System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting diagnosis information; means for transmitting the diagnosis information to a server; means for performing an automatic examination based on the diagnosis information in the server; means for receiving and notifying a diagnosis result and a treatment plan generated by the automatic examination; means for processing an insurance premium payment based on the treatment plan; means for notifying the insurance premium payment result; means for introducing a specialist based on the treatment plan; and means for supporting an appointment procedure to the specialist.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] Under the conventional insurance system, it took a long time to pay insurance claims after treatment or surgery, making it difficult for patients to receive appropriate treatment quickly. Furthermore, getting a second opinion required visiting another medical institution and undergoing further examinations, which was a significant time and effort commitment. Under these circumstances, early detection and treatment were difficult, increasing patient anxiety. [Means for solving the problem]

[0005] This invention provides a system equipped with a means for inputting diagnostic information and transmitting it to a server, a means for automatic review, a means for notifying patients of diagnostic results and treatment plans, a means for processing insurance premium payments, and a means for introducing specialists and assisting with appointment procedures. This allows patients to receive prompt and appropriate diagnoses and treatment, and the insurance payment procedures are also automated, preventing delays in treatment. Furthermore, patients can easily obtain the opinions of specialists, enabling early detection and early treatment based on appropriate treatment plans.

[0006] "Diagnostic information" refers to information about the user's own poor physical condition and diagnostic results.

[0007] "Server" refers to a computer system that receives, stores, processes data over a network, and transmits the results to other devices.

[0008] "Automated review" refers to the process by which the server uses algorithms to generate diagnostic results and treatment plans based on the diagnostic information received.

[0009] "Diagnosis result" refers to an assessment of the cause of a user's ill health or suspected medical condition generated by an automated review.

[0010] A "treatment plan" refers to a list of appropriate tests and treatment procedures proposed based on the diagnostic results.

[0011] "Payment of insurance premiums" refers to the transfer or payment procedure in which the amount calculated by the server is transferred to a bank account or other account designated by the user.

[0012] A "specialist" is a doctor with advanced knowledge and experience in a particular medical field.

[0013] The "reservation procedure" refers to a series of procedures that a user goes through to make an appointment with a specialist for an examination or treatment. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] 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.

[0019] 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.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] 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.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] overview

[0036] This invention is a system for efficiently inputting and transmitting diagnostic information, automatically reviewing it, notifying users of diagnostic results and treatment plans, automatically paying insurance premiums, and referral and appointment procedures for specialists. This system allows users to receive prompt and appropriate medical care and automates insurance payment procedures, preventing delays in treatment.

[0037] System configuration

[0038] server

[0039] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0040] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[0041] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[0042] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[0043] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[0044] Terminal (device used by the user)

[0045] The terminal provides an interface for the user to input diagnostic information.

[0046] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[0047] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[0048] The terminal provides a function to assist the user in making an appointment with a specialist.

[0049] User (patient)

[0050] The user inputs their own health condition and diagnosis results through the terminal.

[0051] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[0052] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[0053] Program processing explanation

[0054] Entering and sending diagnostic information

[0055] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[0056] The terminal formats this data and sends it to the server.

[0057] Automated review and diagnostic generation

[0058] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[0059] The server generates and provides diagnostic results and standard treatment plans to the user.

[0060] Premium payment processing and notification

[0061] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[0062] The server sends the payment result to the terminal and notifies the user.

[0063] Specialist opinion and referral

[0064] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[0065] The server sends the appointment information to the specialist and confirms the appointment.

[0066] Confirm appointment and start treatment

[0067] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[0068] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[0069] The above configuration and functions enable users to receive prompt and accurate medical services and facilitate smooth insurance payment procedures, thereby reducing delays in treatment and patient anxiety.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] The user inputs their own health condition and diagnosis results into the device application.

[0073] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[0074] Step 2:

[0075] The terminal formats the entered diagnostic information and sends it to the server.

[0076] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[0077] Step 3:

[0078] The server stores the received diagnostic information in a database.

[0079] Specifically, the received data is validated and stored in the appropriate database tables.

[0080] Step 4:

[0081] The server will start the automatic review.

[0082] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[0083] Step 5:

[0084] The server generates a diagnosis and a standard treatment plan.

[0085] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[0086] Step 6:

[0087] The server sends the generated diagnostic results and treatment plan to the terminal.

[0088] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[0089] Step 7:

[0090] The terminal notifies the user of the received diagnosis results and treatment plan.

[0091] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[0092] Step 8:

[0093] The server automates the insurance payment process.

[0094] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[0095] Step 9:

[0096] The server sends a notification of payment completion to the terminal.

[0097] Specifically, the transfer success status and detailed information are sent to the terminal.

[0098] Step 10:

[0099] The terminal displays a notification to the user that the payment has been completed.

[0100] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[0101] Step 11:

[0102] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[0103] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[0104] Step 12:

[0105] The terminal displays a list of specialists to the user.

[0106] Specifically, when a user opens the application, it displays a list of specialists.

[0107] Step 13:

[0108] The user selects the desired specialist and makes a reservation.

[0109] Specifically, fill out the reservation form within the application and press the submit button.

[0110] Step 14:

[0111] The terminal sends the reservation procedure to the server.

[0112] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[0113] Step 15:

[0114] The server sends the appointment information to the specialist for confirmation.

[0115] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[0116] Step 16:

[0117] The terminal notifies the user of the reservation confirmation information.

[0118] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[0119] Through these processing steps, users can receive prompt and accurate diagnosis and treatment, and the automated payment process prevents delays in treatment.

[0120] Example 1

[0121] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0122] In the current medical system, patients must enter diagnostic information, receive diagnostic results, receive notification of treatment plans, pay insurance premiums, and refer to specialists and make appointments individually, which takes time and effort, and can prevent patients from receiving medical services promptly and appropriately.There is also concern that delays in insurance payment procedures could delay the start of treatment.

[0123] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0124] In this invention, the server includes a means for automatically reviewing the diagnostic information and using an algorithm that references past diagnostic data and standard treatment protocols, a means for notifying the generated diagnostic results and treatment plan, and a means for calculating insurance premiums based on the treatment plan and automatically transferring the premiums to a designated bank account. This enables rapid review of diagnostic information, provision of diagnostic results and treatment plans, and automatic payment of insurance premiums, allowing patients to receive medical services efficiently and without delay.

[0125] "Diagnosis information" is information entered by the user regarding their own poor physical condition or symptoms.

[0126] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0127] "Automated review" is the process of using an algorithm to perform a diagnosis based on received diagnostic information and generate a result.

[0128] An "algorithm" is a computational method that analyzes diagnostic information and matches it with historical diagnostic data and standard treatment protocols.

[0129] A "diagnostic result" is a specific diagnostic conclusion generated by an automated review.

[0130] A "treatment plan" is a specific treatment step and prescription proposed based on diagnostic results.

[0131] "Premium" is the payment amount calculated based on the diagnosis and treatment plan.

[0132] "Direct deposit" is the process of transferring funds electronically to a designated bank account.

[0133] A "specialist" is a doctor who is well-versed and certified in a particular field.

[0134] The "reservation procedure" is the procedure for confirming the date and time of an appointment with a specialist.

[0135] A "generative AI model" is a model that uses artificial intelligence to analyze diagnostic information and automatically review and generate diagnostic results.

[0136] overview

[0137] This invention is a system for efficiently inputting, transmitting, and automatically reviewing diagnostic information, notifying diagnostic results and treatment plans, automatically paying insurance premiums, and processing specialist referrals and appointment procedures. This system is designed to enable users to receive prompt and appropriate medical care by using generative AI models to analyze diagnostic information and automate various procedures.

[0138] Hardware and Software Used

[0139] server:

[0140] A server is a computer system that receives, stores, processes data, and sends the results to other devices over a network. For example, this could include a database management system or a diagnostic algorithm running on a Linux server.

[0141] Device:

[0142] The terminal is the device used by the user, such as a smartphone, tablet, or laptop, that provides the user interface and assists in entering diagnostic information, displaying received results, and scheduling appointments with specialists.

[0143] Generative AI models:

[0144] An artificial intelligence model for analyzing diagnostic information and generating diagnostic results and treatment plans, using machine learning frameworks such as TensorFlow and PyTorch.

[0145] Processing flow

[0146] 1. The user uses the device interface to input their own health condition and diagnosis results. For example, the user enters "I've been feeling tired a lot recently" in the text box.

[0147] 2. The device formats this information (e.g., in JSON format) and sends it to the server.

[0148] 3. The server uses the received data to perform an automated review using a generative AI model. For example, it uses past diagnostic data to determine whether "easily fatigued" is an early symptom of hypothyroidism.

[0149] 4. The server generates the diagnosis and standard treatment plan (e.g., blood tests and thyroid hormone replacement therapy recommendations) and sends them to the device.

[0150] 5. The device displays the diagnosis and treatment plan to the user.

[0151] 6. The server calculates the insurance premium based on the treatment plan and uses a financial API to automatically transfer the payment to the bank account specified by the user.

[0152] 7. The server notifies the terminal of the transfer result so that the user can check it.

[0153] 8. The terminal displays a list of appropriate specialists to the user, allowing the user to select the desired specialist and make an appointment.

[0154] 9. The server sends the reservation information to the specialist, and once confirmation is received, it sends the reservation confirmation information to the terminal.

[0155] 10. The terminal displays the reservation confirmation information to the user.

[0156] 11. The user visits the specialist at the specified date and time and begins treatment based on the diagnosis results.

[0157] Examples of concrete examples and prompts

[0158] Specific examples

[0159] 1. The user types "I've been feeling very tired lately" into the device and sends it.

[0160] 2. The device sends this information to the server.

[0161] 3. The server analyzes the received data and generates a diagnosis of suspected hypothyroidism and a treatment plan.

[0162] 4. The server sends the result to the terminal and notifies the user.

[0163] 5. The server calculates the insurance premium based on the treatment plan and transfers the amount to the specified bank account.

[0164] 6. The device notifies the user of the results and provides a list of specialists.

[0165] 7. The user selects the specialist of their choice and makes an appointment.

[0166] 8. The server sends the appointment information to the specialist for confirmation.

[0167] Prompt Sentence Examples

[0168] "Have you been feeling tired more often recently?"

[0169] "A diagnosis and treatment plan have been generated. Please review the details."

[0170] "Insurance premium payment completed. Please check the results."

[0171] "Here's a list of suitable specialists. Please select one if you would like to make an appointment."

[0172] The system allows users to receive medical services efficiently and without delay, and the use of generative AI models improves the accuracy of diagnostic results and treatment plans, further enhancing user convenience.

[0173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0174] Step 1:

[0175] The user uses the device interface to input diagnostic information about their health condition or symptoms. For example, the user might type, "I've been feeling tired a lot recently" into a text box. The input data is formatted and ready to be recognized by the system.

[0176] Step 2:

[0177] The device converts the diagnostic information entered into a standard format such as JSON and sends it to the server. The formatted data is then transferred to the server as an HTTP request.

[0178] Step 3:

[0179] The server stores the received diagnostic information in a database and starts analysis by accessing the data repository. Specifically, it executes an INSERT query in the database.

[0180] Step 4:

[0181] The server performs an automated review based on the diagnostic information. It uses a generative AI model to analyze the diagnostic information and compare it with past diagnostic data and standard treatment protocols. For example, it compares it with past patient data with the symptom of "easily fatigued" and evaluates the relevance. The input is the diagnostic information, and the output is the diagnostic results and treatment plan.

[0182] Step 5:

[0183] The server generates diagnostic results and treatment plans, which are packaged in JSON format and sent to the device. For example, the diagnostic results for hypothyroidism and the treatment plan for "thyroid hormone replacement therapy" are included. This allows the user to check the diagnostic results.

[0184] Step 6:

[0185] The terminal displays the diagnosis results and treatment plan received on the user interface. For example, the diagnosis name and recommended treatment details are displayed. Specifically, the data is displayed in the UI component.

[0186] Step 7:

[0187] The server calculates insurance premiums based on diagnosis results and treatment plans. It uses a financial API to calculate insurance premiums in real time and automatically transfers the funds to a designated bank account. The input is diagnosis results and insurance information, and the output is the transfer results.

[0188] Step 8:

[0189] The server generates the transfer result and sends it to the terminal in JSON format, such as "$200 has been transferred to the specified bank account." The terminal receives this and makes it available.

[0190] Step 9:

[0191] The terminal notifies the user of the payment result. For example, a message such as "Insurance payment has been completed. Please check the result" is displayed. Specifically, the message is displayed in the notification component.

[0192] Step 10:

[0193] The device displays a list of appropriate specialists to the user, for example, a list of categories such as "endocrinologists," and provides an interface for the user to select the desired specialist.

[0194] Step 11:

[0195] When a user selects a specialist and wishes to make an appointment, they complete the reservation procedure through their terminal. For example, they enter "I would like to make an appointment with an endocrinologist" into the reservation form. The input is sent to the server.

[0196] Step 12:

[0197] The server sends the appointment information to the specialist and confirms it. For example, it checks the appointment schedule and generates appointment confirmation information. The input is the user's appointment information, and the output is the appointment confirmation information.

[0198] Step 13:

[0199] The device displays reservation confirmation information to the user. For example, a message like "Reservation confirmed. Please confirm the date, time, and location" is displayed. Specifically, the schedule information is displayed in the calendar component.

[0200] Step 14:

[0201] The user visits a specialist at a specified date and time and begins treatment based on the diagnosis. For example, a user might visit a designated endocrinologist to receive treatment for hypothyroidism.

[0202] (Application example 1)

[0203] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0204] In modern healthcare services, to ensure patients receive prompt and appropriate diagnoses and treatment, it is necessary to streamline a series of processes, from entering and submitting diagnostic information to automatic review, notification of diagnostic results, insurance payment, specialist referrals, and appointment procedures. However, when these processes are performed manually, they require a lot of time and effort, resulting in treatment delays and patient anxiety. Furthermore, if medical data security is not ensured, there is a risk that patient privacy will be compromised. To solve these issues, an efficient and secure healthcare service delivery system is required.

[0205] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0206] In this invention, the server includes a means for inputting diagnostic information, a means for transmitting the diagnostic information to the server, a means for performing an automatic review based on the diagnostic information in the server, a means for encrypting the diagnostic information and transmitting it to the server, a means for performing an automatic review using an AI model and generating a diagnostic result, a means for processing insurance premium payments via an online payment system, and a means for synchronizing appointment information with a calendar. This enables secure transmission of diagnostic information, automated generation of diagnostic results, prompt insurance premium payment processing, and smooth appointment procedures with specialists.

[0207] "Diagnostic information" refers to information entered by a patient about their health condition or symptoms.

[0208] A "server" is a computer system that receives, stores, processes, and transmits data over a network.

[0209] "Automated review" refers to the process of using algorithms or AI models based on input diagnostic information to generate diagnostic results without manual intervention.

[0210] "Diagnostic result" means a medical judgment or diagnosis of a patient's symptoms generated by an automated review means.

[0211] A "treatment plan" refers to the specific treatment content and procedures that a patient should undergo based on the diagnostic results.

[0212] "Premiums" are the money paid by patients to cover medical expenses and are calculated based on automated screening results and treatment plans.

[0213] An "online payment system" is a system that automatically conducts monetary transactions via the Internet.

[0214] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[0215] "Appointment booking" refers to the process for booking a date and time to see a specialist.

[0216] "Calendar synchronization" means linking reservation information and other data with a digital calendar system to maintain consistency of information.

[0217] "Encryption" is a technique for converting data into a format that cannot be deciphered by third parties.

[0218] An "AI model" is a model that uses artificial intelligence algorithms to automatically extract patterns and knowledge from data and make diagnoses and predictions.

[0219] System configuration

[0220] A system for implementing this invention includes the following major components:

[0221] 1. Terminal (device used by the user)

[0222] 2. Server

[0223] 3. Network

[0224] Terminal

[0225] The terminal is a device that provides an interface for users to input diagnostic information and send it to the server. The terminal is a mobile device that can connect to the Internet, such as a smartphone or tablet. The terminal has the following functions:

[0226] Entering and sending encrypted diagnostic information (using encryption technology such as AES-256)

[0227] Notification of diagnosis and treatment plan

[0228] Displaying a list of specialists and assisting with appointment booking (Calendar synchronization using Google Calendar API)

[0229] server

[0230] The server is a computer system that receives data sent from the terminals via the network and performs automatic review and processing. The server processes the data using the following software:

[0231] Backend: Node.js and Express

[0232] Database: Use MongoDB to manage health data

[0233] AI diagnostic model: Automated screening using TensorFlow

[0234] Online payment system: Stripe API or PayPal API

[0235] Processing Details

[0236] Entering and sending diagnostic information

[0237] Users use the device to enter their diagnostic information, including details of their illness and symptoms, which is then securely transmitted to the server using AES-256 encryption.

[0238] Automated review and diagnostic generation

[0239] The server inputs the received diagnostic information into an AI diagnostic model (TensorFlow) for automatic review. It generates diagnostic results and a treatment plan using an algorithm that references past diagnostic data and standard treatment protocols, and sends them to the device.

[0240] Insurance premium payment processing

[0241] The server calculates the insurance premium based on the diagnosis results and treatment plan, and automatically processes the payment using an online payment system (such as Stripe API or PayPal API). The results are then sent to the terminal.

[0242] Specialist referrals and appointments

[0243] Based on the information received from the server, the device displays a list of appropriate specialists to the user. Once the user selects a specialist, the device uses the Google Calendar API to synchronize the appointment information with the calendar and assist with the appointment process.

[0244] Examples and prompts

[0245] Examples:

[0246] User input: "I've been feeling tired and dizzy lately."

[0247] The AI ​​model says: "These symptoms may indicate hypothyroidism. We'll provide a treatment plan based on the diagnosis and a referral specialist."

[0248] Payment procedure: "Insurance premium calculation completed. 2500 yen has been automatically paid."

[0249] Example prompt for a generative AI model:

[0250] "Create an application that uses an automated diagnostic model to generate a diagnosis based on the health information entered by the user, and then calculates insurance premiums and processes payments based on the results. It also refers users to the appropriate specialist and automatically schedules appointments."

[0251] As a result, the present invention can provide efficient and secure medical services and reduce the burden on patients.

[0252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0253] Step 1:

[0254] User enters diagnostic information

[0255] Input: The user uses the terminal to input diagnostic information (e.g., fatigue, dizziness).

[0256] Specific operation: The user uses a smartphone or tablet to enter their symptoms into the input form of a dedicated application.

[0257] Output: Entered diagnostic information is saved to the terminal.

[0258] Step 2:

[0259] The device encrypts the diagnostic information and sends it to the server

[0260] Input: The diagnostic information entered in Step 1.

[0261] Data processing: Diagnostic information is encrypted using AES-256 encryption technology.

[0262] Specific operation: The terminal application encrypts the entered diagnostic information and sends it to the server using a secure communication protocol (HTTPS).

[0263] Output: Encrypted diagnostic information is sent to the server.

[0264] Step 3:

[0265] The server performs an automatic review based on the diagnostic information.

[0266] Input: Diagnostic information sent encrypted.

[0267] Data processing: The server decrypts the encrypted data and converts it into a format that can be input into the AI ​​diagnostic model (TensorFlow).

[0268] What it does: The server decrypts the diagnostic information and runs the AI ​​model using historical diagnostic data and standard treatment protocols.

[0269] Output: Diagnosis and treatment plan generated by the AI ​​diagnostic model.

[0270] Step 4:

[0271] The server sends the diagnosis results and treatment plan to the device.

[0272] Input: The diagnosis and treatment plan generated in step 3.

[0273] Specific operation: The server converts the diagnosis results and treatment plan into a data format (such as JSON) and sends them to the terminal.

[0274] Output: The diagnosis and treatment plan are sent to the device.

[0275] Step 5:

[0276] The device notifies you of the diagnosis and treatment plan

[0277] Input: Diagnosis and treatment plan submitted in step 4.

