This makes it possible to support patients in taking appropriate self-care measures even when communication is poor.

[0032] The alternative communication suggestion unit can suggest alternative communication means to patients when communication is poor. For example, when communication is poor, ChatGPT automatically suggests alternative communication means. For example, it suggests ways to continue medical treatment using SMS or voice calls. The alternative communication suggestion unit also suggests alternative communication means to patients when communication is interrupted, allowing treatment to continue. For example, it sends an SMS to the patient's smartphone to provide treatment instructions. The alternative communication suggestion unit also allows ChatGPT to continue contacting patients using alternative communication means until communication is reconnected. For example, it uses voice calls to check the progress of treatment. This allows treatment to continue even when communication is poor.

[0033] The communication analysis unit can analyze areas and time periods where communication problems occur frequently and notify patients in advance. For example, ChatGPT can analyze areas and time periods where communication problems occur frequently and build a system to notify patients in advance. For example, an alert can be sent to patients to advise them to avoid times when communication is unstable. The communication analysis unit also analyzes past communication data to identify areas and time periods where communication problems are likely to occur. For example, it can analyze trends in communication problems in specific areas and notify patients. Furthermore, if communication problems are predicted, ChatGPT can notify patients in advance and adjust the consultation schedule. For example, it can suggest rescheduling the consultation to a time period when communication is stable. This can prevent communication problems from occurring.

[0034] ChatGPT can analyze patients' symptoms in detail and shorten consultation times. For example, ChatGPT can build a system that analyzes patients' symptoms in detail and shortens consultation times. For example, it can automatically analyze symptom input and quickly provide diagnosis results. ChatGPT can also analyze patients' symptoms before consultation and provide necessary information before doctors begin treatment. For example, it can present detailed symptom analysis results to doctors. ChatGPT can also analyze patients' symptoms in real time during consultations, shortening consultation times. For example, it can instantly detect changes in symptoms and update diagnosis results. This can shorten consultation times and enable more patients to be treated.

[0035] ChatGPT can automate post-consultation follow-ups and reduce the burden on doctors. For example, ChatGPT can build a system that automates post-consultation follow-ups. For example, it can automatically send regular check-ins and reminders to monitor patient conditions. ChatGPT can also automate post-consultation follow-ups and reduce the burden on doctors. For example, it can automatically record patient symptoms and treatment results and report them to doctors. ChatGPT can also automate post-consultation follow-ups and reduce costs. For example, it can monitor patient conditions and notify doctors if abnormalities are detected. This can reduce the burden on doctors and reduce costs.

[0036] ChatGPT can reduce the frequency of return visits by educating patients before and after consultations and improving their self-management skills. ChatGPT can, for example, build a system that provides patient education before and after consultations to improve their self-management skills. For example, it can provide methods for health management and lifestyle improvement. ChatGPT can also provide educational content to patients before consultations to improve their self-management skills. For example, it can provide information on disease prevention methods and treatments. ChatGPT can also provide follow-up education to patients after consultations to reduce the frequency of return visits. For example, it can provide advice and reminders to maintain treatment effects. This can improve self-management skills and reduce the frequency of return visits.

[0037] ChatGPT can automatically generate reports to improve the operational efficiency of medical institutions based on data collected during consultations. ChatGPT can, for example, build a system that automatically generates reports to improve the operational efficiency of medical institutions based on data collected during consultations. For example, it analyzes the performance of medical treatment and patient satisfaction. ChatGPT can also analyze data collected during consultations and generate reports to improve the operational efficiency of medical institutions. For example, it can make suggestions for improving the efficiency of medical treatment and reducing costs. ChatGPT can also automatically generate reports to improve the operational efficiency of medical institutions based on data collected during consultations and provide them to administrators. For example, it can suggest areas for improvement in medical treatment and ways to increase efficiency. This can improve the operational efficiency of medical institutions.

[0038] ChatGPT can automatically collect information about a patient's lifestyle and environment, supplementing the information needed for medical treatment. For example, ChatGPT can build a system that automatically collects information about a patient's lifestyle and environment. For example, it can collect information about a patient's diet, exercise habits, living environment, and other factors, and use this information to aid in medical treatment. ChatGPT can also collect information about a patient's lifestyle and environment in real time to supplement the information needed for medical treatment. For example, it can obtain data from a patient's smart device and reflect this information in medical treatment. ChatGPT can also analyze a patient's lifestyle and environment information to provide the information needed for medical treatment. For example, it can report to a doctor areas for improvement in lifestyle habits and the impact of environmental factors. This can supplement the information needed for medical treatment.