[0278] What it does: The device application uses notifications to display diagnostic results and treatment plans to the user.

[0279] Output: The user is informed of the diagnosis and treatment plan.

[0280] Step 6:

[0281] The server calculates and pays the insurance premiums.

[0282] Input: The treatment plan generated in step 4.

[0283] Data calculation: Calculates insurance premiums based on treatment plans and executes payment procedures via online payment systems (Stripe API or PayPal API).

[0284] Specific operation: The server analyzes the treatment plan, calculates the required insurance premium, and then calls the API of the online payment system to automatically make the payment.

[0285] Output: Premium payment result.

[0286] Step 7:

[0287] The server sends the insurance premium payment result to the terminal

[0288] Input: Premium payment results obtained in step 6.

[0289] Specific operation: The server converts the insurance premium payment results into a data format (such as JSON) that is easy for the user to understand and sends it to the terminal.

[0290] Output: The insurance premium payment result is sent to the terminal.

[0291] Step 8:

[0292] The terminal notifies the result of the insurance premium payment

[0293] Input: Premium payment result sent in step 7.

[0294] Specific operation: The terminal application uses the notification function to display the insurance premium payment result to the user.

[0295] Output: The user is notified of the insurance premium payment result.

[0296] Step 9:

[0297] The device displays a list of specialists and assists with the appointment process

[0298] Input: Treatment plan and specialist information submitted in step 4.

[0299] What it does: The device application displays a list of appropriate specialists based on the treatment plan, helps the user schedule an appointment with the selected specialist, and synchronizes the appointment information using the Google Calendar API.

[0300] Output: The user is presented with a list of specialists and is assisted in the appointment process.

[0301] Step 10:

[0302] The server sends the appointment information to the specialist

[0303] Input: Reservation information generated in step 9.

[0304] Specific operation: The server sends the appointment information to the specialist's system and confirms the appointment.

[0305] Output: Appointment information is sent to the specialist and confirmed.

[0306] Step 11:

[0307] The device will notify you of the reservation confirmation information

[0308] Input: Reservation information confirmed in step 10.

[0309] Specific behavior: The device application uses the notification function to display reservation confirmation information to the user.

[0310] Output: The user is notified of the reservation confirmation.

[0311] These steps ensure that the process proceeds efficiently, enabling users to receive prompt and appropriate medical services.

[0312] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0313] overview

[0314] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. Furthermore, by incorporating an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, the system provides optimal medical services according to the user's psychological state.

[0315] System configuration

[0316] server

[0317] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0318] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[0319] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[0320] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[0321] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[0322] The server includes an emotion engine that analyzes the user's emotion data and customizes the diagnosis and treatment plan.

[0323] Terminal (device used by the user)

[0324] The terminal provides an interface for the user to input diagnostic information.

[0325] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[0326] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[0327] The terminal provides a function to assist the user in making an appointment with a specialist.

[0328] The terminal transmits the user's emotion data generated by the emotion engine to the server.

[0329] User (patient)

[0330] The user inputs their own health condition and diagnosis results through the terminal.

[0331] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[0332] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[0333] The user's emotional data is appropriately evaluated by the system and a customized treatment plan is then provided.

[0334] Program processing explanation

[0335] Entering and sending diagnostic information

[0336] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[0337] The terminal formats this data and sends it to the server.

[0338] Automated review and diagnostic generation

[0339] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[0340] The server generates and provides diagnostic results and standard treatment plans to the user.

[0341] Analysis and customization with emotion engine

[0342] The device generates emotion data based on the user's input and sends it to the server. For example, it determines that the user is feeling anxious or stressed based on the input information.

[0343] The server analyzes the emotional data using an emotion engine to customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, stress management advice and mental health support will be added to the treatment plan.

[0344] Premium payment processing and notification

[0345] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[0346] The server sends the payment result to the terminal and notifies the user.

[0347] Specialist opinion and referral

[0348] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[0349] The server sends the appointment information to the specialist for confirmation.

[0350] Confirm appointment and start treatment

[0351] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[0352] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[0353] The above configuration and functions enable users to receive prompt and accurate medical services, and by incorporating an emotion engine, the system provides optimal treatment plans based on the user's psychological state.In addition, the automation of insurance payment procedures prevents delays in treatment.

[0354] The processing flow will be explained below.

[0355] Step 1:

[0356] The user inputs their own health condition and diagnosis results into the device application.

[0357] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[0358] Step 2:

[0359] The terminal formats the entered diagnostic information and sends it to the server.

[0360] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[0361] Step 3:

[0362] The server stores the received diagnostic information in a database.

[0363] Specifically, the received data is validated and stored in the appropriate database tables.

[0364] Step 4:

[0365] The server will start the automatic review.

[0366] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[0367] Step 5:

[0368] The server generates a diagnosis and a standard treatment plan.

[0369] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[0370] Step 6:

[0371] The server sends the generated diagnostic results and treatment plan to the terminal.

[0372] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[0373] Step 7:

[0374] The terminal notifies the user of the received diagnosis results and treatment plan.

[0375] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[0376] Step 8:

[0377] The user inputs their own feelings based on the diagnosis results.

[0378] Specifically, after being notified that a blood test is required as a diagnostic result, the user inputs, "I feel uneasy about this result."

[0379] Step 9:

[0380] The terminal formats the user's emotional data and sends it to the server.

[0381] Specifically, the user emotion data is converted into JSON format and sent to the server.

[0382] Step 10:

[0383] The server executes an emotion engine based on the received emotion data.

[0384] Specifically, the system analyzes emotional data to assess the user's psychological state, and if, for example, anxiety levels are high, it adjusts the treatment plan accordingly.

[0385] Step 11:

[0386] The server uses the analysis results from the emotion engine to customize a treatment plan.

[0387] Specifically, for users with high levels of anxiety, a treatment plan is generated that recommends stress management advice and relaxation techniques.

[0388] Step 12:

[0389] The server sends the customized treatment plan to the device.

[0390] Specifically, the customized treatment plan is encoded in JSON format and sent to the device.

[0391] Step 13:

[0392] The device notifies the user of the customized treatment plan.

[0393] Specifically, when a user opens the application, a pop-up notification or email notification displays the customized treatment plan.

[0394] Step 14:

[0395] The server automates the insurance payment process.

[0396] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[0397] Step 15:

[0398] The server sends a notification of payment completion to the terminal.

[0399] Specifically, the transfer success status and detailed information are sent to the terminal.

[0400] Step 16:

[0401] The terminal displays a notification to the user that the payment has been completed.

[0402] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[0403] Step 17:

[0404] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[0405] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[0406] Step 18:

[0407] The terminal displays a list of specialists to the user.

[0408] Specifically, when a user opens the application, it displays a list of specialists.

[0409] Step 19:

[0410] The user selects the desired specialist and makes a reservation.

[0411] Specifically, fill out the reservation form within the application and press the submit button.

[0412] Step 20:

[0413] The terminal sends the reservation procedure to the server.

[0414] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[0415] Step 21:

[0416] The server sends the appointment information to the specialist for confirmation.

[0417] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[0418] Step 22:

[0419] The terminal notifies the user of the reservation confirmation information.

[0420] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[0421] Through these processing steps, users can receive a quick and accurate diagnosis and treatment. Furthermore, the introduction of an emotion engine provides an optimal treatment plan based on their psychological state. Furthermore, the automated payment procedures for insurance premiums prevent delays in treatment.

[0422] Example 2

[0423] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0424] Conventional medical systems require users to input and submit diagnostic information, automatically review it, receive notifications of diagnostic results and treatment plans, automatically pay insurance premiums, and refer and schedule appointments, all individually, which takes time and effort. Furthermore, they do not provide customized treatment plans that take into account the user's psychological state, which reduces user satisfaction.

[0425] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting diagnostic information, means for transmitting the diagnostic information to the server, means for performing automatic examination based on the diagnostic information in the server, means for receiving and notifying the diagnostic results and treatment plan generated by the automatic examination, means for processing insurance premium payment based on the treatment plan, means for notifying the insurance premium payment result, means for referring to a specialist based on the treatment plan, means for supporting the appointment procedure with the specialist, means for generating user emotion data and transmitting it to the server, and means for analyzing the emotion data and customizing the diagnostic results and treatment plan. This allows users to receive prompt and accurate medical services. Furthermore, by incorporating an emotion engine, an optimal treatment plan tailored to the user's psychological state can be provided, thereby eliminating dissatisfaction.

[0426] "Diagnostic information" is information about health conditions and symptoms entered by the user.

[0427] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0428] "Automatic review" refers to the process of analyzing and making judgments based on the diagnostic information received by the server using machine learning algorithms and databases.

[0429] A "diagnosis result" is a conclusion regarding the user's health condition obtained through an automated screening.

[0430] A "treatment plan" is a proposed treatment policy or procedure based on diagnostic results.

[0431] "Premium" is an amount calculated to subsidize a portion of a user's medical expenses.

[0432] "Automatic transfer procedure" is a process in which the server automatically transfers the amount to a specified bank account.

[0433] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[0434] The "reservation procedure" is a procedure for reserving a consultation time with a specialist in advance.

[0435] "Emotion data" is data relating to a psychological state generated by an emotion engine from information input by a user.

[0436] The "emotion engine" is an algorithm and module for analyzing a user's emotional data and customizing diagnostic results and treatment plans.

[0437] overview

[0438] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. It also incorporates an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, providing optimal medical services according to the user's psychological state.

[0439] System Configuration

[0440] server

[0441] The server is a computer system that receives, stores, processes, and transmits data to other devices via a network. Specifically, it automatically reviews diagnostic information and generates diagnostic results and treatment plans. It also automatically processes insurance payments and performs specialist referrals and appointment confirmations. Furthermore, the server is equipped with an emotion engine that analyzes users' emotional data and customizes diagnostic results and treatment plans.

[0442] Terminal

[0443] The terminal is a device that provides an interface for users to input diagnostic information. It has the function of formatting the user's input information and sending it to the server. It also receives and notifies the user of diagnostic results and treatment plans, and assists in the specialist appointment process.

[0444] User

[0445] Users can input their symptoms and emotional state through a terminal, check the diagnosis results and treatment plans provided by the system, make appointments with specialists, and check the results of insurance premium payments.

[0446] Hardware and software used

[0447] Server: High-performance cloud computing services (e.g., AWS, Google Cloud)

[0448] Devices: Smartphones, tablets, PCs

[0449] Emotion engine: Machine learning algorithms (e.g. TensorFlow, PyTorch)

[0450] Specific Examples

[0451] Entering and sending diagnostic information

[0452] The user inputs their own health condition and diagnosis results into a dedicated smartphone app. For example, they might enter, "I've been feeling tired a lot recently." The device then formats this information and sends it to the server.

[0453] Automated screening and diagnostic results generation

[0454] The server automatically reviews the diagnostic information it receives. The algorithm compares it with past cases and standard diagnostic protocols to generate a diagnosis and treatment plan. For example, it may determine that the symptom of "easily tired" is a possible sign of hypothyroidism and recommend a blood test.

[0455] Analysis and customization with emotion engine

[0456] The device generates emotion data from the user's input and sends it to the server, which uses an emotion engine to analyze this data and customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, it may add stress management advice.

[0457] Processing premium payments

[0458] The server calculates the insurance premium based on the diagnosis and treatment plan, performs the automatic transfer procedure, and sends the transfer result to the terminal and notifies the user.

[0459] Specialist referrals and appointment procedures

[0460] Based on the data received by the terminal, a list of appropriate specialists is displayed to the user, and the server sends the appointment information to the specialist selected by the user for confirmation.

[0461] Prompt Sentence Examples

[0462] "A 45-year-old woman has recently been experiencing frequent fatigue and headaches. Based on this information, please suggest a diagnosis and treatment plan. Also, please use the emotion engine to take into account emotional data."

[0463] This system allows users to receive prompt and accurate medical services, and by incorporating an emotion engine, it provides optimal treatment plans based on the user's psychological state.In addition, the system automates insurance payment procedures, preventing delays in treatment.

[0464] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0465] System program processing flow

[0466] Step 1: Enter diagnostic information

[0467] Input: User inputs their health condition and symptoms

[0468] Processing: The terminal receives and formats the incoming data.

[0469] Output: Formatted diagnostic information

[0470] Specific behavior:

[0471] The user opens a dedicated smartphone app and enters information about their symptoms. For example, they might enter, "I've been feeling tired a lot recently." The device then converts this information into a format such as "Symptom: Fatigue easily" and "Start date: 2 weeks ago."

[0472] Step 2: Send diagnostic information

[0473] Input: Formatted diagnostic information

[0474] Action: The device sends formatted diagnostic information to the server.

[0475] Output: Diagnostic information sent to the server

[0476] Specific behavior:

[0477] The device sends formatted diagnostic information to the server using a security protocol (e.g., HTTPS). The information sent includes, for example, "Symptom: fatigue easily" and "Start time: 2 weeks ago."

[0478] Step 3: Automated review and diagnostic results generation

[0479] Input: Diagnostic information received by the server

[0480] Processing: The server performs automated review using machine learning algorithms

[0481] Output: Diagnostic results and treatment plan

[0482] Specific behavior:

[0483] The server compares the received diagnostic information with past cases and standard diagnostic protocols to generate a diagnosis. For example, if it determines that the symptom of "easily fatigued" is related to hypothyroidism, it generates a diagnosis result of "suspected hypothyroidism" and a treatment plan of "recommended blood test."

[0484] Step 4: Notification of diagnosis and treatment plan

[0485] Input: Diagnosis and treatment plan

[0486] Processing: The server sends the diagnosis results and treatment plan to the device.

[0487] Output: Diagnostic results and treatment plan received by the user

[0488] Specific behavior:

[0489] The server sends the generated diagnosis and treatment plan to the device, which notifies the user and displays on the screen, "Diagnosis: Suspected hypothyroidism" and "Treatment plan: Blood test recommended."

[0490] Step 5: Generate and send emotion data

[0491] Input: User input information

[0492] Processing: The device generates emotion data using the emotion recognition API and sends it to the server.

[0493] Output: Emotion data sent to the server

[0494] Specific behavior:

[0495] The device generates emotional data from the user's input. For example, the system can detect a high stress level based on the frequency of the word "fatigue" and the user's use of the word, and format the emotional data as "Stress level: high." This emotional data is then sent to the server.

[0496] Step 6: Analyze sentiment data and customize diagnosis

[0497] Input: Emotion data

[0498] Processing: The server uses an emotion engine to analyze the emotion data and customize the diagnosis and treatment plan.

[0499] Output: Customized diagnostic results and treatment plans

[0500] Specific behavior:

[0501] The server analyzes the emotion data and updates the diagnosis and treatment plan, for example, customizing it as "Diagnosis: Suspected hypothyroidism, Treatment plan: Recommend blood test + Recommend mental health support for stress management."

[0502] Step 7: Process premium payments

[0503] Input: Diagnosis and treatment plan

[0504] Processing: The server calculates the insurance premium and processes the automatic transfer.

[0505] Output: Notification of transfer completion

[0506] Specific behavior:

[0507] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the money to the user's bank account. After the transfer is complete, the result is sent to the terminal. The terminal then notifies the user that "the insurance payment has been transferred."

[0508] Step 8: Specialist referral

[0509] Input: Customized diagnostic results and treatment plans

[0510] Action: The device displays a list of appropriate specialists to the user.

[0511] Output: List of specialists and available appointments

[0512] Specific behavior:

[0513] Based on the information received from the server, the device displays a list of appropriate specialists to the user. For example, the user is provided with information such as "Thyroid specialist: Dr. Smith, available appointments: Monday 14:00-16:00."

[0514] Step 9: Book an appointment with a specialist

[0515] Input: User reservation information

[0516] Processing: The server sends the appointment information to the specialist and confirms it.

[0517] Output: Reservation confirmation information

[0518] Specific behavior:

[0519] A user makes an appointment with a specialist through a terminal. The server sends the appointment information to the specialist's system and receives confirmation from the specialist. Once the appointment is confirmed, the terminal displays a message saying, "Your appointment has been confirmed. Please see Dr. Smith at 2:00 PM on Monday."

[0520] Step 10: Confirm appointment and start treatment

[0521] Input: Reservation confirmation information

[0522] Action: User consults a specialist

[0523] Output: Examination and treatment results

[0524] Specific behavior:

[0525] The user visits the specialist at the scheduled time and receives the consultation and any necessary tests or treatment. The specialist explains the results of the consultation to the user and provides a plan for any further treatment or tests that may be required.

[0526] Through these steps, the system can provide users with fast and accurate medical services and customize the optimal treatment plan according to the user's emotional state.

[0527] (Application example 2)

[0528] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0529] In today's healthcare system, the process of entering diagnostic information, obtaining diagnostic results, receiving treatment plans, paying insurance premiums, and referrals and appointment bookings is often not smooth, resulting in delays and inaccuracies. Properly assessing users' psychological state and providing optimal treatment plans is also a major challenge. While it is particularly important for online healthcare services to properly analyze users' emotions and reflect them in diagnostic results and treatment plans, effective systems for achieving this are currently lacking.

[0530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0531] In this invention, the server includes a means for transmitting diagnostic information to the server, a means for performing automated review, and a means for utilizing an emotion engine to customize diagnostic results and treatment plans, thereby enabling the provision of highly accurate diagnostic results and treatment plans tailored to the user's emotional state.

[0532] "Diagnostic Information" is data entered by a user about their health condition or symptoms.

[0533] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0534] "Automated review" is the process by which the server uses algorithms to reference past diagnostic data and standard treatment protocols based on the diagnostic information received, to generate a diagnostic result and treatment plan.

[0535] A "treatment plan" is a set of medical procedures or instructions provided to a user based on a diagnosis.

[0536] "Premium" means money paid to cover a user's medical expenses and treatment costs.

[0537] The "emotion engine" is part of a system that analyzes emotional data based on user input and customizes diagnostic results and treatment plans.

[0538] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[0539] A "user" is a person who uses the diagnostic system to input information about their health condition and receive diagnostic results and treatment plans.

[0540] This invention is a system that efficiently inputs, transmits, and automatically reviews diagnostic information, notifies users of diagnostic results and treatment plans, processes insurance premium payments, and provides referrals and appointment procedures to specialists, while also providing optimal medical services that reflect the user's feelings.

[0541] System configuration

[0542] 1. Server

[0543] A server is a computer system that receives, stores, and processes data over a network. The specific software used is the Django framework.

[0544] Diagnostic information is received and automatically reviewed using algorithms (e.g., machine learning models) that reference previous diagnostic data and standard treatment protocols.

[0545] It generates diagnostic results and treatment plans, and also customizes them based on the user's emotional data using an emotion engine, which uses generative AI models such as TensorFlow.

[0546] The insurance premium payment is automatically made and the user is notified of the result.

[0547] An appropriate specialist will be selected from the list and referred to the user.

[0548] 2. Terminal

[0549] The terminal is a smartphone or PC that provides an interface for the user to input diagnostic information.

[0550] The diagnostic information is formatted and sent to the server, and the processing results are received and notified to the user. The specific software is a smartphone app developed using React Native.

[0551] It displays diagnostic results and treatment plans and suggests next actions for the user (such as scheduling an appointment with a specialist).

[0552] The emotion data generated by the emotion engine is transmitted to the server.

[0553] 3. Users

[0554] Users enter information about their health condition and symptoms through the device.

[0555] Review the provided diagnosis and treatment plan, select the appropriate specialist, and schedule an appointment.

[0556] Treatment is provided based on the results of insurance payment processing and treatment plan.

[0557] The emotional data is evaluated by the system and a customized treatment plan is given.

[0558] Specific examples of processing and prompt statements

[0559] As a concrete example, consider the case where a user enters into a device, "I've been feeling tired and stressed recently." The device formalizes this information and sends it to the server. The server then performs an automatic review based on the received data and generates a diagnosis of "suspected hypothyroidism." At the same time, the emotion engine recognizes high stress levels and generates a treatment plan of "blood tests, hormone therapy, and stress management advice," and notifies the user.