[0039] ChatGPT can monitor patient symptoms in real time and notify doctors if an abnormality is detected. ChatGPT will build a system that monitors patient symptoms in real time and notifies doctors if an abnormality is detected. For example, it will monitor patient vital signs and send an alert if an abnormality is detected. ChatGPT will also analyze patient symptoms in real time and notify doctors if an abnormality is detected. For example, it will detect changes in a patient's symptoms and report them to the doctor. ChatGPT will also develop a system that continuously monitors patient symptoms and notifies doctors if an abnormality is detected. For example, it will monitor a patient's health condition in real time and immediately notify doctors if an abnormality is detected. This will allow for a quick response if an abnormality is detected.

[0040] ChatGPT can collect information from a patient's family and caregivers and provide comprehensive medical information. ChatGPT, for example, collects information from a patient's family and caregivers and builds a system to provide comprehensive medical information. For example, it collects information on the family's health condition and care status and uses it to improve medical treatment. ChatGPT also collects information from a patient's family and caregivers in real time to supplement the information needed for medical treatment. For example, it collects family opinions and caregiver observations and reflects them in medical treatment. ChatGPT also analyzes information from a patient's family and caregivers to provide comprehensive medical information. For example, it reports family health history and care status to a doctor. This allows it to provide comprehensive medical information.

[0041] ChatGPT can analyze a patient's past medical data and discover patterns and trends that are useful for medical treatment. ChatGPT can, for example, build a system that analyzes a patient's past medical data and discovers patterns and trends that are useful for medical treatment. For example, it can analyze past medical history and use it as a reference for diagnosis. ChatGPT can also analyze a patient's past medical data in real time and discover patterns and trends that are useful for medical treatment. For example, it can analyze past changes in symptoms and the effectiveness of treatment. ChatGPT can also analyze a patient's past medical data and discover patterns and trends that are useful for medical treatment and provide them to doctors. For example, it can predict diagnosis results based on past medical data. This makes it possible to discover patterns and trends that are useful for medical treatment.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The online medical consultation system can further include a lifestyle monitoring unit that monitors the patient's lifestyle. For example, the lifestyle monitoring unit can record the patient's diet, exercise, and sleep patterns and provide health advice based on this data. The lifestyle monitoring unit can also obtain data from the patient's smart device and suggest lifestyle improvements in real time. Furthermore, the lifestyle monitoring unit can analyze the patient's lifestyle data and provide a long-term health management plan. This allows for comprehensive management of the patient's lifestyle and supports health maintenance.

[0044] The provisional diagnosis unit can also make a diagnosis that takes into account the patient's genetic information. For example, it can be equipped with a genetic information analysis unit to evaluate the risk of disease based on the patient's genetic information. The genetic information analysis unit can also analyze the patient's family history and genetic tendencies to provide personalized diagnostic results. Furthermore, the genetic information analysis unit can also suggest preventive measures and treatments based on the genetic information. This enables more accurate diagnoses and personalized treatments.

[0045] The self-care advice unit can also monitor the patient's nutritional status and provide nutritional advice. For example, a nutrition monitoring unit can be provided to record the patient's diet and evaluate nutritional balance. The nutrition monitoring unit can also propose a meal plan based on the patient's nutritional status. Furthermore, the nutrition monitoring unit can monitor the patient's nutritional status in real time and suggest nutritional supplements as needed. This allows for comprehensive management of the patient's nutritional status and supports health maintenance.

[0046] The alternative communication suggestion unit can also provide advice to optimize the patient's communication environment. For example, a communication environment optimization unit can be provided to evaluate the patient's communication environment and suggest the optimal communication method. The communication environment optimization unit can also suggest settings or upgrades for communication devices based on the patient's communication environment. Furthermore, the communication environment optimization unit can monitor the patient's communication environment in real time and provide advice to prevent communication problems. This can minimize medical problems caused by poor communication.

[0047] The communication analysis unit can further analyze the patient's communication history and identify the cause of the communication problem. For example, a communication history analysis unit can be provided to analyze data on past communication problems. The communication history analysis unit can also identify patterns of communication problems and propose preventive measures. Furthermore, the communication history analysis unit can identify the cause of the communication problem and provide measures to improve the communication environment. This makes it possible to prevent the recurrence of communication problems and provide a stable communication environment.

[0048] ChatGPT can also provide preventive medical advice based on a patient's health data. For example, it has a preventive medical advice module that analyzes the patient's health data and suggests preventive measures. The preventive medical advice module can also suggest ways to improve lifestyle habits based on the patient's health status. Furthermore, the preventive medical advice module can monitor the patient's health data in real time and provide continuous preventive medical advice. This helps maintain the patient's health and prevent disease.

[0049] ChatGPT can also provide personalized health management plans based on patients' health data. For example, it has a health management plan provider that analyzes patients' health data. The health management plan provider can also propose personalized health management plans based on the patient's health status. Furthermore, the health management plan provider can monitor patients' health data in real time and adjust the health management plan. This allows for comprehensive health management and support for maintaining health.

[0050] The processing flow of the first embodiment will be briefly explained below.

[0051] Step 1: The medical record unit records the medical treatment details. For example, the medical record unit records the diagnosis, treatment plan, and patient symptoms. The medical record unit can also automatically record conversations and notes during the treatment. Step 2: The provisional diagnosis unit makes a provisional diagnosis based on the medical details recorded by the medical record unit. For example, the provisional diagnosis unit makes a provisional diagnosis using an algorithm based on the medical history and symptoms. The provisional diagnosis unit can also make a provisional diagnosis based on the patient's past medical history and current symptoms. Step 3: The self-care advice unit provides self-care advice to patients when communication is poor. For example, the self-care advice unit suggests first aid measures and lifestyle improvement methods according to symptoms. The self-care advice unit can also provide methods for pain relief and relaxation techniques. Step 4: The emotion estimation unit estimates the patient's emotions when communication is poor and provides relaxation messages. For example, the emotion estimation unit estimates the patient's emotions using facial expression recognition, voice analysis, and text analysis. The emotion estimation unit can also provide relaxing music or breathing exercises. Step 5: The alternative communication suggestion unit suggests an alternative means of communication when communication is poor. For example, the alternative communication suggestion unit suggests telephone, email, or a messaging app. The alternative communication suggestion unit can also suggest a method of continuing medical treatment using SMS or voice calls. Step 6: The communication analysis unit analyzes the areas and time periods where communication problems occur frequently. For example, the communication analysis unit identifies areas and time periods where communication problems occur frequently by analyzing communication logs or using a geographic information system. The communication analysis unit can also notify the patient in advance if communication problems are predicted.

[0052] (Example 2) The online medical consultation system according to an embodiment of the present invention uses ChatGPT, a generation AI, to solve problems such as medical troubles caused by poor communication, poor profitability compared to face-to-face consultations, and a lack of information necessary for medical treatment. As a result, the online medical consultation system can prevent medical troubles caused by poor communication, improve profitability, and collect necessary information in real time.