[0560] Example prompt sentence:

[0561] "Take user input: 'I've been feeling tired and stressed lately,' and use an emotion engine to analyze their stress level and generate a corresponding diagnosis and customized treatment plan."

[0562] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0563] Step 1:

[0564] The user inputs their health condition and symptoms into the device.

[0565] Type: "I've been feeling tired and stressed lately."

[0566] The device receives information about the user's health condition and symptoms, formats this information, and prepares it as data to send to the server.

[0567] Output: Formatted diagnostic information

[0568] Step 2:

[0569] The device sends formatted diagnostic information to the server

[0570] Input: Formatted diagnostic information

[0571] The terminal establishes a network connection to transmit the formatted diagnostic information to the server, and upon completion of the transmission, the terminal receives a transmission completion status.

[0572] Output: Diagnostic information sending completion status

[0573] Step 3:

[0574] The server performs an automatic review based on the diagnostic information received.

[0575] Input: Formatted diagnostic information

[0576] The server inputs the received diagnostic information into an algorithm and automatically diagnoses the patient by referencing past diagnostic data and standard treatment protocols. Specifically, it performs pattern recognition and comparison with a database of past cases.

[0577] Output: Diagnosis (e.g., "suspected hypothyroidism") and treatment plan (e.g., "blood tests, hormone therapy")

[0578] Step 4:

[0579] The server uses an emotion engine to customize the service based on the user's emotion data.

[0580] Input: Formatted diagnostic information and results, treatment plan

[0581] The server uses a TensorFlow-powered emotion engine to analyze the user's input and identify their emotional state (e.g., high stress levels), then generates a customized treatment plan that includes additional information such as stress management advice.

[0582] Output: Customized treatment plan

[0583] Step 5:

[0584] The server sends the diagnosis results and customized treatment plan to the device.

[0585] Input: Diagnosis results, customized treatment plan

[0586] The server transmits the diagnosis results and customized treatment plans to the terminal via the network, checking data consistency and managing communication errors.

[0587] Output: Diagnostic results and customized treatment plan sent to the device

[0588] Step 6:

[0589] The device notifies the user of the diagnosis and a customized treatment plan.

[0590] Input: Diagnostic results and customized treatment plan

[0591] The device provides an interface to display the received diagnosis results and treatment plans in an easy-to-understand manner to the user, specifically by displaying a notification pop-up and detailed information within the app.

[0592] Output: Diagnostic results communicated to the user and a customized treatment plan

[0593] Step 7:

[0594] Users book specialist appointments based on treatment plans

[0595] Input: Customized treatment plan and list of specialists

[0596] The user selects from a list of suitable specialists and schedules an appointment through the terminal, which transmits this information to the server and receives confirmation of the appointment.

[0597] Output: Specialist appointment completion status

[0598] Step 8:

[0599] The server processes the insurance premium payment

[0600] Input: Customized Treatment Plan

[0601] The server calculates the required insurance premium based on the treatment plan, automatically transfers the payment to the designated bank account, and notifies the terminal of the payment result once the transfer is complete.

[0602] Output: Insurance premium payment completion status

[0603] 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.

[0604] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0605] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0606] [Second embodiment]

[0607] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0608] 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.

[0609] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0610] 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.

[0611] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0612] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0613] 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.

[0614] 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.

[0615] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0616] 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.

[0617] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0618] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0619] overview

[0620] This invention is a system for efficiently inputting and transmitting diagnostic information, automatically reviewing it, notifying users of diagnostic results and treatment plans, automatically paying insurance premiums, and referral and appointment procedures for specialists. This system allows users to receive prompt and appropriate medical care and automates insurance payment procedures, preventing delays in treatment.

[0621] System configuration

[0622] server

[0623] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0624] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[0625] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[0626] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[0627] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[0628] Terminal (device used by the user)

[0629] The terminal provides an interface for the user to input diagnostic information.

[0630] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[0631] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[0632] The terminal provides a function to assist the user in making an appointment with a specialist.

[0633] User (patient)

[0634] The user inputs their own health condition and diagnosis results through the terminal.

[0635] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[0636] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[0637] Program processing explanation

[0638] Entering and sending diagnostic information

[0639] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[0640] The terminal formats this data and sends it to the server.

[0641] Automated review and diagnostic generation

[0642] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[0643] The server generates and provides diagnostic results and standard treatment plans to the user.

[0644] Premium payment processing and notification

[0645] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[0646] The server sends the payment result to the terminal and notifies the user.

[0647] Specialist opinion and referral

[0648] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[0649] The server sends the appointment information to the specialist and confirms the appointment.

[0650] Confirm appointment and start treatment

[0651] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[0652] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[0653] The above configuration and functions enable users to receive prompt and accurate medical services and facilitate smooth insurance payment procedures, thereby reducing delays in treatment and patient anxiety.

[0654] The processing flow will be explained below.

[0655] Step 1:

[0656] The user inputs their own health condition and diagnosis results into the device application.

[0657] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[0658] Step 2:

[0659] The terminal formats the entered diagnostic information and sends it to the server.

[0660] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[0661] Step 3:

[0662] The server stores the received diagnostic information in a database.

[0663] Specifically, the received data is validated and stored in the appropriate database tables.

[0664] Step 4:

[0665] The server will start the automatic review.

[0666] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[0667] Step 5:

[0668] The server generates a diagnosis and a standard treatment plan.

[0669] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[0670] Step 6:

[0671] The server sends the generated diagnostic results and treatment plan to the terminal.

[0672] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[0673] Step 7:

[0674] The terminal notifies the user of the received diagnosis results and treatment plan.

[0675] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[0676] Step 8:

[0677] The server automates the insurance payment process.

[0678] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[0679] Step 9:

[0680] The server sends a notification of payment completion to the terminal.

[0681] Specifically, the transfer success status and detailed information are sent to the terminal.

[0682] Step 10:

[0683] The terminal displays a notification to the user that the payment has been completed.

[0684] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[0685] Step 11:

[0686] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[0687] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[0688] Step 12:

[0689] The terminal displays a list of specialists to the user.

[0690] Specifically, when a user opens the application, it displays a list of specialists.

[0691] Step 13:

[0692] The user selects the desired specialist and makes a reservation.

[0693] Specifically, fill out the reservation form within the application and press the submit button.

[0694] Step 14:

[0695] The terminal sends the reservation procedure to the server.

[0696] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[0697] Step 15:

[0698] The server sends the appointment information to the specialist for confirmation.

[0699] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[0700] Step 16:

[0701] The terminal notifies the user of the reservation confirmation information.

[0702] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[0703] Through these processing steps, users can receive prompt and accurate diagnosis and treatment, and the automated payment process prevents delays in treatment.

[0704] Example 1

[0705] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0706] In the current medical system, patients must enter diagnostic information, receive diagnostic results, receive notification of treatment plans, pay insurance premiums, and refer to specialists and make appointments individually, which takes time and effort, and can prevent patients from receiving medical services promptly and appropriately.There is also concern that delays in insurance payment procedures could delay the start of treatment.

[0707] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0708] In this invention, the server includes a means for automatically reviewing the diagnostic information and using an algorithm that references past diagnostic data and standard treatment protocols, a means for notifying the generated diagnostic results and treatment plan, and a means for calculating insurance premiums based on the treatment plan and automatically transferring the premiums to a designated bank account. This enables rapid review of diagnostic information, provision of diagnostic results and treatment plans, and automatic payment of insurance premiums, allowing patients to receive medical services efficiently and without delay.

[0709] "Diagnosis information" is information entered by the user regarding their own poor physical condition or symptoms.

[0710] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0711] "Automated review" is the process of using an algorithm to perform a diagnosis based on received diagnostic information and generate a result.

[0712] An "algorithm" is a computational method that analyzes diagnostic information and matches it with historical diagnostic data and standard treatment protocols.

[0713] A "diagnostic result" is a specific diagnostic conclusion generated by an automated review.

[0714] A "treatment plan" is a specific treatment step and prescription proposed based on diagnostic results.

[0715] "Premium" is the payment amount calculated based on the diagnosis and treatment plan.

[0716] "Direct deposit" is the process of transferring funds electronically to a designated bank account.

[0717] A "specialist" is a doctor who is well-versed and certified in a particular field.

[0718] The "reservation procedure" is the procedure for confirming the date and time of an appointment with a specialist.

[0719] A "generative AI model" is a model that uses artificial intelligence to analyze diagnostic information and automatically review and generate diagnostic results.

[0720] overview

[0721] This invention is a system for efficiently inputting, transmitting, and automatically reviewing diagnostic information, notifying diagnostic results and treatment plans, automatically paying insurance premiums, and processing specialist referrals and appointment procedures. This system is designed to enable users to receive prompt and appropriate medical care by using generative AI models to analyze diagnostic information and automate various procedures.

[0722] Hardware and Software Used

[0723] server:

[0724] A server is a computer system that receives, stores, processes data, and sends the results to other devices over a network. For example, this could include a database management system or a diagnostic algorithm running on a Linux server.

[0725] Device:

[0726] The terminal is the device used by the user, such as a smartphone, tablet, or laptop, that provides the user interface and assists in entering diagnostic information, displaying received results, and scheduling appointments with specialists.

[0727] Generative AI models:

[0728] An artificial intelligence model for analyzing diagnostic information and generating diagnostic results and treatment plans, using machine learning frameworks such as TensorFlow and PyTorch.

[0729] Processing flow

[0730] 1. The user uses the device interface to input their own health condition and diagnosis results. For example, the user enters "I've been feeling tired a lot recently" in the text box.

[0731] 2. The device formats this information (e.g., in JSON format) and sends it to the server.

[0732] 3. The server uses the received data to perform an automated review using a generative AI model. For example, it uses past diagnostic data to determine whether "easily fatigued" is an early symptom of hypothyroidism.

[0733] 4. The server generates the diagnosis and standard treatment plan (e.g., blood tests and thyroid hormone replacement therapy recommendations) and sends them to the device.

[0734] 5. The device displays the diagnosis and treatment plan to the user.

[0735] 6. The server calculates the insurance premium based on the treatment plan and uses a financial API to automatically transfer the payment to the bank account specified by the user.

[0736] 7. The server notifies the terminal of the transfer result so that the user can check it.

[0737] 8. The terminal displays a list of appropriate specialists to the user, allowing the user to select the desired specialist and make an appointment.

[0738] 9. The server sends the reservation information to the specialist, and once confirmation is received, it sends the reservation confirmation information to the terminal.

[0739] 10. The terminal displays the reservation confirmation information to the user.

[0740] 11. The user visits the specialist at the specified date and time and begins treatment based on the diagnosis results.

[0741] Examples of concrete examples and prompts

[0742] Specific examples

[0743] 1. The user types "I've been feeling very tired lately" into the device and sends it.

[0744] 2. The device sends this information to the server.

[0745] 3. The server analyzes the received data and generates a diagnosis of suspected hypothyroidism and a treatment plan.

[0746] 4. The server sends the result to the terminal and notifies the user.

[0747] 5. The server calculates the insurance premium based on the treatment plan and transfers the amount to the specified bank account.

[0748] 6. The device notifies the user of the results and provides a list of specialists.

[0749] 7. The user selects the specialist of their choice and makes an appointment.

[0750] 8. The server sends the appointment information to the specialist for confirmation.

[0751] Prompt Sentence Examples

[0752] "Have you been feeling tired more often recently?"

[0753] "A diagnosis and treatment plan have been generated. Please review the details."

[0754] "Insurance premium payment completed. Please check the results."

[0755] "Here's a list of suitable specialists. Please select one if you would like to make an appointment."

[0756] The system allows users to receive medical services efficiently and without delay, and the use of generative AI models improves the accuracy of diagnostic results and treatment plans, further enhancing user convenience.

[0757] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0758] Step 1:

[0759] The user uses the device interface to input diagnostic information about their health condition or symptoms. For example, the user might type, "I've been feeling tired a lot recently" into a text box. The input data is formatted and ready to be recognized by the system.

[0760] Step 2:

[0761] The device converts the diagnostic information entered into a standard format such as JSON and sends it to the server. The formatted data is then transferred to the server as an HTTP request.

[0762] Step 3:

[0763] The server stores the received diagnostic information in a database and starts analysis by accessing the data repository. Specifically, it executes an INSERT query in the database.

[0764] Step 4:

[0765] The server performs an automated review based on the diagnostic information. It uses a generative AI model to analyze the diagnostic information and compare it with past diagnostic data and standard treatment protocols. For example, it compares it with past patient data with the symptom of "easily fatigued" and evaluates the relevance. The input is the diagnostic information, and the output is the diagnostic results and treatment plan.

[0766] Step 5:

[0767] The server generates diagnostic results and treatment plans, which are packaged in JSON format and sent to the device. For example, the diagnostic results for hypothyroidism and the treatment plan for "thyroid hormone replacement therapy" are included. This allows the user to check the diagnostic results.

[0768] Step 6:

[0769] The terminal displays the diagnosis results and treatment plan received on the user interface. For example, the diagnosis name and recommended treatment details are displayed. Specifically, the data is displayed in the UI component.

[0770] Step 7:

[0771] The server calculates insurance premiums based on diagnosis results and treatment plans. It uses a financial API to calculate insurance premiums in real time and automatically transfers the funds to a designated bank account. The input is diagnosis results and insurance information, and the output is the transfer results.

[0772] Step 8:

[0773] The server generates the transfer result and sends it to the terminal in JSON format, such as "$200 has been transferred to the specified bank account." The terminal receives this and makes it available.

[0774] Step 9:

[0775] The terminal notifies the user of the payment result. For example, a message such as "Insurance payment has been completed. Please check the result" is displayed. Specifically, the message is displayed in the notification component.

[0776] Step 10:

[0777] The device displays a list of appropriate specialists to the user, for example, a list of categories such as "endocrinologists," and provides an interface for the user to select the desired specialist.

[0778] Step 11:

[0779] When a user selects a specialist and wishes to make an appointment, they complete the reservation procedure through their terminal. For example, they enter "I would like to make an appointment with an endocrinologist" into the reservation form. The input is sent to the server.

[0780] Step 12:

[0781] The server sends the appointment information to the specialist and confirms it. For example, it checks the appointment schedule and generates appointment confirmation information. The input is the user's appointment information, and the output is the appointment confirmation information.

[0782] Step 13:

[0783] The device displays reservation confirmation information to the user. For example, a message like "Reservation confirmed. Please confirm the date, time, and location" is displayed. Specifically, the schedule information is displayed in the calendar component.

[0784] Step 14:

[0785] The user visits a specialist at a specified date and time and begins treatment based on the diagnosis. For example, a user might visit a designated endocrinologist to receive treatment for hypothyroidism.

[0786] (Application example 1)

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

[0788] In modern healthcare services, to ensure patients receive prompt and appropriate diagnoses and treatment, it is necessary to streamline a series of processes, from entering and submitting diagnostic information to automatic review, notification of diagnostic results, insurance payment, specialist referrals, and appointment procedures. However, when these processes are performed manually, they require a lot of time and effort, resulting in treatment delays and patient anxiety. Furthermore, if medical data security is not ensured, there is a risk that patient privacy will be compromised. To solve these issues, an efficient and secure healthcare service delivery system is required.

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

[0790] In this invention, the server includes a means for inputting diagnostic information, a means for transmitting the diagnostic information to the server, a means for performing an automatic review based on the diagnostic information in the server, a means for encrypting the diagnostic information and transmitting it to the server, a means for performing an automatic review using an AI model and generating a diagnostic result, a means for processing insurance premium payments via an online payment system, and a means for synchronizing appointment information with a calendar. This enables secure transmission of diagnostic information, automated generation of diagnostic results, prompt insurance premium payment processing, and smooth appointment procedures with specialists.

[0791] "Diagnostic information" refers to information entered by a patient about their health condition or symptoms.

[0792] A "server" is a computer system that receives, stores, processes, and transmits data over a network.

[0793] "Automated review" refers to the process of using algorithms or AI models based on input diagnostic information to generate diagnostic results without manual intervention.

[0794] "Diagnostic result" means a medical judgment or diagnosis of a patient's symptoms generated by an automated review means.

[0795] A "treatment plan" refers to the specific treatment content and procedures that a patient should undergo based on the diagnostic results.

[0796] "Premiums" are the money paid by patients to cover medical expenses and are calculated based on automated screening results and treatment plans.

[0797] An "online payment system" is a system that automatically conducts monetary transactions via the Internet.

[0798] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[0799] "Appointment booking" refers to the process for booking a date and time to see a specialist.

[0800] "Calendar synchronization" means linking reservation information and other data with a digital calendar system to maintain consistency of information.

[0801] "Encryption" is a technique for converting data into a format that cannot be deciphered by third parties.

[0802] An "AI model" is a model that uses artificial intelligence algorithms to automatically extract patterns and knowledge from data and make diagnoses and predictions.

[0803] System configuration

[0804] A system for implementing this invention includes the following major components:

[0805] 1. Terminal (device used by the user)

[0806] 2. Server

[0807] 3. Network

[0808] Terminal

[0809] The terminal is a device that provides an interface for users to input diagnostic information and send it to the server. The terminal is a mobile device that can connect to the Internet, such as a smartphone or tablet. The terminal has the following functions:

[0810] Entering and sending encrypted diagnostic information (using encryption technology such as AES-256)

[0811] Notification of diagnosis and treatment plan

[0812] Displaying a list of specialists and assisting with appointment booking (Calendar synchronization using Google Calendar API)

[0813] server

[0814] The server is a computer system that receives data sent from the terminals via the network and performs automatic review and processing. The server processes the data using the following software:

[0815] Backend: Node.js and Express

[0816] Database: Use MongoDB to manage health data

[0817] AI diagnostic model: Automated screening using TensorFlow

[0818] Online payment system: Stripe API or PayPal API

[0819] Processing Details

[0820] Entering and sending diagnostic information

[0821] Users use the device to enter their diagnostic information, including details of their illness and symptoms, which is then securely transmitted to the server using AES-256 encryption.

[0822] Automated review and diagnostic generation

[0823] The server inputs the received diagnostic information into an AI diagnostic model (TensorFlow) for automatic review. It generates diagnostic results and a treatment plan using an algorithm that references past diagnostic data and standard treatment protocols, and sends them to the device.

[0824] Insurance premium payment processing

[0825] The server calculates the insurance premium based on the diagnosis results and treatment plan, and automatically processes the payment using an online payment system (such as Stripe API or PayPal API). The results are then sent to the terminal.

[0826] Specialist referrals and appointments

[0827] Based on the information received from the server, the device displays a list of appropriate specialists to the user. Once the user selects a specialist, the device uses the Google Calendar API to synchronize the appointment information with the calendar and assist with the appointment process.

[0828] Examples and prompts

[0829] Examples:

[0830] User input: "I've been feeling tired and dizzy lately."

[0831] The AI ​​model says: "These symptoms may indicate hypothyroidism. We'll provide a treatment plan based on the diagnosis and a referral specialist."

[0832] Payment procedure: "Insurance premium calculation completed. 2500 yen has been automatically paid."

[0833] Example prompt for a generative AI model:

[0834] "Create an application that uses an automated diagnostic model to generate a diagnosis based on the health information entered by the user, and then calculates insurance premiums and processes payments based on the results. It also refers users to the appropriate specialist and automatically schedules appointments."

[0835] As a result, the present invention can provide efficient and secure medical services and reduce the burden on patients.

[0836] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0837] Step 1:

[0838] User enters diagnostic information

[0839] Input: The user uses the terminal to input diagnostic information (e.g., fatigue, dizziness).

[0840] Specific operation: The user uses a smartphone or tablet to enter their symptoms into the input form of a dedicated application.

[0841] Output: Entered diagnostic information is saved to the terminal.

[0842] Step 2:

[0843] The device encrypts the diagnostic information and sends it to the server

[0844] Input: The diagnostic information entered in Step 1.