[0053] The online medical consultation system according to the embodiment includes a medical record unit, a provisional diagnosis unit, a self-care advice unit, an emotion estimation unit, an alternative communication suggestion unit, and a communication analysis unit. The medical record unit records the details of the medical consultation. For example, the medical record unit records the diagnosis results, treatment plans, and the patient's symptoms. The medical record unit can also automatically record conversations and notes during the consultation. The provisional diagnosis unit makes a provisional diagnosis based on the details of the medical consultation recorded by the medical record unit. For example, the provisional diagnosis unit makes a provisional diagnosis using an algorithm based on the medical history and symptoms. The provisional diagnosis unit can also make a provisional diagnosis based on the patient's past medical history and current symptoms. The self-care advice unit provides self-care advice to the patient when communication is poor. For example, the self-care advice unit suggests first aid and lifestyle improvement methods according to the symptoms. The self-care advice unit can also provide pain relief methods and relaxation techniques. The emotion estimation unit estimates the patient's emotion when communication is poor and provides a relaxation message. For example, the emotion estimation unit estimates the patient's emotion using facial expression recognition, voice analysis, or text analysis. The emotion estimation unit can also provide relaxing music or breathing exercises. The alternative communication suggestion unit can suggest alternative communication methods when a communication failure occurs. For example, the alternative communication suggestion unit can suggest telephone, email, or a messaging app. The alternative communication suggestion unit can also suggest a method of continuing medical treatment using SMS or voice calls. The communication analysis unit analyzes areas and time periods where communication failures frequently occur. For example, the communication analysis unit can identify areas and time periods where communication failures frequently occur using communication log analysis or a geographic information system. The communication analysis unit can also notify patients in advance when a communication failure is predicted. This allows the online medical consultation system according to the embodiment to resolve medical treatment problems caused by communication failures and increase patient peace of mind. For example, when a communication failure occurs, the medical record unit automatically records the medical treatment details and provides information for resuming medical treatment after reconnection. The provisional diagnosis unit makes a provisional diagnosis based on the patient's past medical history and current symptoms, and proposes the diagnosis to the doctor after reconnection. The self-care advice unit provides self-care advice to patients when a communication failure occurs, supporting them until reconnection is achieved.The emotion estimation unit estimates the patient's emotions when communication is poor and provides a relaxation message. The alternative communication suggestion unit suggests alternative communication methods when communication is poor, allowing treatment to continue. The communication analysis unit analyzes areas and time periods where communication problems occur frequently and notifies the patient in advance. This allows patients to receive treatment with peace of mind.

[0054] The provisional diagnosis unit can make a provisional diagnosis based on medical history and symptoms. For example, when communication is interrupted, ChatGPT makes a provisional diagnosis based on the patient's past medical history and current symptoms. For example, it analyzes past medical history and current symptoms to generate a possible diagnosis. In addition, when communication is interrupted, ChatGPT monitors the patient's symptoms in real time and makes a provisional diagnosis. For example, it generates a diagnosis based on symptoms and questions entered by the patient. In addition, when communication is reconnected, ChatGPT proposes the provisional diagnosis result to the doctor, allowing for a smooth resumption of treatment. For example, presenting the provisional diagnosis result to the doctor makes treatment more efficient after reconnection. This allows for a provisional diagnosis to be made even when communication is poor, allowing for a smooth resumption of treatment.

[0055] The self-care advice unit can provide self-care advice to patients when communication is poor. For example, ChatGPT provides self-care advice to patients when communication is poor. For example, it suggests first aid measures and lifestyle improvement methods according to the symptoms. In addition, the self-care advice unit provides real-time self-care advice based on the patient's symptoms when communication is interrupted. For example, it suggests ways to relieve pain or relax. In addition, ChatGPT continues to provide self-care advice to patients until communication is reconnected. For example, it sends periodic check-ins and reminders. This makes it possible to support patients in taking appropriate self-care measures even when communication is poor.

[0056] The emotion estimation unit can estimate the patient's emotions and provide relaxation messages when communication is disrupted. For example, when a communication failure occurs, ChatGPT uses its emotion estimation function to automatically generate relaxation messages to reduce the patient's anxiety. For example, it can send breathing exercises or positive messages to help them relax. The emotion estimation unit also monitors the patient's emotional state in real time when communication is disrupted and provides messages to reduce anxiety. For example, it can send reassuring words or links to relaxing music. The emotion estimation unit also continuously monitors the patient's emotional state until communication is reconnected and periodically sends relaxation messages. For example, it can periodically send encouraging messages or suggest relaxation techniques. This helps reduce the patient's anxiety and provide a sense of security even when communication is disrupted.

[0057] The alternative communication suggestion unit can suggest alternative communication means to patients when communication is poor. For example, when communication is poor, ChatGPT automatically suggests alternative communication means. For example, it suggests ways to continue medical treatment using SMS or voice calls. The alternative communication suggestion unit also suggests alternative communication means to patients when communication is interrupted, allowing treatment to continue. For example, it sends an SMS to the patient's smartphone to provide treatment instructions. The alternative communication suggestion unit also allows ChatGPT to continue contacting patients using alternative communication means until communication is reconnected. For example, it uses voice calls to check the progress of treatment. This allows treatment to continue even when communication is poor.