[0845] Data processing: Diagnostic information is encrypted using AES-256 encryption technology.

[0846] Specific operation: The terminal application encrypts the entered diagnostic information and sends it to the server using a secure communication protocol (HTTPS).

[0847] Output: Encrypted diagnostic information is sent to the server.

[0848] Step 3:

[0849] The server performs an automatic review based on the diagnostic information.

[0850] Input: Diagnostic information sent encrypted.

[0851] Data processing: The server decrypts the encrypted data and converts it into a format that can be input into the AI ​​diagnostic model (TensorFlow).

[0852] What it does: The server decrypts the diagnostic information and runs the AI ​​model using historical diagnostic data and standard treatment protocols.

[0853] Output: Diagnosis and treatment plan generated by the AI ​​diagnostic model.

[0854] Step 4:

[0855] The server sends the diagnosis results and treatment plan to the device.

[0856] Input: The diagnosis and treatment plan generated in step 3.

[0857] Specific operation: The server converts the diagnosis results and treatment plan into a data format (such as JSON) and sends them to the terminal.

[0858] Output: The diagnosis and treatment plan are sent to the device.

[0859] Step 5:

[0860] The device notifies you of the diagnosis and treatment plan

[0861] Input: Diagnosis and treatment plan submitted in step 4.

[0862] What it does: The device application uses notifications to display diagnostic results and treatment plans to the user.

[0863] Output: The user is informed of the diagnosis and treatment plan.

[0864] Step 6:

[0865] The server calculates and pays the insurance premiums.

[0866] Input: The treatment plan generated in step 4.

[0867] Data calculation: Calculates insurance premiums based on treatment plans and executes payment procedures via online payment systems (Stripe API or PayPal API).

[0868] Specific operation: The server analyzes the treatment plan, calculates the required insurance premium, and then calls the API of the online payment system to automatically make the payment.

[0869] Output: Premium payment result.

[0870] Step 7:

[0871] The server sends the insurance premium payment result to the terminal

[0872] Input: Premium payment results obtained in step 6.

[0873] Specific operation: The server converts the insurance premium payment results into a data format (such as JSON) that is easy for the user to understand and sends it to the terminal.

[0874] Output: The insurance premium payment result is sent to the terminal.

[0875] Step 8:

[0876] The terminal notifies the result of the insurance premium payment

[0877] Input: Premium payment result sent in step 7.

[0878] Specific operation: The terminal application uses the notification function to display the insurance premium payment result to the user.

[0879] Output: The user is notified of the insurance premium payment result.

[0880] Step 9:

[0881] The device displays a list of specialists and assists with the appointment process

[0882] Input: Treatment plan and specialist information submitted in step 4.

[0883] What it does: The device application displays a list of appropriate specialists based on the treatment plan, helps the user schedule an appointment with the selected specialist, and synchronizes the appointment information using the Google Calendar API.

[0884] Output: The user is presented with a list of specialists and is assisted in the appointment process.

[0885] Step 10:

[0886] The server sends the appointment information to the specialist

[0887] Input: Reservation information generated in step 9.

[0888] Specific operation: The server sends the appointment information to the specialist's system and confirms the appointment.

[0889] Output: Appointment information is sent to the specialist and confirmed.

[0890] Step 11:

[0891] The device will notify you of the reservation confirmation information

[0892] Input: Reservation information confirmed in step 10.

[0893] Specific behavior: The device application uses the notification function to display reservation confirmation information to the user.

[0894] Output: The user is notified of the reservation confirmation.

[0895] These steps ensure that the process proceeds efficiently, enabling users to receive prompt and appropriate medical services.

[0896] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0897] overview

[0898] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. Furthermore, by incorporating an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, the system provides optimal medical services according to the user's psychological state.

[0899] System configuration

[0900] server

[0901] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[0902] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[0903] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[0904] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[0905] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[0906] The server includes an emotion engine that analyzes the user's emotion data and customizes the diagnosis and treatment plan.

[0907] Terminal (device used by the user)

[0908] The terminal provides an interface for the user to input diagnostic information.

[0909] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[0910] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[0911] The terminal provides a function to assist the user in making an appointment with a specialist.

[0912] The terminal transmits the user's emotion data generated by the emotion engine to the server.

[0913] User (patient)

[0914] The user inputs their own health condition and diagnosis results through the terminal.

[0915] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[0916] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[0917] The user's emotional data is appropriately evaluated by the system and a customized treatment plan is then provided.

[0918] Program processing explanation

[0919] Entering and sending diagnostic information

[0920] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[0921] The terminal formats this data and sends it to the server.

[0922] Automated review and diagnostic generation

[0923] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[0924] The server generates and provides diagnostic results and standard treatment plans to the user.

[0925] Analysis and customization with emotion engine

[0926] The device generates emotion data based on the user's input and sends it to the server. For example, it determines that the user is feeling anxious or stressed based on the input information.

[0927] The server analyzes the emotional data using an emotion engine to customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, stress management advice and mental health support will be added to the treatment plan.

[0928] Premium payment processing and notification

[0929] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[0930] The server sends the payment result to the terminal and notifies the user.

[0931] Specialist opinion and referral

[0932] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[0933] The server sends the appointment information to the specialist for confirmation.

[0934] Confirm appointment and start treatment

[0935] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[0936] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[0937] The above configuration and functions enable users to receive prompt and accurate medical services, and by incorporating an emotion engine, the system provides optimal treatment plans based on the user's psychological state.In addition, the automation of insurance payment procedures prevents delays in treatment.

[0938] The processing flow will be explained below.

[0939] Step 1:

[0940] The user inputs their own health condition and diagnosis results into the device application.

[0941] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[0942] Step 2:

[0943] The terminal formats the entered diagnostic information and sends it to the server.

[0944] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[0945] Step 3:

[0946] The server stores the received diagnostic information in a database.

[0947] Specifically, the received data is validated and stored in the appropriate database tables.

[0948] Step 4:

[0949] The server will start the automatic review.

[0950] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[0951] Step 5:

[0952] The server generates a diagnosis and a standard treatment plan.

[0953] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[0954] Step 6:

[0955] The server sends the generated diagnostic results and treatment plan to the terminal.

[0956] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[0957] Step 7:

[0958] The terminal notifies the user of the received diagnosis results and treatment plan.

[0959] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[0960] Step 8:

[0961] The user inputs their own feelings based on the diagnosis results.

[0962] Specifically, after being notified that a blood test is required as a diagnostic result, the user inputs, "I feel uneasy about this result."

[0963] Step 9:

[0964] The terminal formats the user's emotional data and sends it to the server.

[0965] Specifically, the user emotion data is converted into JSON format and sent to the server.

[0966] Step 10:

[0967] The server executes an emotion engine based on the received emotion data.

[0968] Specifically, the system analyzes emotional data to assess the user's psychological state, and if, for example, anxiety levels are high, it adjusts the treatment plan accordingly.

[0969] Step 11:

[0970] The server uses the analysis results from the emotion engine to customize a treatment plan.

[0971] Specifically, for users with high levels of anxiety, a treatment plan is generated that recommends stress management advice and relaxation techniques.

[0972] Step 12:

[0973] The server sends the customized treatment plan to the device.

[0974] Specifically, the customized treatment plan is encoded in JSON format and sent to the device.

[0975] Step 13:

[0976] The device notifies the user of the customized treatment plan.

[0977] Specifically, when a user opens the application, a pop-up notification or email notification displays the customized treatment plan.

[0978] Step 14:

[0979] The server automates the insurance payment process.

[0980] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[0981] Step 15:

[0982] The server sends a notification of payment completion to the terminal.

[0983] Specifically, the transfer success status and detailed information are sent to the terminal.

[0984] Step 16:

[0985] The terminal displays a notification to the user that the payment has been completed.

[0986] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[0987] Step 17:

[0988] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[0989] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[0990] Step 18:

[0991] The terminal displays a list of specialists to the user.

[0992] Specifically, when a user opens the application, it displays a list of specialists.

[0993] Step 19:

[0994] The user selects the desired specialist and makes a reservation.

[0995] Specifically, fill out the reservation form within the application and press the submit button.

[0996] Step 20:

[0997] The terminal sends the reservation procedure to the server.

[0998] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[0999] Step 21:

[1000] The server sends the appointment information to the specialist for confirmation.

[1001] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[1002] Step 22:

[1003] The terminal notifies the user of the reservation confirmation information.

[1004] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[1005] Through these processing steps, users can receive a quick and accurate diagnosis and treatment. Furthermore, the introduction of an emotion engine provides an optimal treatment plan based on their psychological state. Furthermore, the automated payment procedures for insurance premiums prevent delays in treatment.

[1006] Example 2

[1007] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1008] Conventional medical systems require users to input and submit diagnostic information, automatically review it, receive notifications of diagnostic results and treatment plans, automatically pay insurance premiums, and refer and schedule appointments, all individually, which takes time and effort. Furthermore, they do not provide customized treatment plans that take into account the user's psychological state, which reduces user satisfaction.

[1009] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting diagnostic information, means for transmitting the diagnostic information to the server, means for performing automatic examination based on the diagnostic information in the server, means for receiving and notifying the diagnostic results and treatment plan generated by the automatic examination, means for processing insurance premium payment based on the treatment plan, means for notifying the insurance premium payment result, means for referring to a specialist based on the treatment plan, means for supporting the appointment procedure with the specialist, means for generating user emotion data and transmitting it to the server, and means for analyzing the emotion data and customizing the diagnostic results and treatment plan. This allows users to receive prompt and accurate medical services. Furthermore, by incorporating an emotion engine, an optimal treatment plan tailored to the user's psychological state can be provided, thereby eliminating dissatisfaction.

[1010] "Diagnostic information" is information about health conditions and symptoms entered by the user.

[1011] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1012] "Automatic review" refers to the process of analyzing and making judgments based on the diagnostic information received by the server using machine learning algorithms and databases.

[1013] A "diagnosis result" is a conclusion regarding the user's health condition obtained through an automated screening.

[1014] A "treatment plan" is a proposed treatment policy or procedure based on diagnostic results.

[1015] "Premium" is an amount calculated to subsidize a portion of a user's medical expenses.

[1016] "Automatic transfer procedure" is a process in which the server automatically transfers the amount to a specified bank account.

[1017] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[1018] The "reservation procedure" is a procedure for reserving a consultation time with a specialist in advance.

[1019] "Emotion data" is data relating to a psychological state generated by an emotion engine from information input by a user.

[1020] The "emotion engine" is an algorithm and module for analyzing a user's emotional data and customizing diagnostic results and treatment plans.

[1021] overview

[1022] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. It also incorporates an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, providing optimal medical services according to the user's psychological state.

[1023] System Configuration

[1024] server

[1025] The server is a computer system that receives, stores, processes, and transmits data to other devices via a network. Specifically, it automatically reviews diagnostic information and generates diagnostic results and treatment plans. It also automatically processes insurance payments and performs specialist referrals and appointment confirmations. Furthermore, the server is equipped with an emotion engine that analyzes users' emotional data and customizes diagnostic results and treatment plans.

[1026] Terminal

[1027] The terminal is a device that provides an interface for users to input diagnostic information. It has the function of formatting the user's input information and sending it to the server. It also receives and notifies the user of diagnostic results and treatment plans, and assists in the specialist appointment process.

[1028] User

[1029] Users can input their symptoms and emotional state through a terminal, check the diagnosis results and treatment plans provided by the system, make appointments with specialists, and check the results of insurance premium payments.

[1030] Hardware and software used

[1031] Server: High-performance cloud computing services (e.g., AWS, Google Cloud)

[1032] Devices: Smartphones, tablets, PCs

[1033] Emotion engine: Machine learning algorithms (e.g. TensorFlow, PyTorch)

[1034] Specific Examples

[1035] Entering and sending diagnostic information

[1036] The user inputs their own health condition and diagnosis results into a dedicated smartphone app. For example, they might enter, "I've been feeling tired a lot recently." The device then formats this information and sends it to the server.

[1037] Automated screening and diagnostic results generation

[1038] The server automatically reviews the diagnostic information it receives. The algorithm compares it with past cases and standard diagnostic protocols to generate a diagnosis and treatment plan. For example, it may determine that the symptom of "easily tired" is a possible sign of hypothyroidism and recommend a blood test.

[1039] Analysis and customization with emotion engine

[1040] The device generates emotion data from the user's input and sends it to the server, which uses an emotion engine to analyze this data and customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, it may add stress management advice.

[1041] Processing premium payments

[1042] The server calculates the insurance premium based on the diagnosis and treatment plan, performs the automatic transfer procedure, and sends the transfer result to the terminal and notifies the user.

[1043] Specialist referrals and appointment procedures

[1044] Based on the data received by the terminal, a list of appropriate specialists is displayed to the user, and the server sends the appointment information to the specialist selected by the user for confirmation.

[1045] Prompt Sentence Examples

[1046] "A 45-year-old woman has recently been experiencing frequent fatigue and headaches. Based on this information, please suggest a diagnosis and treatment plan. Also, please use the emotion engine to take into account emotional data."

[1047] This system allows users to receive prompt and accurate medical services, and by incorporating an emotion engine, it provides optimal treatment plans based on the user's psychological state.In addition, the system automates insurance payment procedures, preventing delays in treatment.

[1048] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1049] System program processing flow

[1050] Step 1: Enter diagnostic information

[1051] Input: User inputs their health condition and symptoms

[1052] Processing: The terminal receives and formats the incoming data.

[1053] Output: Formatted diagnostic information

[1054] Specific behavior:

[1055] The user opens a dedicated smartphone app and enters information about their symptoms. For example, they might enter, "I've been feeling tired a lot recently." The device then converts this information into a format such as "Symptom: Fatigue easily" and "Start date: 2 weeks ago."

[1056] Step 2: Send diagnostic information

[1057] Input: Formatted diagnostic information

[1058] Action: The device sends formatted diagnostic information to the server.

[1059] Output: Diagnostic information sent to the server

[1060] Specific behavior:

[1061] The device sends formatted diagnostic information to the server using a security protocol (e.g., HTTPS). The information sent includes, for example, "Symptom: fatigue easily" and "Start time: 2 weeks ago."

[1062] Step 3: Automated review and diagnostic results generation

[1063] Input: Diagnostic information received by the server

[1064] Processing: The server performs automated review using machine learning algorithms

[1065] Output: Diagnostic results and treatment plan

[1066] Specific behavior:

[1067] The server compares the received diagnostic information with past cases and standard diagnostic protocols to generate a diagnosis. For example, if it determines that the symptom of "easily fatigued" is related to hypothyroidism, it generates a diagnosis result of "suspected hypothyroidism" and a treatment plan of "recommended blood test."

[1068] Step 4: Notification of diagnosis and treatment plan

[1069] Input: Diagnosis and treatment plan

[1070] Processing: The server sends the diagnosis results and treatment plan to the device.

[1071] Output: Diagnostic results and treatment plan received by the user

[1072] Specific behavior:

[1073] The server sends the generated diagnosis and treatment plan to the device, which notifies the user and displays on the screen, "Diagnosis: Suspected hypothyroidism" and "Treatment plan: Blood test recommended."

[1074] Step 5: Generate and send emotion data

[1075] Input: User input information

[1076] Processing: The device generates emotion data using the emotion recognition API and sends it to the server.

[1077] Output: Emotion data sent to the server

[1078] Specific behavior:

[1079] The device generates emotional data from the user's input. For example, the system can detect a high stress level based on the frequency of the word "fatigue" and the user's use of the word, and format the emotional data as "Stress level: high." This emotional data is then sent to the server.

[1080] Step 6: Analyze sentiment data and customize diagnosis

[1081] Input: Emotion data

[1082] Processing: The server uses an emotion engine to analyze the emotion data and customize the diagnosis and treatment plan.

[1083] Output: Customized diagnostic results and treatment plans

[1084] Specific behavior:

[1085] The server analyzes the emotion data and updates the diagnosis and treatment plan, for example, customizing it as "Diagnosis: Suspected hypothyroidism, Treatment plan: Recommend blood test + Recommend mental health support for stress management."

[1086] Step 7: Process premium payments

[1087] Input: Diagnosis and treatment plan

[1088] Processing: The server calculates the insurance premium and processes the automatic transfer.

[1089] Output: Notification of transfer completion

[1090] Specific behavior:

[1091] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the money to the user's bank account. After the transfer is complete, the result is sent to the terminal. The terminal then notifies the user that "the insurance payment has been transferred."

[1092] Step 8: Specialist referral

[1093] Input: Customized diagnostic results and treatment plans

[1094] Action: The device displays a list of appropriate specialists to the user.

[1095] Output: List of specialists and available appointments

[1096] Specific behavior:

[1097] Based on the information received from the server, the device displays a list of appropriate specialists to the user. For example, the user is provided with information such as "Thyroid specialist: Dr. Smith, available appointments: Monday 14:00-16:00."

[1098] Step 9: Book an appointment with a specialist

[1099] Input: User reservation information

[1100] Processing: The server sends the appointment information to the specialist and confirms it.

[1101] Output: Reservation confirmation information

[1102] Specific behavior:

[1103] A user makes an appointment with a specialist through a terminal. The server sends the appointment information to the specialist's system and receives confirmation from the specialist. Once the appointment is confirmed, the terminal displays a message saying, "Your appointment has been confirmed. Please see Dr. Smith at 2:00 PM on Monday."

[1104] Step 10: Confirm appointment and start treatment

[1105] Input: Reservation confirmation information

[1106] Action: User consults a specialist

[1107] Output: Examination and treatment results

[1108] Specific behavior:

[1109] The user visits the specialist at the scheduled time and receives the consultation and any necessary tests or treatment. The specialist explains the results of the consultation to the user and provides a plan for any further treatment or tests that may be required.

[1110] Through these steps, the system can provide users with fast and accurate medical services and customize the optimal treatment plan according to the user's emotional state.

[1111] (Application example 2)

[1112] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1113] In today's healthcare system, the process of entering diagnostic information, obtaining diagnostic results, receiving treatment plans, paying insurance premiums, and referrals and appointment bookings is often not smooth, resulting in delays and inaccuracies. Properly assessing users' psychological state and providing optimal treatment plans is also a major challenge. While it is particularly important for online healthcare services to properly analyze users' emotions and reflect them in diagnostic results and treatment plans, effective systems for achieving this are currently lacking.

[1114] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1115] In this invention, the server includes a means for transmitting diagnostic information to the server, a means for performing automated review, and a means for utilizing an emotion engine to customize diagnostic results and treatment plans, thereby enabling the provision of highly accurate diagnostic results and treatment plans tailored to the user's emotional state.

[1116] "Diagnostic Information" is data entered by a user about their health condition or symptoms.

[1117] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1118] "Automated review" is the process by which the server uses algorithms to reference past diagnostic data and standard treatment protocols based on the diagnostic information received, to generate a diagnostic result and treatment plan.

[1119] A "treatment plan" is a set of medical procedures or instructions provided to a user based on a diagnosis.

[1120] "Premium" means money paid to cover a user's medical expenses and treatment costs.

[1121] The "emotion engine" is part of a system that analyzes emotional data based on user input and customizes diagnostic results and treatment plans.

[1122] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[1123] A "user" is a person who uses the diagnostic system to input information about their health condition and receive diagnostic results and treatment plans.

[1124] This invention is a system that efficiently inputs, transmits, and automatically reviews diagnostic information, notifies users of diagnostic results and treatment plans, processes insurance premium payments, and provides referrals and appointment procedures to specialists, while also providing optimal medical services that reflect the user's feelings.

[1125] System configuration

[1126] 1. Server

[1127] A server is a computer system that receives, stores, and processes data over a network. The specific software used is the Django framework.

[1128] Diagnostic information is received and automatically reviewed using algorithms (e.g., machine learning models) that reference previous diagnostic data and standard treatment protocols.

[1129] It generates diagnostic results and treatment plans, and also customizes them based on the user's emotional data using an emotion engine, which uses generative AI models such as TensorFlow.

[1130] The insurance premium payment is automatically made and the user is notified of the result.

[1131] An appropriate specialist will be selected from the list and referred to the user.

[1132] 2. Terminal

[1133] The terminal is a smartphone or PC that provides an interface for the user to input diagnostic information.

[1134] The diagnostic information is formatted and sent to the server, and the processing results are received and notified to the user. The specific software is a smartphone app developed using React Native.

[1135] It displays diagnostic results and treatment plans and suggests next actions for the user (such as scheduling an appointment with a specialist).

[1136] The emotion data generated by the emotion engine is transmitted to the server.

[1137] 3. Users

[1138] Users enter information about their health condition and symptoms through the device.

[1139] Review the provided diagnosis and treatment plan, select the appropriate specialist, and schedule an appointment.

[1140] Treatment is provided based on the results of insurance payment processing and treatment plan.

[1141] The emotional data is evaluated by the system and a customized treatment plan is given.

[1142] Specific examples of processing and prompt statements

[1143] As a concrete example, consider the case where a user enters into a device, "I've been feeling tired and stressed recently." The device formalizes this information and sends it to the server. The server then performs an automatic review based on the received data and generates a diagnosis of "suspected hypothyroidism." At the same time, the emotion engine recognizes high stress levels and generates a treatment plan of "blood tests, hormone therapy, and stress management advice," and notifies the user.

[1144] Example prompt sentence:

[1145] "Take user input: 'I've been feeling tired and stressed lately,' and use an emotion engine to analyze their stress level and generate a corresponding diagnosis and customized treatment plan."

[1146] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1147] Step 1:

[1148] The user inputs their health condition and symptoms into the device.

[1149] Type: "I've been feeling tired and stressed lately."

[1150] The device receives information about the user's health condition and symptoms, formats this information, and prepares it as data to send to the server.

[1151] Output: Formatted diagnostic information

[1152] Step 2:

[1153] The device sends formatted diagnostic information to the server

[1154] Input: Formatted diagnostic information

[1155] The terminal establishes a network connection to transmit the formatted diagnostic information to the server, and upon completion of the transmission, the terminal receives a transmission completion status.

[1156] Output: Diagnostic information sending completion status

[1157] Step 3:

[1158] The server performs an automatic review based on the diagnostic information received.

[1159] Input: Formatted diagnostic information

[1160] The server inputs the received diagnostic information into an algorithm and automatically diagnoses the patient by referencing past diagnostic data and standard treatment protocols. Specifically, it performs pattern recognition and comparison with a database of past cases.

[1161] Output: Diagnosis (e.g., "suspected hypothyroidism") and treatment plan (e.g., "blood tests, hormone therapy")

[1162] Step 4:

[1163] The server uses an emotion engine to customize the service based on the user's emotion data.

[1164] Input: Formatted diagnostic information and results, treatment plan

[1165] The server uses a TensorFlow-powered emotion engine to analyze the user's input and identify their emotional state (e.g., high stress levels), then generates a customized treatment plan that includes additional information such as stress management advice.

[1166] Output: Customized treatment plan

[1167] Step 5:

[1168] The server sends the diagnosis results and customized treatment plan to the device.

[1169] Input: Diagnosis results, customized treatment plan

[1170] The server transmits the diagnosis results and customized treatment plans to the terminal via the network, checking data consistency and managing communication errors.

[1171] Output: Diagnostic results and customized treatment plan sent to the device

[1172] Step 6:

[1173] The device notifies the user of the diagnosis and a customized treatment plan.

[1174] Input: Diagnostic results and customized treatment plan

[1175] The device provides an interface to display the received diagnosis results and treatment plans in an easy-to-understand manner to the user, specifically by displaying a notification pop-up and detailed information within the app.

[1176] Output: Diagnostic results communicated to the user and a customized treatment plan

[1177] Step 7:

[1178] Users book specialist appointments based on treatment plans

[1179] Input: Customized treatment plan and list of specialists

[1180] The user selects from a list of suitable specialists and schedules an appointment through the terminal, which transmits this information to the server and receives confirmation of the appointment.

[1181] Output: Specialist appointment completion status

[1182] Step 8:

[1183] The server processes the insurance premium payment

[1184] Input: Customized Treatment Plan

[1185] The server calculates the required insurance premium based on the treatment plan, automatically transfers the payment to the designated bank account, and notifies the terminal of the payment result once the transfer is complete.

[1186] Output: Insurance premium payment completion status

[1187] 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.

[1188] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1189] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1190] [Third embodiment]

[1191] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1192] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1193] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1194] 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.

[1195] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1196] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1197] 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.

[1198] 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.

[1199] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1200] 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.

[1201] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1202] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1203] overview

[1204] This invention is a system for efficiently inputting and transmitting diagnostic information, automatically reviewing it, notifying users of diagnostic results and treatment plans, automatically paying insurance premiums, and referral and appointment procedures for specialists. This system allows users to receive prompt and appropriate medical care and automates insurance payment procedures, preventing delays in treatment.

[1205] System configuration

[1206] server

[1207] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1208] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[1209] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[1210] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[1211] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[1212] Terminal (device used by the user)

[1213] The terminal provides an interface for the user to input diagnostic information.

[1214] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[1215] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[1216] The terminal provides a function to assist the user in making an appointment with a specialist.

[1217] User (patient)

[1218] The user inputs their own health condition and diagnosis results through the terminal.

[1219] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[1220] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[1221] Program processing explanation

[1222] Entering and sending diagnostic information

[1223] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[1224] The terminal formats this data and sends it to the server.

[1225] Automated review and diagnostic generation

[1226] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[1227] The server generates and provides diagnostic results and standard treatment plans to the user.

[1228] Premium payment processing and notification

[1229] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[1230] The server sends the payment result to the terminal and notifies the user.

[1231] Specialist opinion and referral

[1232] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[1233] The server sends the appointment information to the specialist and confirms the appointment.

[1234] Confirm appointment and start treatment

[1235] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[1236] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[1237] The above configuration and functions enable users to receive prompt and accurate medical services and facilitate smooth insurance payment procedures, thereby reducing delays in treatment and patient anxiety.

[1238] The processing flow will be explained below.

[1239] Step 1:

[1240] The user inputs their own health condition and diagnosis results into the device application.

[1241] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[1242] Step 2:

[1243] The terminal formats the entered diagnostic information and sends it to the server.

[1244] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[1245] Step 3:

[1246] The server stores the received diagnostic information in a database.

[1247] Specifically, the received data is validated and stored in the appropriate database tables.

[1248] Step 4:

[1249] The server will start the automatic review.

[1250] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[1251] Step 5:

[1252] The server generates a diagnosis and a standard treatment plan.

[1253] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[1254] Step 6:

[1255] The server sends the generated diagnostic results and treatment plan to the terminal.

[1256] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[1257] Step 7:

[1258] The terminal notifies the user of the received diagnosis results and treatment plan.

[1259] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[1260] Step 8:

[1261] The server automates the insurance payment process.

[1262] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[1263] Step 9:

[1264] The server sends a notification of payment completion to the terminal.

[1265] Specifically, the transfer success status and detailed information are sent to the terminal.

[1266] Step 10:

[1267] The terminal displays a notification to the user that the payment has been completed.

[1268] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[1269] Step 11:

[1270] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[1271] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[1272] Step 12:

[1273] The terminal displays a list of specialists to the user.

[1274] Specifically, when a user opens the application, it displays a list of specialists.

[1275] Step 13:

[1276] The user selects the desired specialist and makes a reservation.

[1277] Specifically, fill out the reservation form within the application and press the submit button.

[1278] Step 14:

[1279] The terminal sends the reservation procedure to the server.

[1280] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[1281] Step 15:

[1282] The server sends the appointment information to the specialist for confirmation.

[1283] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[1284] Step 16:

[1285] The terminal notifies the user of the reservation confirmation information.

[1286] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[1287] Through these processing steps, users can receive prompt and accurate diagnosis and treatment, and the automated payment process prevents delays in treatment.

[1288] Example 1

[1289] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1290] In the current medical system, patients must enter diagnostic information, receive diagnostic results, receive notification of treatment plans, pay insurance premiums, and refer to specialists and make appointments individually, which takes time and effort, and can prevent patients from receiving medical services promptly and appropriately.There is also concern that delays in insurance payment procedures could delay the start of treatment.

[1291] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1292] In this invention, the server includes a means for automatically reviewing the diagnostic information and using an algorithm that references past diagnostic data and standard treatment protocols, a means for notifying the generated diagnostic results and treatment plan, and a means for calculating insurance premiums based on the treatment plan and automatically transferring the premiums to a designated bank account. This enables rapid review of diagnostic information, provision of diagnostic results and treatment plans, and automatic payment of insurance premiums, allowing patients to receive medical services efficiently and without delay.

[1293] "Diagnosis information" is information entered by the user regarding their own poor physical condition or symptoms.

[1294] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1295] "Automated review" is the process of using an algorithm to perform a diagnosis based on received diagnostic information and generate a result.

[1296] An "algorithm" is a computational method that analyzes diagnostic information and matches it with historical diagnostic data and standard treatment protocols.

[1297] A "diagnostic result" is a specific diagnostic conclusion generated by an automated review.

[1298] A "treatment plan" is a specific treatment step and prescription proposed based on diagnostic results.

[1299] "Premium" is the payment amount calculated based on the diagnosis and treatment plan.

[1300] "Direct deposit" is the process of transferring funds electronically to a designated bank account.

[1301] A "specialist" is a doctor who is well-versed and certified in a particular field.

[1302] The "reservation procedure" is the procedure for confirming the date and time of an appointment with a specialist.

[1303] A "generative AI model" is a model that uses artificial intelligence to analyze diagnostic information and automatically review and generate diagnostic results.

[1304] overview

[1305] This invention is a system for efficiently inputting, transmitting, and automatically reviewing diagnostic information, notifying diagnostic results and treatment plans, automatically paying insurance premiums, and processing specialist referrals and appointment procedures. This system is designed to enable users to receive prompt and appropriate medical care by using generative AI models to analyze diagnostic information and automate various procedures.

[1306] Hardware and Software Used

[1307] server:

[1308] A server is a computer system that receives, stores, processes data, and sends the results to other devices over a network. For example, this could include a database management system or a diagnostic algorithm running on a Linux server.

[1309] Device:

[1310] The terminal is the device used by the user, such as a smartphone, tablet, or laptop, that provides the user interface and assists in entering diagnostic information, displaying received results, and scheduling appointments with specialists.

[1311] Generative AI models:

[1312] An artificial intelligence model for analyzing diagnostic information and generating diagnostic results and treatment plans, using machine learning frameworks such as TensorFlow and PyTorch.

[1313] Processing flow

[1314] 1. The user uses the device interface to input their own health condition and diagnosis results. For example, the user enters "I've been feeling tired a lot recently" in the text box.

[1315] 2. The device formats this information (e.g., in JSON format) and sends it to the server.

[1316] 3. The server uses the received data to perform an automated review using a generative AI model. For example, it uses past diagnostic data to determine whether "easily fatigued" is an early symptom of hypothyroidism.

[1317] 4. The server generates the diagnosis and standard treatment plan (e.g., blood tests and thyroid hormone replacement therapy recommendations) and sends them to the device.

[1318] 5. The device displays the diagnosis and treatment plan to the user.

[1319] 6. The server calculates the insurance premium based on the treatment plan and uses a financial API to automatically transfer the payment to the bank account specified by the user.

[1320] 7. The server notifies the terminal of the transfer result so that the user can check it.

[1321] 8. The terminal displays a list of appropriate specialists to the user, allowing the user to select the desired specialist and make an appointment.

[1322] 9. The server sends the reservation information to the specialist, and once confirmation is received, it sends the reservation confirmation information to the terminal.

[1323] 10. The terminal displays the reservation confirmation information to the user.

[1324] 11. The user visits the specialist at the specified date and time and begins treatment based on the diagnosis results.

[1325] Examples of concrete examples and prompts

[1326] Specific examples

[1327] 1. The user types "I've been feeling very tired lately" into the device and sends it.

[1328] 2. The device sends this information to the server.

[1329] 3. The server analyzes the received data and generates a diagnosis of suspected hypothyroidism and a treatment plan.

[1330] 4. The server sends the result to the terminal and notifies the user.

[1331] 5. The server calculates the insurance premium based on the treatment plan and transfers the amount to the specified bank account.

[1332] 6. The device notifies the user of the results and provides a list of specialists.

[1333] 7. The user selects the specialist of their choice and makes an appointment.

[1334] 8. The server sends the appointment information to the specialist for confirmation.

[1335] Prompt Sentence Examples

[1336] "Have you been feeling tired more often recently?"

[1337] "A diagnosis and treatment plan have been generated. Please review the details."

[1338] "Insurance premium payment completed. Please check the results."

[1339] "Here's a list of suitable specialists. Please select one if you would like to make an appointment."

[1340] The system allows users to receive medical services efficiently and without delay, and the use of generative AI models improves the accuracy of diagnostic results and treatment plans, further enhancing user convenience.

[1341] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1342] Step 1:

[1343] The user uses the device interface to input diagnostic information about their health condition or symptoms. For example, the user might type, "I've been feeling tired a lot recently" into a text box. The input data is formatted and ready to be recognized by the system.

[1344] Step 2:

[1345] The device converts the diagnostic information entered into a standard format such as JSON and sends it to the server. The formatted data is then transferred to the server as an HTTP request.

[1346] Step 3:

[1347] The server stores the received diagnostic information in a database and starts analysis by accessing the data repository. Specifically, it executes an INSERT query in the database.

[1348] Step 4:

[1349] The server performs an automated review based on the diagnostic information. It uses a generative AI model to analyze the diagnostic information and compare it with past diagnostic data and standard treatment protocols. For example, it compares it with past patient data with the symptom of "easily fatigued" and evaluates the relevance. The input is the diagnostic information, and the output is the diagnostic results and treatment plan.

[1350] Step 5:

[1351] The server generates diagnostic results and treatment plans, which are packaged in JSON format and sent to the device. For example, the diagnostic results for hypothyroidism and the treatment plan for "thyroid hormone replacement therapy" are included. This allows the user to check the diagnostic results.

[1352] Step 6:

[1353] The terminal displays the diagnosis results and treatment plan received on the user interface. For example, the diagnosis name and recommended treatment details are displayed. Specifically, the data is displayed in the UI component.

[1354] Step 7:

[1355] The server calculates insurance premiums based on diagnosis results and treatment plans. It uses a financial API to calculate insurance premiums in real time and automatically transfers the funds to a designated bank account. The input is diagnosis results and insurance information, and the output is the transfer results.

[1356] Step 8:

[1357] The server generates the transfer result and sends it to the terminal in JSON format, such as "$200 has been transferred to the specified bank account." The terminal receives this and makes it available.

[1358] Step 9:

[1359] The terminal notifies the user of the payment result. For example, a message such as "Insurance payment has been completed. Please check the result" is displayed. Specifically, the message is displayed in the notification component.

[1360] Step 10:

[1361] The device displays a list of appropriate specialists to the user, for example, a list of categories such as "endocrinologists," and provides an interface for the user to select the desired specialist.

[1362] Step 11:

[1363] When a user selects a specialist and wishes to make an appointment, they complete the reservation procedure through their terminal. For example, they enter "I would like to make an appointment with an endocrinologist" into the reservation form. The input is sent to the server.

[1364] Step 12:

[1365] The server sends the appointment information to the specialist and confirms it. For example, it checks the appointment schedule and generates appointment confirmation information. The input is the user's appointment information, and the output is the appointment confirmation information.

[1366] Step 13:

[1367] The device displays reservation confirmation information to the user. For example, a message like "Reservation confirmed. Please confirm the date, time, and location" is displayed. Specifically, the schedule information is displayed in the calendar component.

[1368] Step 14:

[1369] The user visits a specialist at a specified date and time and begins treatment based on the diagnosis. For example, a user might visit a designated endocrinologist to receive treatment for hypothyroidism.

[1370] (Application example 1)

[1371] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1372] In modern healthcare services, to ensure patients receive prompt and appropriate diagnoses and treatment, it is necessary to streamline a series of processes, from entering and submitting diagnostic information to automatic review, notification of diagnostic results, insurance payment, specialist referrals, and appointment procedures. However, when these processes are performed manually, they require a lot of time and effort, resulting in treatment delays and patient anxiety. Furthermore, if medical data security is not ensured, there is a risk that patient privacy will be compromised. To solve these issues, an efficient and secure healthcare service delivery system is required.

[1373] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1374] In this invention, the server includes a means for inputting diagnostic information, a means for transmitting the diagnostic information to the server, a means for performing an automatic review based on the diagnostic information in the server, a means for encrypting the diagnostic information and transmitting it to the server, a means for performing an automatic review using an AI model and generating a diagnostic result, a means for processing insurance premium payments via an online payment system, and a means for synchronizing appointment information with a calendar. This enables secure transmission of diagnostic information, automated generation of diagnostic results, prompt insurance premium payment processing, and smooth appointment procedures with specialists.

[1375] "Diagnostic information" refers to information entered by a patient about their health condition or symptoms.

[1376] A "server" is a computer system that receives, stores, processes, and transmits data over a network.

[1377] "Automated review" refers to the process of using algorithms or AI models based on input diagnostic information to generate diagnostic results without manual intervention.

[1378] "Diagnostic result" means a medical judgment or diagnosis of a patient's symptoms generated by an automated review means.

[1379] A "treatment plan" refers to the specific treatment content and procedures that a patient should undergo based on the diagnostic results.

[1380] "Premiums" are the money paid by patients to cover medical expenses and are calculated based on automated screening results and treatment plans.

[1381] An "online payment system" is a system that automatically conducts monetary transactions via the Internet.

[1382] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[1383] "Appointment booking" refers to the process for booking a date and time to see a specialist.

[1384] "Calendar synchronization" means linking reservation information and other data with a digital calendar system to maintain consistency of information.

[1385] "Encryption" is a technique for converting data into a format that cannot be deciphered by third parties.

[1386] An "AI model" is a model that uses artificial intelligence algorithms to automatically extract patterns and knowledge from data and make diagnoses and predictions.

[1387] System configuration

[1388] A system for implementing this invention includes the following major components:

[1389] 1. Terminal (device used by the user)

[1390] 2. Server

[1391] 3. Network

[1392] Terminal

[1393] The terminal is a device that provides an interface for users to input diagnostic information and send it to the server. The terminal is a mobile device that can connect to the Internet, such as a smartphone or tablet. The terminal has the following functions:

[1394] Entering and sending encrypted diagnostic information (using encryption technology such as AES-256)

[1395] Notification of diagnosis and treatment plan

[1396] Displaying a list of specialists and assisting with appointment booking (Calendar synchronization using Google Calendar API)

[1397] server

[1398] The server is a computer system that receives data sent from the terminals via the network and performs automatic review and processing. The server processes the data using the following software:

[1399] Backend: Node.js and Express

[1400] Database: Use MongoDB to manage health data

[1401] AI diagnostic model: Automated screening using TensorFlow

[1402] Online payment system: Stripe API or PayPal API

[1403] Processing Details

[1404] Entering and sending diagnostic information

[1405] Users use the device to enter their diagnostic information, including details of their illness and symptoms, which is then securely transmitted to the server using AES-256 encryption.

[1406] Automated review and diagnostic generation

[1407] The server inputs the received diagnostic information into an AI diagnostic model (TensorFlow) for automatic review. It generates diagnostic results and a treatment plan using an algorithm that references past diagnostic data and standard treatment protocols, and sends them to the device.

[1408] Insurance premium payment processing

[1409] The server calculates the insurance premium based on the diagnosis results and treatment plan, and automatically processes the payment using an online payment system (such as Stripe API or PayPal API). The results are then sent to the terminal.

[1410] Specialist referrals and appointments

[1411] Based on the information received from the server, the device displays a list of appropriate specialists to the user. Once the user selects a specialist, the device uses the Google Calendar API to synchronize the appointment information with the calendar and assist with the appointment process.