[0058] The communication analysis unit can analyze areas and time periods where communication problems occur frequently and notify patients in advance. For example, ChatGPT can analyze areas and time periods where communication problems occur frequently and build a system to notify patients in advance. For example, an alert can be sent to patients to advise them to avoid times when communication is unstable. The communication analysis unit also analyzes past communication data to identify areas and time periods where communication problems are likely to occur. For example, it can analyze trends in communication problems in specific areas and notify patients. Furthermore, if communication problems are predicted, ChatGPT can notify patients in advance and adjust the consultation schedule. For example, it can suggest rescheduling the consultation to a time period when communication is stable. This can prevent communication problems from occurring.

[0059] The emotion estimation unit can monitor the patient's emotions in real time during communication problems and take appropriate measures. For example, when a communication problem occurs, ChatGPT uses its emotion estimation function to monitor the patient's emotions in real time. For example, it detects signs of anxiety or stress and takes appropriate measures. The emotion estimation unit also monitors the patient's emotional state when communication is interrupted and provides appropriate responses. For example, it sends relaxation messages or self-care advice. The emotion estimation unit also continuously monitors the patient's emotional state until communication is reconnected and takes appropriate measures. For example, it suggests encouraging messages or relaxation techniques depending on the patient's emotional changes. This allows ChatGPT to understand the patient's emotional state and take appropriate measures even during communication problems.

[0060] ChatGPT can analyze patients' symptoms in detail and shorten consultation times. For example, ChatGPT can build a system that analyzes patients' symptoms in detail and shortens consultation times. For example, it can automatically analyze symptom input and quickly provide diagnosis results. ChatGPT can also analyze patients' symptoms before consultation and provide necessary information before doctors begin treatment. For example, it can present detailed symptom analysis results to doctors. ChatGPT can also analyze patients' symptoms in real time during consultations, shortening consultation times. For example, it can instantly detect changes in symptoms and update diagnosis results. This can shorten consultation times and enable more patients to be treated.

[0061] ChatGPT can automate post-consultation follow-ups and reduce the burden on doctors. For example, ChatGPT can build a system that automates post-consultation follow-ups. For example, it can automatically send regular check-ins and reminders to monitor patient conditions. ChatGPT can also automate post-consultation follow-ups and reduce the burden on doctors. For example, it can automatically record patient symptoms and treatment results and report them to doctors. ChatGPT can also automate post-consultation follow-ups and reduce costs. For example, it can monitor patient conditions and notify doctors if abnormalities are detected. This can reduce the burden on doctors and reduce costs.

[0062] ChatGPT uses its emotion estimation function to provide customized treatment plans to improve patient satisfaction and increase repeat customers. ChatGPT, for example, uses its emotion estimation function to provide customized treatment plans to improve patient satisfaction. For example, it proposes treatment plans based on the patient's emotional state. ChatGPT also monitors patients' emotional states in real time and provides treatment plans to improve satisfaction. For example, it adjusts treatment content according to changes in the patient's emotions. ChatGPT also uses emotion estimation data to provide customized treatment plans to improve patient satisfaction and increase repeat customers. For example, it proposes treatment plans tailored to the patient's preferences and interests. This improves patient satisfaction and increases repeat customers.

[0063] ChatGPT can reduce the frequency of return visits by educating patients before and after consultations and improving their self-management skills. ChatGPT can, for example, build a system that provides patient education before and after consultations to improve their self-management skills. For example, it can provide methods for health management and lifestyle improvement. ChatGPT can also provide educational content to patients before consultations to improve their self-management skills. For example, it can provide information on disease prevention methods and treatments. ChatGPT can also provide follow-up education to patients after consultations to reduce the frequency of return visits. For example, it can provide advice and reminders to maintain treatment effects. This can improve self-management skills and reduce the frequency of return visits.

[0064] ChatGPT can automatically generate reports to improve the operational efficiency of medical institutions based on data collected during consultations. ChatGPT can, for example, build a system that automatically generates reports to improve the operational efficiency of medical institutions based on data collected during consultations. For example, it analyzes the performance of medical treatment and patient satisfaction. ChatGPT can also analyze data collected during consultations and generate reports to improve the operational efficiency of medical institutions. For example, it can make suggestions for improving the efficiency of medical treatment and reducing costs. ChatGPT can also automatically generate reports to improve the operational efficiency of medical institutions based on data collected during consultations and provide them to administrators. For example, it can suggest areas for improvement in medical treatment and ways to increase efficiency. This can improve the operational efficiency of medical institutions.