[1412] Examples and prompts

[1413] Examples:

[1414] User input: "I've been feeling tired and dizzy lately."

[1415] The AI ​​model says: "These symptoms may indicate hypothyroidism. We'll provide a treatment plan based on the diagnosis and a referral specialist."

[1416] Payment procedure: "Insurance premium calculation completed. 2500 yen has been automatically paid."

[1417] Example prompt for a generative AI model:

[1418] "Create an application that uses an automated diagnostic model to generate a diagnosis based on the health information entered by the user, and then calculates insurance premiums and processes payments based on the results. It also refers users to the appropriate specialist and automatically schedules appointments."

[1419] As a result, the present invention can provide efficient and secure medical services and reduce the burden on patients.

[1420] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1421] Step 1:

[1422] User enters diagnostic information

[1423] Input: The user uses the terminal to input diagnostic information (e.g., fatigue, dizziness).

[1424] Specific operation: The user uses a smartphone or tablet to enter their symptoms into the input form of a dedicated application.

[1425] Output: Entered diagnostic information is saved to the terminal.

[1426] Step 2:

[1427] The device encrypts the diagnostic information and sends it to the server

[1428] Input: The diagnostic information entered in Step 1.

[1429] Data processing: Diagnostic information is encrypted using AES-256 encryption technology.

[1430] Specific operation: The terminal application encrypts the entered diagnostic information and sends it to the server using a secure communication protocol (HTTPS).

[1431] Output: Encrypted diagnostic information is sent to the server.

[1432] Step 3:

[1433] The server performs an automatic review based on the diagnostic information.

[1434] Input: Diagnostic information sent encrypted.

[1435] Data processing: The server decrypts the encrypted data and converts it into a format that can be input into the AI ​​diagnostic model (TensorFlow).

[1436] What it does: The server decrypts the diagnostic information and runs the AI ​​model using historical diagnostic data and standard treatment protocols.

[1437] Output: Diagnosis and treatment plan generated by the AI ​​diagnostic model.

[1438] Step 4:

[1439] The server sends the diagnosis results and treatment plan to the device.

[1440] Input: The diagnosis and treatment plan generated in step 3.

[1441] Specific operation: The server converts the diagnosis results and treatment plan into a data format (such as JSON) and sends them to the terminal.

[1442] Output: The diagnosis and treatment plan are sent to the device.

[1443] Step 5:

[1444] The device notifies you of the diagnosis and treatment plan

[1445] Input: Diagnosis and treatment plan submitted in step 4.

[1446] What it does: The device application uses notifications to display diagnostic results and treatment plans to the user.

[1447] Output: The user is informed of the diagnosis and treatment plan.

[1448] Step 6:

[1449] The server calculates and pays the insurance premiums.

[1450] Input: The treatment plan generated in step 4.

[1451] Data calculation: Calculates insurance premiums based on treatment plans and executes payment procedures via online payment systems (Stripe API or PayPal API).

[1452] Specific operation: The server analyzes the treatment plan, calculates the required insurance premium, and then calls the API of the online payment system to automatically make the payment.

[1453] Output: Premium payment result.

[1454] Step 7:

[1455] The server sends the insurance premium payment result to the terminal

[1456] Input: Premium payment results obtained in step 6.

[1457] Specific operation: The server converts the insurance premium payment results into a data format (such as JSON) that is easy for the user to understand and sends it to the terminal.

[1458] Output: The insurance premium payment result is sent to the terminal.

[1459] Step 8:

[1460] The terminal notifies the result of the insurance premium payment

[1461] Input: Premium payment result sent in step 7.

[1462] Specific operation: The terminal application uses the notification function to display the insurance premium payment result to the user.

[1463] Output: The user is notified of the insurance premium payment result.

[1464] Step 9:

[1465] The device displays a list of specialists and assists with the appointment process

[1466] Input: Treatment plan and specialist information submitted in step 4.

[1467] What it does: The device application displays a list of appropriate specialists based on the treatment plan, helps the user schedule an appointment with the selected specialist, and synchronizes the appointment information using the Google Calendar API.

[1468] Output: The user is presented with a list of specialists and is assisted in the appointment process.

[1469] Step 10:

[1470] The server sends the appointment information to the specialist

[1471] Input: Reservation information generated in step 9.

[1472] Specific operation: The server sends the appointment information to the specialist's system and confirms the appointment.

[1473] Output: Appointment information is sent to the specialist and confirmed.

[1474] Step 11:

[1475] The device will notify you of the reservation confirmation information

[1476] Input: Reservation information confirmed in step 10.

[1477] Specific behavior: The device application uses the notification function to display reservation confirmation information to the user.

[1478] Output: The user is notified of the reservation confirmation.

[1479] These steps ensure that the process proceeds efficiently, enabling users to receive prompt and appropriate medical services.

[1480] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1481] overview

[1482] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. Furthermore, by incorporating an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, the system provides optimal medical services according to the user's psychological state.

[1483] System configuration

[1484] server

[1485] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1486] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[1487] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[1488] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[1489] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[1490] The server includes an emotion engine that analyzes the user's emotion data and customizes the diagnosis and treatment plan.

[1491] Terminal (device used by the user)

[1492] The terminal provides an interface for the user to input diagnostic information.

[1493] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[1494] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[1495] The terminal provides a function to assist the user in making an appointment with a specialist.

[1496] The terminal transmits the user's emotion data generated by the emotion engine to the server.

[1497] User (patient)

[1498] The user inputs their own health condition and diagnosis results through the terminal.

[1499] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[1500] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[1501] The user's emotional data is appropriately evaluated by the system and a customized treatment plan is then provided.

[1502] Program processing explanation

[1503] Entering and sending diagnostic information

[1504] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[1505] The terminal formats this data and sends it to the server.

[1506] Automated review and diagnostic generation

[1507] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[1508] The server generates and provides diagnostic results and standard treatment plans to the user.

[1509] Analysis and customization with emotion engine

[1510] The device generates emotion data based on the user's input and sends it to the server. For example, it determines that the user is feeling anxious or stressed based on the input information.

[1511] The server analyzes the emotional data using an emotion engine to customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, stress management advice and mental health support will be added to the treatment plan.

[1512] Premium payment processing and notification

[1513] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[1514] The server sends the payment result to the terminal and notifies the user.

[1515] Specialist opinion and referral

[1516] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[1517] The server sends the appointment information to the specialist for confirmation.

[1518] Confirm appointment and start treatment

[1519] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[1520] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[1521] The above configuration and functions enable users to receive prompt and accurate medical services, and by incorporating an emotion engine, the system provides optimal treatment plans based on the user's psychological state.In addition, the automation of insurance payment procedures prevents delays in treatment.

[1522] The processing flow will be explained below.

[1523] Step 1:

[1524] The user inputs their own health condition and diagnosis results into the device application.

[1525] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[1526] Step 2:

[1527] The terminal formats the entered diagnostic information and sends it to the server.

[1528] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[1529] Step 3:

[1530] The server stores the received diagnostic information in a database.

[1531] Specifically, the received data is validated and stored in the appropriate database tables.

[1532] Step 4:

[1533] The server will start the automatic review.

[1534] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[1535] Step 5:

[1536] The server generates a diagnosis and a standard treatment plan.

[1537] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[1538] Step 6:

[1539] The server sends the generated diagnostic results and treatment plan to the terminal.

[1540] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[1541] Step 7:

[1542] The terminal notifies the user of the received diagnosis results and treatment plan.

[1543] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[1544] Step 8:

[1545] The user inputs their own feelings based on the diagnosis results.

[1546] Specifically, after being notified that a blood test is required as a diagnostic result, the user inputs, "I feel uneasy about this result."

[1547] Step 9:

[1548] The terminal formats the user's emotional data and sends it to the server.

[1549] Specifically, the user emotion data is converted into JSON format and sent to the server.

[1550] Step 10:

[1551] The server executes an emotion engine based on the received emotion data.

[1552] Specifically, the system analyzes emotional data to assess the user's psychological state, and if, for example, anxiety levels are high, it adjusts the treatment plan accordingly.

[1553] Step 11:

[1554] The server uses the analysis results from the emotion engine to customize a treatment plan.

[1555] Specifically, for users with high levels of anxiety, a treatment plan is generated that recommends stress management advice and relaxation techniques.

[1556] Step 12:

[1557] The server sends the customized treatment plan to the device.

[1558] Specifically, the customized treatment plan is encoded in JSON format and sent to the device.

[1559] Step 13:

[1560] The device notifies the user of the customized treatment plan.

[1561] Specifically, when a user opens the application, a pop-up notification or email notification displays the customized treatment plan.

[1562] Step 14:

[1563] The server automates the insurance payment process.

[1564] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[1565] Step 15:

[1566] The server sends a notification of payment completion to the terminal.

[1567] Specifically, the transfer success status and detailed information are sent to the terminal.

[1568] Step 16:

[1569] The terminal displays a notification to the user that the payment has been completed.

[1570] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[1571] Step 17:

[1572] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[1573] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[1574] Step 18:

[1575] The terminal displays a list of specialists to the user.

[1576] Specifically, when a user opens the application, it displays a list of specialists.

[1577] Step 19:

[1578] The user selects the desired specialist and makes a reservation.

[1579] Specifically, fill out the reservation form within the application and press the submit button.

[1580] Step 20:

[1581] The terminal sends the reservation procedure to the server.

[1582] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[1583] Step 21:

[1584] The server sends the appointment information to the specialist for confirmation.

[1585] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[1586] Step 22:

[1587] The terminal notifies the user of the reservation confirmation information.

[1588] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[1589] Through these processing steps, users can receive a quick and accurate diagnosis and treatment. Furthermore, the introduction of an emotion engine provides an optimal treatment plan based on their psychological state. Furthermore, the automated payment procedures for insurance premiums prevent delays in treatment.

[1590] Example 2

[1591] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1592] Conventional medical systems require users to input and submit diagnostic information, automatically review it, receive notifications of diagnostic results and treatment plans, automatically pay insurance premiums, and refer and schedule appointments, all individually, which takes time and effort. Furthermore, they do not provide customized treatment plans that take into account the user's psychological state, which reduces user satisfaction.

[1593] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting diagnostic information, means for transmitting the diagnostic information to the server, means for performing automatic examination based on the diagnostic information in the server, means for receiving and notifying the diagnostic results and treatment plan generated by the automatic examination, means for processing insurance premium payment based on the treatment plan, means for notifying the insurance premium payment result, means for referring to a specialist based on the treatment plan, means for supporting the appointment procedure with the specialist, means for generating user emotion data and transmitting it to the server, and means for analyzing the emotion data and customizing the diagnostic results and treatment plan. This allows users to receive prompt and accurate medical services. Furthermore, by incorporating an emotion engine, an optimal treatment plan tailored to the user's psychological state can be provided, thereby eliminating dissatisfaction.

[1594] "Diagnostic information" is information about health conditions and symptoms entered by the user.

[1595] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1596] "Automatic review" refers to the process of analyzing and making judgments based on the diagnostic information received by the server using machine learning algorithms and databases.

[1597] A "diagnosis result" is a conclusion regarding the user's health condition obtained through an automated screening.

[1598] A "treatment plan" is a proposed treatment policy or procedure based on diagnostic results.

[1599] "Premium" is an amount calculated to subsidize a portion of a user's medical expenses.

[1600] "Automatic transfer procedure" is a process in which the server automatically transfers the amount to a specified bank account.

[1601] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[1602] The "reservation procedure" is a procedure for reserving a consultation time with a specialist in advance.

[1603] "Emotion data" is data relating to a psychological state generated by an emotion engine from information input by a user.

[1604] The "emotion engine" is an algorithm and module for analyzing a user's emotional data and customizing diagnostic results and treatment plans.

[1605] overview

[1606] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. It also incorporates an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, providing optimal medical services according to the user's psychological state.

[1607] System Configuration

[1608] server

[1609] The server is a computer system that receives, stores, processes, and transmits data to other devices via a network. Specifically, it automatically reviews diagnostic information and generates diagnostic results and treatment plans. It also automatically processes insurance payments and performs specialist referrals and appointment confirmations. Furthermore, the server is equipped with an emotion engine that analyzes users' emotional data and customizes diagnostic results and treatment plans.

[1610] Terminal

[1611] The terminal is a device that provides an interface for users to input diagnostic information. It has the function of formatting the user's input information and sending it to the server. It also receives and notifies the user of diagnostic results and treatment plans, and assists in the specialist appointment process.

[1612] User

[1613] Users can input their symptoms and emotional state through a terminal, check the diagnosis results and treatment plans provided by the system, make appointments with specialists, and check the results of insurance premium payments.

[1614] Hardware and software used

[1615] Server: High-performance cloud computing services (e.g., AWS, Google Cloud)

[1616] Devices: Smartphones, tablets, PCs

[1617] Emotion engine: Machine learning algorithms (e.g. TensorFlow, PyTorch)

[1618] Specific Examples

[1619] Entering and sending diagnostic information

[1620] The user inputs their own health condition and diagnosis results into a dedicated smartphone app. For example, they might enter, "I've been feeling tired a lot recently." The device then formats this information and sends it to the server.

[1621] Automated screening and diagnostic results generation

[1622] The server automatically reviews the diagnostic information it receives. The algorithm compares it with past cases and standard diagnostic protocols to generate a diagnosis and treatment plan. For example, it may determine that the symptom of "easily tired" is a possible sign of hypothyroidism and recommend a blood test.

[1623] Analysis and customization with emotion engine

[1624] The device generates emotion data from the user's input and sends it to the server, which uses an emotion engine to analyze this data and customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, it may add stress management advice.

[1625] Processing premium payments

[1626] The server calculates the insurance premium based on the diagnosis and treatment plan, performs the automatic transfer procedure, and sends the transfer result to the terminal and notifies the user.

[1627] Specialist referrals and appointment procedures

[1628] Based on the data received by the terminal, a list of appropriate specialists is displayed to the user, and the server sends the appointment information to the specialist selected by the user for confirmation.

[1629] Prompt Sentence Examples

[1630] "A 45-year-old woman has recently been experiencing frequent fatigue and headaches. Based on this information, please suggest a diagnosis and treatment plan. Also, please use the emotion engine to take into account emotional data."

[1631] This system allows users to receive prompt and accurate medical services, and by incorporating an emotion engine, it provides optimal treatment plans based on the user's psychological state.In addition, the system automates insurance payment procedures, preventing delays in treatment.

[1632] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1633] System program processing flow

[1634] Step 1: Enter diagnostic information

[1635] Input: User inputs their health condition and symptoms

[1636] Processing: The terminal receives and formats the incoming data.

[1637] Output: Formatted diagnostic information

[1638] Specific behavior:

[1639] The user opens a dedicated smartphone app and enters information about their symptoms. For example, they might enter, "I've been feeling tired a lot recently." The device then converts this information into a format such as "Symptom: Fatigue easily" and "Start date: 2 weeks ago."

[1640] Step 2: Send diagnostic information

[1641] Input: Formatted diagnostic information

[1642] Action: The device sends formatted diagnostic information to the server.

[1643] Output: Diagnostic information sent to the server

[1644] Specific behavior:

[1645] The device sends formatted diagnostic information to the server using a security protocol (e.g., HTTPS). The information sent includes, for example, "Symptom: fatigue easily" and "Start time: 2 weeks ago."

[1646] Step 3: Automated review and diagnostic results generation

[1647] Input: Diagnostic information received by the server

[1648] Processing: The server performs automated review using machine learning algorithms

[1649] Output: Diagnostic results and treatment plan

[1650] Specific behavior:

[1651] The server compares the received diagnostic information with past cases and standard diagnostic protocols to generate a diagnosis. For example, if it determines that the symptom of "easily fatigued" is related to hypothyroidism, it generates a diagnosis result of "suspected hypothyroidism" and a treatment plan of "recommended blood test."

[1652] Step 4: Notification of diagnosis and treatment plan

[1653] Input: Diagnosis and treatment plan

[1654] Processing: The server sends the diagnosis results and treatment plan to the device.

[1655] Output: Diagnostic results and treatment plan received by the user

[1656] Specific behavior:

[1657] The server sends the generated diagnosis and treatment plan to the device, which notifies the user and displays on the screen, "Diagnosis: Suspected hypothyroidism" and "Treatment plan: Blood test recommended."

[1658] Step 5: Generate and send emotion data

[1659] Input: User input information

[1660] Processing: The device generates emotion data using the emotion recognition API and sends it to the server.

[1661] Output: Emotion data sent to the server

[1662] Specific behavior:

[1663] The device generates emotional data from the user's input. For example, the system can detect a high stress level based on the frequency of the word "fatigue" and the user's use of the word, and format the emotional data as "Stress level: high." This emotional data is then sent to the server.

[1664] Step 6: Analyze sentiment data and customize diagnosis

[1665] Input: Emotion data

[1666] Processing: The server uses an emotion engine to analyze the emotion data and customize the diagnosis and treatment plan.

[1667] Output: Customized diagnostic results and treatment plans

[1668] Specific behavior:

[1669] The server analyzes the emotion data and updates the diagnosis and treatment plan, for example, customizing it as "Diagnosis: Suspected hypothyroidism, Treatment plan: Recommend blood test + Recommend mental health support for stress management."

[1670] Step 7: Process premium payments

[1671] Input: Diagnosis and treatment plan

[1672] Processing: The server calculates the insurance premium and processes the automatic transfer.

[1673] Output: Notification of transfer completion

[1674] Specific behavior:

[1675] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the money to the user's bank account. After the transfer is complete, the result is sent to the terminal. The terminal then notifies the user that "the insurance payment has been transferred."

[1676] Step 8: Specialist referral

[1677] Input: Customized diagnostic results and treatment plans

[1678] Action: The device displays a list of appropriate specialists to the user.

[1679] Output: List of specialists and available appointments

[1680] Specific behavior:

[1681] Based on the information received from the server, the device displays a list of appropriate specialists to the user. For example, the user is provided with information such as "Thyroid specialist: Dr. Smith, available appointments: Monday 14:00-16:00."

[1682] Step 9: Book an appointment with a specialist

[1683] Input: User reservation information

[1684] Processing: The server sends the appointment information to the specialist and confirms it.

[1685] Output: Reservation confirmation information

[1686] Specific behavior:

[1687] A user makes an appointment with a specialist through a terminal. The server sends the appointment information to the specialist's system and receives confirmation from the specialist. Once the appointment is confirmed, the terminal displays a message saying, "Your appointment has been confirmed. Please see Dr. Smith at 2:00 PM on Monday."

[1688] Step 10: Confirm appointment and start treatment

[1689] Input: Reservation confirmation information

[1690] Action: User consults a specialist

[1691] Output: Examination and treatment results

[1692] Specific behavior:

[1693] The user visits the specialist at the scheduled time and receives the consultation and any necessary tests or treatment. The specialist explains the results of the consultation to the user and provides a plan for any further treatment or tests that may be required.

[1694] Through these steps, the system can provide users with fast and accurate medical services and customize the optimal treatment plan according to the user's emotional state.

[1695] (Application example 2)

[1696] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1697] In today's healthcare system, the process of entering diagnostic information, obtaining diagnostic results, receiving treatment plans, paying insurance premiums, and referrals and appointment bookings is often not smooth, resulting in delays and inaccuracies. Properly assessing users' psychological state and providing optimal treatment plans is also a major challenge. While it is particularly important for online healthcare services to properly analyze users' emotions and reflect them in diagnostic results and treatment plans, effective systems for achieving this are currently lacking.

[1698] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1699] In this invention, the server includes a means for transmitting diagnostic information to the server, a means for performing automated review, and a means for utilizing an emotion engine to customize diagnostic results and treatment plans, thereby enabling the provision of highly accurate diagnostic results and treatment plans tailored to the user's emotional state.

[1700] "Diagnostic Information" is data entered by a user about their health condition or symptoms.

[1701] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1702] "Automated review" is the process by which the server uses algorithms to reference past diagnostic data and standard treatment protocols based on the diagnostic information received, to generate a diagnostic result and treatment plan.

[1703] A "treatment plan" is a set of medical procedures or instructions provided to a user based on a diagnosis.

[1704] "Premium" means money paid to cover a user's medical expenses and treatment costs.

[1705] The "emotion engine" is part of a system that analyzes emotional data based on user input and customizes diagnostic results and treatment plans.

[1706] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[1707] A "user" is a person who uses the diagnostic system to input information about their health condition and receive diagnostic results and treatment plans.

[1708] This invention is a system that efficiently inputs, transmits, and automatically reviews diagnostic information, notifies users of diagnostic results and treatment plans, processes insurance premium payments, and provides referrals and appointment procedures to specialists, while also providing optimal medical services that reflect the user's feelings.

[1709] System configuration

[1710] 1. Server

[1711] A server is a computer system that receives, stores, and processes data over a network. The specific software used is the Django framework.

[1712] Diagnostic information is received and automatically reviewed using algorithms (e.g., machine learning models) that reference previous diagnostic data and standard treatment protocols.

[1713] It generates diagnostic results and treatment plans, and also customizes them based on the user's emotional data using an emotion engine, which uses generative AI models such as TensorFlow.

[1714] The insurance premium payment is automatically made and the user is notified of the result.

[1715] An appropriate specialist will be selected from the list and referred to the user.

[1716] 2. Terminal

[1717] The terminal is a smartphone or PC that provides an interface for the user to input diagnostic information.

[1718] The diagnostic information is formatted and sent to the server, and the processing results are received and notified to the user. The specific software is a smartphone app developed using React Native.

[1719] It displays diagnostic results and treatment plans and suggests next actions for the user (such as scheduling an appointment with a specialist).

[1720] The emotion data generated by the emotion engine is transmitted to the server.

[1721] 3. Users

[1722] Users enter information about their health condition and symptoms through the device.

[1723] Review the provided diagnosis and treatment plan, select the appropriate specialist, and schedule an appointment.

[1724] Treatment is provided based on the results of insurance payment processing and treatment plan.

[1725] The emotional data is evaluated by the system and a customized treatment plan is given.

[1726] Specific examples of processing and prompt statements

[1727] As a concrete example, consider the case where a user enters into a device, "I've been feeling tired and stressed recently." The device formalizes this information and sends it to the server. The server then performs an automatic review based on the received data and generates a diagnosis of "suspected hypothyroidism." At the same time, the emotion engine recognizes high stress levels and generates a treatment plan of "blood tests, hormone therapy, and stress management advice," and notifies the user.

[1728] Example prompt sentence:

[1729] "Take user input: 'I've been feeling tired and stressed lately,' and use an emotion engine to analyze their stress level and generate a corresponding diagnosis and customized treatment plan."

[1730] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1731] Step 1:

[1732] The user inputs their health condition and symptoms into the device.

[1733] Type: "I've been feeling tired and stressed lately."

[1734] The device receives information about the user's health condition and symptoms, formats this information, and prepares it as data to send to the server.

[1735] Output: Formatted diagnostic information

[1736] Step 2:

[1737] The device sends formatted diagnostic information to the server

[1738] Input: Formatted diagnostic information

[1739] The terminal establishes a network connection to transmit the formatted diagnostic information to the server, and upon completion of the transmission, the terminal receives a transmission completion status.

[1740] Output: Diagnostic information sending completion status

[1741] Step 3:

[1742] The server performs an automatic review based on the diagnostic information received.

[1743] Input: Formatted diagnostic information

[1744] The server inputs the received diagnostic information into an algorithm and automatically diagnoses the patient by referencing past diagnostic data and standard treatment protocols. Specifically, it performs pattern recognition and comparison with a database of past cases.

[1745] Output: Diagnosis (e.g., "suspected hypothyroidism") and treatment plan (e.g., "blood tests, hormone therapy")

[1746] Step 4:

[1747] The server uses an emotion engine to customize the service based on the user's emotion data.

[1748] Input: Formatted diagnostic information and results, treatment plan

[1749] The server uses a TensorFlow-powered emotion engine to analyze the user's input and identify their emotional state (e.g., high stress levels), then generates a customized treatment plan that includes additional information such as stress management advice.

[1750] Output: Customized treatment plan

[1751] Step 5:

[1752] The server sends the diagnosis results and customized treatment plan to the device.

[1753] Input: Diagnosis results, customized treatment plan

[1754] The server transmits the diagnosis results and customized treatment plans to the terminal via the network, checking data consistency and managing communication errors.

[1755] Output: Diagnostic results and customized treatment plan sent to the device

[1756] Step 6:

[1757] The device notifies the user of the diagnosis and a customized treatment plan.

[1758] Input: Diagnostic results and customized treatment plan

[1759] The device provides an interface to display the received diagnosis results and treatment plans in an easy-to-understand manner to the user, specifically by displaying a notification pop-up and detailed information within the app.

[1760] Output: Diagnostic results communicated to the user and a customized treatment plan

[1761] Step 7:

[1762] Users book specialist appointments based on treatment plans

[1763] Input: Customized treatment plan and list of specialists

[1764] The user selects from a list of suitable specialists and schedules an appointment through the terminal, which transmits this information to the server and receives confirmation of the appointment.

[1765] Output: Specialist appointment completion status

[1766] Step 8:

[1767] The server processes the insurance premium payment

[1768] Input: Customized Treatment Plan

[1769] The server calculates the required insurance premium based on the treatment plan, automatically transfers the payment to the designated bank account, and notifies the terminal of the payment result once the transfer is complete.

[1770] Output: Insurance premium payment completion status

[1771] 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.

[1772] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1773] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1774] [Fourth embodiment]

[1775] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1776] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1777] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1778] 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.

[1779] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1780] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1781] 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.

[1782] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1783] 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.

[1784] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1785] 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.

[1786] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1787] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1788] overview

[1789] This invention is a system for efficiently inputting and transmitting diagnostic information, automatically reviewing it, notifying users of diagnostic results and treatment plans, automatically paying insurance premiums, and referral and appointment procedures for specialists. This system allows users to receive prompt and appropriate medical care and automates insurance payment procedures, preventing delays in treatment.

[1790] System configuration

[1791] server

[1792] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1793] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[1794] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[1795] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[1796] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[1797] Terminal (device used by the user)

[1798] The terminal provides an interface for the user to input diagnostic information.

[1799] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[1800] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[1801] The terminal provides a function to assist the user in making an appointment with a specialist.

[1802] User (patient)

[1803] The user inputs their own health condition and diagnosis results through the terminal.

[1804] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[1805] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[1806] Program processing explanation

[1807] Entering and sending diagnostic information

[1808] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[1809] The terminal formats this data and sends it to the server.

[1810] Automated review and diagnostic generation

[1811] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[1812] The server generates and provides diagnostic results and standard treatment plans to the user.

[1813] Premium payment processing and notification

[1814] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[1815] The server sends the payment result to the terminal and notifies the user.

[1816] Specialist opinion and referral

[1817] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[1818] The server sends the appointment information to the specialist and confirms the appointment.

[1819] Confirm appointment and start treatment

[1820] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[1821] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[1822] The above configuration and functions enable users to receive prompt and accurate medical services and facilitate smooth insurance payment procedures, thereby reducing delays in treatment and patient anxiety.

[1823] The processing flow will be explained below.

[1824] Step 1:

[1825] The user inputs their own health condition and diagnosis results into the device application.

[1826] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[1827] Step 2:

[1828] The terminal formats the entered diagnostic information and sends it to the server.

[1829] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[1830] Step 3:

[1831] The server stores the received diagnostic information in a database.

[1832] Specifically, the received data is validated and stored in the appropriate database tables.

[1833] Step 4:

[1834] The server will start the automatic review.

[1835] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[1836] Step 5:

[1837] The server generates a diagnosis and a standard treatment plan.

[1838] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[1839] Step 6:

[1840] The server sends the generated diagnostic results and treatment plan to the terminal.

[1841] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[1842] Step 7:

[1843] The terminal notifies the user of the received diagnosis results and treatment plan.

[1844] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[1845] Step 8:

[1846] The server automates the insurance payment process.

[1847] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[1848] Step 9:

[1849] The server sends a notification of payment completion to the terminal.

[1850] Specifically, the transfer success status and detailed information are sent to the terminal.

[1851] Step 10:

[1852] The terminal displays a notification to the user that the payment has been completed.

[1853] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[1854] Step 11:

[1855] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[1856] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[1857] Step 12:

[1858] The terminal displays a list of specialists to the user.

[1859] Specifically, when a user opens the application, it displays a list of specialists.

[1860] Step 13:

[1861] The user selects the desired specialist and makes a reservation.

[1862] Specifically, fill out the reservation form within the application and press the submit button.

[1863] Step 14:

[1864] The terminal sends the reservation procedure to the server.

[1865] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[1866] Step 15:

[1867] The server sends the appointment information to the specialist for confirmation.

[1868] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[1869] Step 16:

[1870] The terminal notifies the user of the reservation confirmation information.

[1871] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[1872] Through these processing steps, users can receive prompt and accurate diagnosis and treatment, and the automated payment process prevents delays in treatment.

[1873] Example 1

[1874] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1875] In the current medical system, patients must enter diagnostic information, receive diagnostic results, receive notification of treatment plans, pay insurance premiums, and refer to specialists and make appointments individually, which takes time and effort, and can prevent patients from receiving medical services promptly and appropriately.There is also concern that delays in insurance payment procedures could delay the start of treatment.

[1876] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1877] In this invention, the server includes a means for automatically reviewing the diagnostic information and using an algorithm that references past diagnostic data and standard treatment protocols, a means for notifying the generated diagnostic results and treatment plan, and a means for calculating insurance premiums based on the treatment plan and automatically transferring the premiums to a designated bank account. This enables rapid review of diagnostic information, provision of diagnostic results and treatment plans, and automatic payment of insurance premiums, allowing patients to receive medical services efficiently and without delay.

[1878] "Diagnosis information" is information entered by the user regarding their own poor physical condition or symptoms.

[1879] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[1880] "Automated review" is the process of using an algorithm to perform a diagnosis based on received diagnostic information and generate a result.

[1881] An "algorithm" is a computational method that analyzes diagnostic information and matches it with historical diagnostic data and standard treatment protocols.

[1882] A "diagnostic result" is a specific diagnostic conclusion generated by an automated review.

[1883] A "treatment plan" is a specific treatment step and prescription proposed based on diagnostic results.

[1884] "Premium" is the payment amount calculated based on the diagnosis and treatment plan.

[1885] "Direct deposit" is the process of transferring funds electronically to a designated bank account.

[1886] A "specialist" is a doctor who is well-versed and certified in a particular field.

[1887] The "reservation procedure" is the procedure for confirming the date and time of an appointment with a specialist.

[1888] A "generative AI model" is a model that uses artificial intelligence to analyze diagnostic information and automatically review and generate diagnostic results.

[1889] overview

[1890] This invention is a system for efficiently inputting, transmitting, and automatically reviewing diagnostic information, notifying diagnostic results and treatment plans, automatically paying insurance premiums, and processing specialist referrals and appointment procedures. This system is designed to enable users to receive prompt and appropriate medical care by using generative AI models to analyze diagnostic information and automate various procedures.

[1891] Hardware and Software Used

[1892] server:

[1893] A server is a computer system that receives, stores, processes data, and sends the results to other devices over a network. For example, this could include a database management system or a diagnostic algorithm running on a Linux server.

[1894] Device:

[1895] The terminal is the device used by the user, such as a smartphone, tablet, or laptop, that provides the user interface and assists in entering diagnostic information, displaying received results, and scheduling appointments with specialists.

[1896] Generative AI models:

[1897] An artificial intelligence model for analyzing diagnostic information and generating diagnostic results and treatment plans, using machine learning frameworks such as TensorFlow and PyTorch.

[1898] Processing flow

[1899] 1. The user uses the device interface to input their own health condition and diagnosis results. For example, the user enters "I've been feeling tired a lot recently" in the text box.

[1900] 2. The device formats this information (e.g., in JSON format) and sends it to the server.

[1901] 3. The server uses the received data to perform an automated review using a generative AI model. For example, it uses past diagnostic data to determine whether "easily fatigued" is an early symptom of hypothyroidism.

[1902] 4. The server generates the diagnosis and standard treatment plan (e.g., blood tests and thyroid hormone replacement therapy recommendations) and sends them to the device.

[1903] 5. The device displays the diagnosis and treatment plan to the user.

[1904] 6. The server calculates the insurance premium based on the treatment plan and uses a financial API to automatically transfer the payment to the bank account specified by the user.

[1905] 7. The server notifies the terminal of the transfer result so that the user can check it.

[1906] 8. The terminal displays a list of appropriate specialists to the user, allowing the user to select the desired specialist and make an appointment.

[1907] 9. The server sends the reservation information to the specialist, and once confirmation is received, it sends the reservation confirmation information to the terminal.

[1908] 10. The terminal displays the reservation confirmation information to the user.

[1909] 11. The user visits the specialist at the specified date and time and begins treatment based on the diagnosis results.

[1910] Examples of concrete examples and prompts

[1911] Specific examples

[1912] 1. The user types "I've been feeling very tired lately" into the device and sends it.

[1913] 2. The device sends this information to the server.

[1914] 3. The server analyzes the received data and generates a diagnosis of suspected hypothyroidism and a treatment plan.

[1915] 4. The server sends the result to the terminal and notifies the user.

[1916] 5. The server calculates the insurance premium based on the treatment plan and transfers the amount to the specified bank account.

[1917] 6. The device notifies the user of the results and provides a list of specialists.

[1918] 7. The user selects the specialist of their choice and makes an appointment.

[1919] 8. The server sends the appointment information to the specialist for confirmation.

[1920] Prompt Sentence Examples

[1921] "Have you been feeling tired more often recently?"

[1922] "A diagnosis and treatment plan have been generated. Please review the details."

[1923] "Insurance premium payment completed. Please check the results."

[1924] "Here's a list of suitable specialists. Please select one if you would like to make an appointment."

[1925] The system allows users to receive medical services efficiently and without delay, and the use of generative AI models improves the accuracy of diagnostic results and treatment plans, further enhancing user convenience.

[1926] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1927] Step 1:

[1928] The user uses the device interface to input diagnostic information about their health condition or symptoms. For example, the user might type, "I've been feeling tired a lot recently" into a text box. The input data is formatted and ready to be recognized by the system.

[1929] Step 2:

[1930] The device converts the diagnostic information entered into a standard format such as JSON and sends it to the server. The formatted data is then transferred to the server as an HTTP request.

[1931] Step 3:

[1932] The server stores the received diagnostic information in a database and starts analysis by accessing the data repository. Specifically, it executes an INSERT query in the database.

[1933] Step 4:

[1934] The server performs an automated review based on the diagnostic information. It uses a generative AI model to analyze the diagnostic information and compare it with past diagnostic data and standard treatment protocols. For example, it compares it with past patient data with the symptom of "easily fatigued" and evaluates the relevance. The input is the diagnostic information, and the output is the diagnostic results and treatment plan.

[1935] Step 5:

[1936] The server generates diagnostic results and treatment plans, which are packaged in JSON format and sent to the device. For example, the diagnostic results for hypothyroidism and the treatment plan for "thyroid hormone replacement therapy" are included. This allows the user to check the diagnostic results.

[1937] Step 6:

[1938] The terminal displays the diagnosis results and treatment plan received on the user interface. For example, the diagnosis name and recommended treatment details are displayed. Specifically, the data is displayed in the UI component.

[1939] Step 7:

[1940] The server calculates insurance premiums based on diagnosis results and treatment plans. It uses a financial API to calculate insurance premiums in real time and automatically transfers the funds to a designated bank account. The input is diagnosis results and insurance information, and the output is the transfer results.

[1941] Step 8:

[1942] The server generates the transfer result and sends it to the terminal in JSON format, such as "$200 has been transferred to the specified bank account." The terminal receives this and makes it available.

[1943] Step 9:

[1944] The terminal notifies the user of the payment result. For example, a message such as "Insurance payment has been completed. Please check the result" is displayed. Specifically, the message is displayed in the notification component.

[1945] Step 10:

[1946] The device displays a list of appropriate specialists to the user, for example, a list of categories such as "endocrinologists," and provides an interface for the user to select the desired specialist.

[1947] Step 11:

[1948] When a user selects a specialist and wishes to make an appointment, they complete the reservation procedure through their terminal. For example, they enter "I would like to make an appointment with an endocrinologist" into the reservation form. The input is sent to the server.

[1949] Step 12:

[1950] The server sends the appointment information to the specialist and confirms it. For example, it checks the appointment schedule and generates appointment confirmation information. The input is the user's appointment information, and the output is the appointment confirmation information.

[1951] Step 13:

[1952] The device displays reservation confirmation information to the user. For example, a message like "Reservation confirmed. Please confirm the date, time, and location" is displayed. Specifically, the schedule information is displayed in the calendar component.

[1953] Step 14:

[1954] The user visits a specialist at a specified date and time and begins treatment based on the diagnosis. For example, a user might visit a designated endocrinologist to receive treatment for hypothyroidism.

[1955] (Application example 1)

[1956] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1957] In modern healthcare services, to ensure patients receive prompt and appropriate diagnoses and treatment, it is necessary to streamline a series of processes, from entering and submitting diagnostic information to automatic review, notification of diagnostic results, insurance payment, specialist referrals, and appointment procedures. However, when these processes are performed manually, they require a lot of time and effort, resulting in treatment delays and patient anxiety. Furthermore, if medical data security is not ensured, there is a risk that patient privacy will be compromised. To solve these issues, an efficient and secure healthcare service delivery system is required.

[1958] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1959] In this invention, the server includes a means for inputting diagnostic information, a means for transmitting the diagnostic information to the server, a means for performing an automatic review based on the diagnostic information in the server, a means for encrypting the diagnostic information and transmitting it to the server, a means for performing an automatic review using an AI model and generating a diagnostic result, a means for processing insurance premium payments via an online payment system, and a means for synchronizing appointment information with a calendar. This enables secure transmission of diagnostic information, automated generation of diagnostic results, prompt insurance premium payment processing, and smooth appointment procedures with specialists.

[1960] "Diagnostic information" refers to information entered by a patient about their health condition or symptoms.

[1961] A "server" is a computer system that receives, stores, processes, and transmits data over a network.

[1962] "Automated review" refers to the process of using algorithms or AI models based on input diagnostic information to generate diagnostic results without manual intervention.

[1963] "Diagnostic result" means a medical judgment or diagnosis of a patient's symptoms generated by an automated review means.

[1964] A "treatment plan" refers to the specific treatment content and procedures that a patient should undergo based on the diagnostic results.

[1965] "Premiums" are the money paid by patients to cover medical expenses and are calculated based on automated screening results and treatment plans.

[1966] An "online payment system" is a system that automatically conducts monetary transactions via the Internet.

[1967] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[1968] "Appointment booking" refers to the process for booking a date and time to see a specialist.

[1969] "Calendar synchronization" means linking reservation information and other data with a digital calendar system to maintain consistency of information.

[1970] "Encryption" is a technique for converting data into a format that cannot be deciphered by third parties.

[1971] An "AI model" is a model that uses artificial intelligence algorithms to automatically extract patterns and knowledge from data and make diagnoses and predictions.

[1972] System configuration

[1973] A system for implementing this invention includes the following major components:

[1974] 1. Terminal (device used by the user)

[1975] 2. Server

[1976] 3. Network

[1977] Terminal

[1978] The terminal is a device that provides an interface for users to input diagnostic information and send it to the server. The terminal is a mobile device that can connect to the Internet, such as a smartphone or tablet. The terminal has the following functions:

[1979] Entering and sending encrypted diagnostic information (using encryption technology such as AES-256)

[1980] Notification of diagnosis and treatment plan

[1981] Displaying a list of specialists and assisting with appointment booking (Calendar synchronization using Google Calendar API)

[1982] server

[1983] The server is a computer system that receives data sent from the terminals via the network and performs automatic review and processing. The server processes the data using the following software:

[1984] Backend: Node.js and Express

[1985] Database: Use MongoDB to manage health data

[1986] AI diagnostic model: Automated screening using TensorFlow

[1987] Online payment system: Stripe API or PayPal API

[1988] Processing Details

[1989] Entering and sending diagnostic information

[1990] Users use the device to enter their diagnostic information, including details of their illness and symptoms, which is then securely transmitted to the server using AES-256 encryption.