[0065] ChatGPT uses its emotion estimation function to develop marketing strategies based on patient emotions, thereby improving profitability. ChatGPT, for example, uses its emotion estimation function to build a system that develops marketing strategies based on patient emotions. For example, it conducts targeted marketing based on patient emotion data. ChatGPT also monitors patients' emotional states in real time and develops emotion-based marketing strategies. For example, it provides specific services to patients with positive emotions. ChatGPT also uses emotion estimation data to develop marketing strategies based on patient emotions, thereby improving profitability. For example, it conducts promotions and campaigns based on emotion data. This can improve profitability.

[0066] ChatGPT can automatically collect information about a patient's lifestyle and environment, supplementing the information needed for medical treatment. For example, ChatGPT can build a system that automatically collects information about a patient's lifestyle and environment. For example, it can collect information about a patient's diet, exercise habits, living environment, and other factors, and use this information to aid in medical treatment. ChatGPT can also collect information about a patient's lifestyle and environment in real time to supplement the information needed for medical treatment. For example, it can obtain data from a patient's smart device and reflect this information in medical treatment. ChatGPT can also analyze a patient's lifestyle and environment information to provide the information needed for medical treatment. For example, it can report to a doctor areas for improvement in lifestyle habits and the impact of environmental factors. This can supplement the information needed for medical treatment.

[0067] ChatGPT can monitor patient symptoms in real time and notify doctors if an abnormality is detected. ChatGPT will build a system that monitors patient symptoms in real time and notifies doctors if an abnormality is detected. For example, it will monitor patient vital signs and send an alert if an abnormality is detected. ChatGPT will also analyze patient symptoms in real time and notify doctors if an abnormality is detected. For example, it will detect changes in a patient's symptoms and report them to the doctor. ChatGPT will also develop a system that continuously monitors patient symptoms and notifies doctors if an abnormality is detected. For example, it will monitor a patient's health condition in real time and immediately notify doctors if an abnormality is detected. This will allow for a quick response if an abnormality is detected.

[0068] ChatGPT uses its emotion estimation function to provide doctors with a patient's emotional state as medical information, supporting more accurate diagnoses. For example, ChatGPT uses its emotion estimation function to build a system that provides doctors with a patient's emotional state as medical information. For example, the patient's emotional score can be presented to doctors to help with diagnosis. ChatGPT can also monitor a patient's emotional state in real time and provide it to doctors as medical information. For example, it can detect changes in the patient's emotions and report them to doctors. ChatGPT can also provide a patient's emotional state as medical information based on emotion estimation data, supporting more accurate diagnoses. For example, it can analyze a patient's emotional state and reflect it in the diagnosis results. This can support more accurate diagnoses.

[0069] ChatGPT can collect information from a patient's family and caregivers and provide comprehensive medical information. ChatGPT, for example, collects information from a patient's family and caregivers and builds a system to provide comprehensive medical information. For example, it collects information on the family's health condition and care status and uses it to improve medical treatment. ChatGPT also collects information from a patient's family and caregivers in real time to supplement the information needed for medical treatment. For example, it collects family opinions and caregiver observations and reflects them in medical treatment. ChatGPT also analyzes information from a patient's family and caregivers to provide comprehensive medical information. For example, it reports family health history and care status to a doctor. This allows it to provide comprehensive medical information.

[0070] ChatGPT can analyze a patient's past medical data and discover patterns and trends that are useful for medical treatment. ChatGPT can, for example, build a system that analyzes a patient's past medical data and discovers patterns and trends that are useful for medical treatment. For example, it can analyze past medical history and use it as a reference for diagnosis. ChatGPT can also analyze a patient's past medical data in real time and discover patterns and trends that are useful for medical treatment. For example, it can analyze past changes in symptoms and the effectiveness of treatment. ChatGPT can also analyze a patient's past medical data and discover patterns and trends that are useful for medical treatment and provide them to doctors. For example, it can predict diagnosis results based on past medical data. This makes it possible to discover patterns and trends that are useful for medical treatment.

[0071] ChatGPT uses its emotion estimation function to suggest treatment approaches based on the patient's emotions, thereby gaining the patient's trust. For example, ChatGPT uses its emotion estimation function to build a system that suggests treatment approaches based on the patient's emotions. For example, it suggests treatment methods based on the patient's emotional state. ChatGPT also monitors the patient's emotional state in real time and suggests treatment approaches based on emotions. For example, it adjusts the treatment content according to the patient's emotional changes. ChatGPT also uses emotion estimation data to suggest treatment approaches based on the patient's emotions, thereby gaining the patient's trust. For example, it analyzes the patient's emotional state and customizes the treatment method. This makes it possible to gain the patient's trust.

[0072] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0073] The online medical consultation system can further include a lifestyle monitoring unit that monitors the patient's lifestyle. For example, the lifestyle monitoring unit can record the patient's diet, exercise, and sleep patterns and provide health advice based on this data. The lifestyle monitoring unit can also obtain data from the patient's smart device and suggest lifestyle improvements in real time. Furthermore, the lifestyle monitoring unit can analyze the patient's lifestyle data and provide a long-term health management plan. This allows for comprehensive management of the patient's lifestyle and supports health maintenance.

[0074] The provisional diagnosis unit can also make a diagnosis that takes into account the patient's genetic information. For example, it can be equipped with a genetic information analysis unit to evaluate the risk of disease based on the patient's genetic information. The genetic information analysis unit can also analyze the patient's family history and genetic tendencies to provide personalized diagnostic results. Furthermore, the genetic information analysis unit can also suggest preventive measures and treatments based on the genetic information. This enables more accurate diagnoses and personalized treatments.

[0075] The self-care advice unit can also monitor the patient's nutritional status and provide nutritional advice. For example, a nutrition monitoring unit can be provided to record the patient's diet and evaluate nutritional balance. The nutrition monitoring unit can also propose a meal plan based on the patient's nutritional status. Furthermore, the nutrition monitoring unit can monitor the patient's nutritional status in real time and suggest nutritional supplements as needed. This allows for comprehensive management of the patient's nutritional status and supports health maintenance.

[0076] The emotion estimation unit can further monitor the patient's stress level and provide stress management advice. For example, the device may include a stress monitoring unit that assesses the patient's stress level in real time. The stress monitoring unit can also suggest relaxation techniques and stress reduction measures based on the patient's stress level. Furthermore, the stress monitoring unit can continuously monitor the patient's stress level and provide a stress management plan as needed. This allows for comprehensive stress management and supports mental health.

[0077] The alternative communication suggestion unit can also provide advice to optimize the patient's communication environment. For example, a communication environment optimization unit can be provided to evaluate the patient's communication environment and suggest the optimal communication method. The communication environment optimization unit can also suggest settings or upgrades for communication devices based on the patient's communication environment. Furthermore, the communication environment optimization unit can monitor the patient's communication environment in real time and provide advice to prevent communication problems. This can minimize medical problems caused by poor communication.

[0078] The communication analysis unit can further analyze the patient's communication history and identify the cause of the communication problem. For example, a communication history analysis unit can be provided to analyze data on past communication problems. The communication history analysis unit can also identify patterns of communication problems and propose preventive measures. Furthermore, the communication history analysis unit can identify the cause of the communication problem and provide measures to improve the communication environment. This makes it possible to prevent the recurrence of communication problems and provide a stable communication environment.

[0079] The emotion estimation unit can further propose a treatment approach according to the patient's emotional state based on the patient's emotional data. For example, an emotion data analysis unit is provided to analyze the patient's emotional data. The emotion data analysis unit can also customize the treatment method based on the patient's emotional state. Furthermore, the emotion data analysis unit can monitor the patient's emotional changes in real time and adjust the treatment approach. This makes it possible to provide treatment according to the patient's emotional state and improve patient satisfaction.

[0080] ChatGPT can also provide preventive medical advice based on a patient's health data. For example, it has a preventive medical advice module that analyzes the patient's health data and suggests preventive measures. The preventive medical advice module can also suggest ways to improve lifestyle habits based on the patient's health status. Furthermore, the preventive medical advice module can monitor the patient's health data in real time and provide continuous preventive medical advice. This helps maintain the patient's health and prevent disease.

[0081] ChatGPT can also provide self-care advice tailored to the patient's emotional state based on the patient's emotional data. For example, it includes an emotional self-care advice unit that analyzes the patient's emotional data. The emotional self-care advice unit can also suggest self-care methods based on the patient's emotional state. Furthermore, the emotional self-care advice unit can monitor the patient's emotional changes in real time and adjust the self-care advice accordingly. This allows for self-care tailored to the patient's emotional state and supports mental health.

[0082] ChatGPT can also provide personalized health management plans based on patients' health data. For example, it has a health management plan provider that analyzes patients' health data. The health management plan provider can also propose personalized health management plans based on the patient's health status. Furthermore, the health management plan provider can monitor patients' health data in real time and adjust the health management plan. This allows for comprehensive health management and support for maintaining health.

[0083] The processing flow of the second embodiment will be briefly explained below.

[0084] Step 1: The medical record unit records the medical treatment details. For example, the medical record unit records the diagnosis, treatment plan, and patient symptoms. The medical record unit can also automatically record conversations and notes during the treatment. Step 2: The provisional diagnosis unit makes a provisional diagnosis based on the medical details recorded by the medical record unit. For example, the provisional diagnosis unit makes a provisional diagnosis using an algorithm based on the medical history and symptoms. The provisional diagnosis unit can also make a provisional diagnosis based on the patient's past medical history and current symptoms. Step 3: The self-care advice unit provides self-care advice to patients when communication is poor. For example, the self-care advice unit suggests first aid measures and lifestyle improvement methods according to symptoms. The self-care advice unit can also provide methods for pain relief and relaxation techniques. Step 4: The emotion estimation unit estimates the patient's emotions when communication is poor and provides relaxation messages. For example, the emotion estimation unit estimates the patient's emotions using facial expression recognition, voice analysis, and text analysis. The emotion estimation unit can also provide relaxing music or breathing exercises. Step 5: The alternative communication suggestion unit suggests an alternative means of communication when communication is poor. For example, the alternative communication suggestion unit suggests telephone, email, or a messaging app. The alternative communication suggestion unit can also suggest a method of continuing medical treatment using SMS or voice calls. Step 6: The communication analysis unit analyzes the areas and time periods where communication problems occur frequently. For example, the communication analysis unit identifies areas and time periods where communication problems occur frequently by analyzing communication logs or using a geographic information system. The communication analysis unit can also notify the patient in advance if communication problems are predicted.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] 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).

[0094] 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.

[0095] 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.

[0096] 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.

[0097] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0098] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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).

[0109] 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.

[0110] 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.

[0111] 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.

[0112] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0113] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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).

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0129] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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).

[0138] 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.

[0139] 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."

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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, in order to avoid confusion and to 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.

[0151] 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]

[0152] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a medical record section for recording medical treatment details; a provisional diagnosis unit that makes a provisional diagnosis based on the medical treatment details recorded by the medical treatment record unit; a self-care advice section that provides self-care advice to patients when communication is poor; an emotion estimation unit that estimates the emotion of a patient when communication is poor and provides a relaxation message; an alternative communication suggestion unit that suggests an alternative communication means when communication is poor; A communication analysis unit that analyzes areas and time periods where communication problems frequently occur. A system characterized by:

2. The provisional diagnosis unit A tentative diagnosis is made based on medical history and symptoms 2. The system of claim 1.

3. The alternative communication suggestion unit Suggesting alternative communication methods to the patient in the event of communication failure 2. The system of claim 1.

4. The ChatGPT is Analyze the patient's symptoms in detail to shorten the consultation time 2. The system of claim 1.

5. The ChatGPT is Automatically collects information on the patient's lifestyle and environment to supplement the information needed for medical treatment.

2. The system of claim 1.

6. The emotion estimation unit Estimate the patient's emotions when communication is poor and provide the relaxation message 2. The system of claim 1.

7. The ChatGPT is Providing customized treatment plans to improve patient satisfaction and increase repeat visits 2. The system of claim 1.

8. The ChatGPT is Propose a treatment approach based on the patient's feelings and gain their trust.

2. The system of claim 1.

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