[1991] Automated review and diagnostic generation

[1992] The server inputs the received diagnostic information into an AI diagnostic model (TensorFlow) for automatic review. It generates diagnostic results and a treatment plan using an algorithm that references past diagnostic data and standard treatment protocols, and sends them to the device.

[1993] Insurance premium payment processing

[1994] The server calculates the insurance premium based on the diagnosis results and treatment plan, and automatically processes the payment using an online payment system (such as Stripe API or PayPal API). The results are then sent to the terminal.

[1995] Specialist referrals and appointments

[1996] Based on the information received from the server, the device displays a list of appropriate specialists to the user. Once the user selects a specialist, the device uses the Google Calendar API to synchronize the appointment information with the calendar and assist with the appointment process.

[1997] Examples and prompts

[1998] Examples:

[1999] User input: "I've been feeling tired and dizzy lately."

[2000] The AI ​​model says: "These symptoms may indicate hypothyroidism. We'll provide a treatment plan based on the diagnosis and a referral specialist."

[2001] Payment procedure: "Insurance premium calculation completed. 2500 yen has been automatically paid."

[2002] Example prompt for a generative AI model:

[2003] "Create an application that uses an automated diagnostic model to generate a diagnosis based on the health information entered by the user, and then calculates insurance premiums and processes payments based on the results. It also refers users to the appropriate specialist and automatically schedules appointments."

[2004] As a result, the present invention can provide efficient and secure medical services and reduce the burden on patients.

[2005] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2006] Step 1:

[2007] User enters diagnostic information

[2008] Input: The user uses the terminal to input diagnostic information (e.g., fatigue, dizziness).

[2009] Specific operation: The user uses a smartphone or tablet to enter their symptoms into the input form of a dedicated application.

[2010] Output: Entered diagnostic information is saved to the terminal.

[2011] Step 2:

[2012] The device encrypts the diagnostic information and sends it to the server

[2013] Input: The diagnostic information entered in Step 1.

[2014] Data processing: Diagnostic information is encrypted using AES-256 encryption technology.

[2015] Specific operation: The terminal application encrypts the entered diagnostic information and sends it to the server using a secure communication protocol (HTTPS).

[2016] Output: Encrypted diagnostic information is sent to the server.

[2017] Step 3:

[2018] The server performs an automatic review based on the diagnostic information.

[2019] Input: Diagnostic information sent encrypted.

[2020] Data processing: The server decrypts the encrypted data and converts it into a format that can be input into the AI ​​diagnostic model (TensorFlow).

[2021] What it does: The server decrypts the diagnostic information and runs the AI ​​model using historical diagnostic data and standard treatment protocols.

[2022] Output: Diagnosis and treatment plan generated by the AI ​​diagnostic model.

[2023] Step 4:

[2024] The server sends the diagnosis results and treatment plan to the device.

[2025] Input: The diagnosis and treatment plan generated in step 3.

[2026] Specific operation: The server converts the diagnosis results and treatment plan into a data format (such as JSON) and sends them to the terminal.

[2027] Output: The diagnosis and treatment plan are sent to the device.

[2028] Step 5:

[2029] The device notifies you of the diagnosis and treatment plan

[2030] Input: Diagnosis and treatment plan submitted in step 4.

[2031] What it does: The device application uses notifications to display diagnostic results and treatment plans to the user.

[2032] Output: The user is informed of the diagnosis and treatment plan.

[2033] Step 6:

[2034] The server calculates and pays the insurance premiums.

[2035] Input: The treatment plan generated in step 4.

[2036] Data calculation: Calculates insurance premiums based on treatment plans and executes payment procedures via online payment systems (Stripe API or PayPal API).

[2037] Specific operation: The server analyzes the treatment plan, calculates the required insurance premium, and then calls the API of the online payment system to automatically make the payment.

[2038] Output: Premium payment result.

[2039] Step 7:

[2040] The server sends the insurance premium payment result to the terminal

[2041] Input: Premium payment results obtained in step 6.

[2042] Specific operation: The server converts the insurance premium payment results into a data format (such as JSON) that is easy for the user to understand and sends it to the terminal.

[2043] Output: The insurance premium payment result is sent to the terminal.

[2044] Step 8:

[2045] The terminal notifies the result of the insurance premium payment

[2046] Input: Premium payment result sent in step 7.

[2047] Specific operation: The terminal application uses the notification function to display the insurance premium payment result to the user.

[2048] Output: The user is notified of the insurance premium payment result.

[2049] Step 9:

[2050] The device displays a list of specialists and assists with the appointment process

[2051] Input: Treatment plan and specialist information submitted in step 4.

[2052] What it does: The device application displays a list of appropriate specialists based on the treatment plan, helps the user schedule an appointment with the selected specialist, and synchronizes the appointment information using the Google Calendar API.

[2053] Output: The user is presented with a list of specialists and is assisted in the appointment process.

[2054] Step 10:

[2055] The server sends the appointment information to the specialist

[2056] Input: Reservation information generated in step 9.

[2057] Specific operation: The server sends the appointment information to the specialist's system and confirms the appointment.

[2058] Output: Appointment information is sent to the specialist and confirmed.

[2059] Step 11:

[2060] The device will notify you of the reservation confirmation information

[2061] Input: Reservation information confirmed in step 10.

[2062] Specific behavior: The device application uses the notification function to display reservation confirmation information to the user.

[2063] Output: The user is notified of the reservation confirmation.

[2064] These steps ensure that the process proceeds efficiently, enabling users to receive prompt and appropriate medical services.

[2065] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2066] overview

[2067] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. Furthermore, by incorporating an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, the system provides optimal medical services according to the user's psychological state.

[2068] System configuration

[2069] server

[2070] A server is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[2071] The server receives the diagnostic information sent by the user, performs an automated review, and generates a diagnostic result and a treatment plan.

[2072] The server uses algorithms to reference past diagnostic data and standard treatment protocols to improve the accuracy of diagnostic results and treatment plans.

[2073] The server automatically performs the insurance premium payment procedure and transfers the money to the designated bank account.

[2074] The server manages a list of appropriate specialists and refers users to specialists based on their treatment plans.

[2075] The server includes an emotion engine that analyzes the user's emotion data and customizes the diagnosis and treatment plan.

[2076] Terminal (device used by the user)

[2077] The terminal provides an interface for the user to input diagnostic information.

[2078] The terminal transmits the diagnostic information to the server, receives the processing results, and notifies the user.

[2079] The terminal displays the diagnostic results and treatment plan and suggests next actions to the user.

[2080] The terminal provides a function to assist the user in making an appointment with a specialist.

[2081] The terminal transmits the user's emotion data generated by the emotion engine to the server.

[2082] User (patient)

[2083] The user inputs their own health condition and diagnosis results through the terminal.

[2084] The user reviews the provided diagnosis and treatment plan, selects an appropriate specialist, and makes an appointment.

[2085] The user carries out the next treatment procedure based on the insurance payment result and the treatment plan.

[2086] The user's emotional data is appropriately evaluated by the system and a customized treatment plan is then provided.

[2087] Program processing explanation

[2088] Entering and sending diagnostic information

[2089] The user inputs their own health condition and diagnosis results into the terminal. For example, the user inputs, "I've been feeling tired a lot recently."

[2090] The terminal formats this data and sends it to the server.

[2091] Automated review and diagnostic generation

[2092] The server performs an automated review of the diagnostic information it receives, using algorithms to compare it with past cases and standard diagnostic protocols to see if the symptom of "easily tired" is related to hypothyroidism or other diseases.

[2093] The server generates and provides diagnostic results and standard treatment plans to the user.

[2094] Analysis and customization with emotion engine

[2095] The device generates emotion data based on the user's input and sends it to the server. For example, it determines that the user is feeling anxious or stressed based on the input information.

[2096] The server analyzes the emotional data using an emotion engine to customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, stress management advice and mental health support will be added to the treatment plan.

[2097] Premium payment processing and notification

[2098] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the payment to the designated bank account.

[2099] The server sends the payment result to the terminal and notifies the user.

[2100] Specialist opinion and referral

[2101] Based on the data received from the server, the terminal displays a list of appropriate specialists to the user. If the user wishes to see a specialist, they can make an appointment through the terminal interface.

[2102] The server sends the appointment information to the specialist for confirmation.

[2103] Confirm appointment and start treatment

[2104] The device displays appointment confirmation information and the user prepares to see a specialist and receive treatment.

[2105] The user visits the specialist at the specified date and time and begins consultation and treatment based on the treatment plan.

[2106] The above configuration and functions enable users to receive prompt and accurate medical services, and by incorporating an emotion engine, the system provides optimal treatment plans based on the user's psychological state.In addition, the automation of insurance payment procedures prevents delays in treatment.

[2107] The processing flow will be explained below.

[2108] Step 1:

[2109] The user inputs their own health condition and diagnosis results into the device application.

[2110] Specifically, the user inputs, "I have been feeling tired frequently for the past month."

[2111] Step 2:

[2112] The terminal formats the entered diagnostic information and sends it to the server.

[2113] Specifically, the input data is converted into JSON format and sent using a secure communication protocol (e.g., HTTPS).

[2114] Step 3:

[2115] The server stores the received diagnostic information in a database.

[2116] Specifically, the received data is validated and stored in the appropriate database tables.

[2117] Step 4:

[2118] The server will start the automatic review.

[2119] Specifically, algorithms are applied based on the stored diagnostic information to begin the process of matching it with similar past cases and standard diagnostic protocols.

[2120] Step 5:

[2121] The server generates a diagnosis and a standard treatment plan.

[2122] Specifically, it estimates the medical conditions with a high probability of diagnosis and lists recommended treatments based on that. For example, it might generate a message such as, "A thyroid abnormality is suspected, so a blood test is required."

[2123] Step 6:

[2124] The server sends the generated diagnostic results and treatment plan to the terminal.

[2125] Specifically, the diagnosis results and treatment plan are encoded in JSON format and sent to the terminal.

[2126] Step 7:

[2127] The terminal notifies the user of the received diagnosis results and treatment plan.

[2128] Specifically, when the user opens the application, the results are displayed in a pop-up notification or email notification.

[2129] Step 8:

[2130] The user inputs their own feelings based on the diagnosis results.

[2131] Specifically, after being notified that a blood test is required as a diagnostic result, the user inputs, "I feel uneasy about this result."

[2132] Step 9:

[2133] The terminal formats the user's emotional data and sends it to the server.

[2134] Specifically, the user emotion data is converted into JSON format and sent to the server.

[2135] Step 10:

[2136] The server executes an emotion engine based on the received emotion data.

[2137] Specifically, the system analyzes emotional data to assess the user's psychological state, and if, for example, anxiety levels are high, it adjusts the treatment plan accordingly.

[2138] Step 11:

[2139] The server uses the analysis results from the emotion engine to customize a treatment plan.

[2140] Specifically, for users with high levels of anxiety, a treatment plan is generated that recommends stress management advice and relaxation techniques.

[2141] Step 12:

[2142] The server sends the customized treatment plan to the device.

[2143] Specifically, the customized treatment plan is encoded in JSON format and sent to the device.

[2144] Step 13:

[2145] The device notifies the user of the customized treatment plan.

[2146] Specifically, when a user opens the application, a pop-up notification or email notification displays the customized treatment plan.

[2147] Step 14:

[2148] The server automates the insurance payment process.

[2149] Specifically, the cost of the diagnosis and treatment plan is calculated and an automatic transfer procedure is carried out to a designated bank account.

[2150] Step 15:

[2151] The server sends a notification of payment completion to the terminal.

[2152] Specifically, the transfer success status and detailed information are sent to the terminal.

[2153] Step 16:

[2154] The terminal displays a notification to the user that the payment has been completed.

[2155] Specifically, the application's notification bar or email notification is used to notify the user that the payment has been completed.

[2156] Step 17:

[2157] The server generates a list of specialists based on the treatment plan and sends it to the terminal.

[2158] Specifically, the system selects appropriate doctors from a database of specialists, creates a list, and sends it to the terminal.

[2159] Step 18:

[2160] The terminal displays a list of specialists to the user.

[2161] Specifically, when a user opens the application, it displays a list of specialists.

[2162] Step 19:

[2163] The user selects the desired specialist and makes a reservation.

[2164] Specifically, fill out the reservation form within the application and press the submit button.

[2165] Step 20:

[2166] The terminal sends the reservation procedure to the server.

[2167] Specifically, the reservation information is sent to the server, and the server returns a confirmation message.

[2168] Step 21:

[2169] The server sends the appointment information to the specialist for confirmation.

[2170] Specifically, reservation information is sent to the specialist's system, and once the reservation is confirmed, a confirmation message is received from the specialist.

[2171] Step 22:

[2172] The terminal notifies the user of the reservation confirmation information.

[2173] Specifically, the user is notified that the reservation has been confirmed, and details of the reservation date, time, and location are displayed.

[2174] Through these processing steps, users can receive a quick and accurate diagnosis and treatment. Furthermore, the introduction of an emotion engine provides an optimal treatment plan based on their psychological state. Furthermore, the automated payment procedures for insurance premiums prevent delays in treatment.

[2175] Example 2

[2176] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2177] Conventional medical systems require users to input and submit diagnostic information, automatically review it, receive notifications of diagnostic results and treatment plans, automatically pay insurance premiums, and refer and schedule appointments, all individually, which takes time and effort. Furthermore, they do not provide customized treatment plans that take into account the user's psychological state, which reduces user satisfaction.

[2178] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting diagnostic information, means for transmitting the diagnostic information to the server, means for performing automatic examination based on the diagnostic information in the server, means for receiving and notifying the diagnostic results and treatment plan generated by the automatic examination, means for processing insurance premium payment based on the treatment plan, means for notifying the insurance premium payment result, means for referring to a specialist based on the treatment plan, means for supporting the appointment procedure with the specialist, means for generating user emotion data and transmitting it to the server, and means for analyzing the emotion data and customizing the diagnostic results and treatment plan. This allows users to receive prompt and accurate medical services. Furthermore, by incorporating an emotion engine, an optimal treatment plan tailored to the user's psychological state can be provided, thereby eliminating dissatisfaction.

[2179] "Diagnostic information" is information about health conditions and symptoms entered by the user.

[2180] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[2181] "Automatic review" refers to the process of analyzing and making judgments based on the diagnostic information received by the server using machine learning algorithms and databases.

[2182] A "diagnosis result" is a conclusion regarding the user's health condition obtained through an automated screening.

[2183] A "treatment plan" is a proposed treatment policy or procedure based on diagnostic results.

[2184] "Premium" is an amount calculated to subsidize a portion of a user's medical expenses.

[2185] "Automatic transfer procedure" is a process in which the server automatically transfers the amount to a specified bank account.

[2186] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[2187] The "reservation procedure" is a procedure for reserving a consultation time with a specialist in advance.

[2188] "Emotion data" is data relating to a psychological state generated by an emotion engine from information input by a user.

[2189] The "emotion engine" is an algorithm and module for analyzing a user's emotional data and customizing diagnostic results and treatment plans.

[2190] overview

[2191] This system efficiently processes the input, transmission, and automatic review of diagnostic information, notification of diagnostic results and treatment plans, automatic payment of insurance premiums, and referral and appointment procedures for specialists. It also incorporates an emotion engine that recognizes the user's emotions and customizes the diagnosis and treatment plan based on those emotions, providing optimal medical services according to the user's psychological state.

[2192] System Configuration

[2193] server

[2194] The server is a computer system that receives, stores, processes, and transmits data to other devices via a network. Specifically, it automatically reviews diagnostic information and generates diagnostic results and treatment plans. It also automatically processes insurance payments and performs specialist referrals and appointment confirmations. Furthermore, the server is equipped with an emotion engine that analyzes users' emotional data and customizes diagnostic results and treatment plans.

[2195] Terminal

[2196] The terminal is a device that provides an interface for users to input diagnostic information. It has the function of formatting the user's input information and sending it to the server. It also receives and notifies the user of diagnostic results and treatment plans, and assists in the specialist appointment process.

[2197] User

[2198] Users can input their symptoms and emotional state through a terminal, check the diagnosis results and treatment plans provided by the system, make appointments with specialists, and check the results of insurance premium payments.

[2199] Hardware and software used

[2200] Server: High-performance cloud computing services (e.g., AWS, Google Cloud)

[2201] Devices: Smartphones, tablets, PCs

[2202] Emotion engine: Machine learning algorithms (e.g. TensorFlow, PyTorch)

[2203] Specific Examples

[2204] Entering and sending diagnostic information

[2205] The user inputs their own health condition and diagnosis results into a dedicated smartphone app. For example, they might enter, "I've been feeling tired a lot recently." The device then formats this information and sends it to the server.

[2206] Automated screening and diagnostic results generation

[2207] The server automatically reviews the diagnostic information it receives. The algorithm compares it with past cases and standard diagnostic protocols to generate a diagnosis and treatment plan. For example, it may determine that the symptom of "easily tired" is a possible sign of hypothyroidism and recommend a blood test.

[2208] Analysis and customization with emotion engine

[2209] The device generates emotion data from the user's input and sends it to the server, which uses an emotion engine to analyze this data and customize the diagnosis and treatment plan. For example, if the user indicates high stress levels, it may add stress management advice.

[2210] Processing premium payments

[2211] The server calculates the insurance premium based on the diagnosis and treatment plan, performs the automatic transfer procedure, and sends the transfer result to the terminal and notifies the user.

[2212] Specialist referrals and appointment procedures

[2213] Based on the data received by the terminal, a list of appropriate specialists is displayed to the user, and the server sends the appointment information to the specialist selected by the user for confirmation.

[2214] Prompt Sentence Examples

[2215] "A 45-year-old woman has recently been experiencing frequent fatigue and headaches. Based on this information, please suggest a diagnosis and treatment plan. Also, please use the emotion engine to take into account emotional data."

[2216] This system allows users to receive prompt and accurate medical services, and by incorporating an emotion engine, it provides optimal treatment plans based on the user's psychological state.In addition, the system automates insurance payment procedures, preventing delays in treatment.

[2217] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2218] System program processing flow

[2219] Step 1: Enter diagnostic information

[2220] Input: User inputs their health condition and symptoms

[2221] Processing: The terminal receives and formats the incoming data.

[2222] Output: Formatted diagnostic information

[2223] Specific behavior:

[2224] The user opens a dedicated smartphone app and enters information about their symptoms. For example, they might enter, "I've been feeling tired a lot recently." The device then converts this information into a format such as "Symptom: Fatigue easily" and "Start date: 2 weeks ago."

[2225] Step 2: Send diagnostic information

[2226] Input: Formatted diagnostic information

[2227] Action: The device sends formatted diagnostic information to the server.

[2228] Output: Diagnostic information sent to the server

[2229] Specific behavior:

[2230] The device sends formatted diagnostic information to the server using a security protocol (e.g., HTTPS). The information sent includes, for example, "Symptom: fatigue easily" and "Start time: 2 weeks ago."

[2231] Step 3: Automated review and diagnostic results generation

[2232] Input: Diagnostic information received by the server

[2233] Processing: The server performs automated review using machine learning algorithms

[2234] Output: Diagnostic results and treatment plan

[2235] Specific behavior:

[2236] The server compares the received diagnostic information with past cases and standard diagnostic protocols to generate a diagnosis. For example, if it determines that the symptom of "easily fatigued" is related to hypothyroidism, it generates a diagnosis result of "suspected hypothyroidism" and a treatment plan of "recommended blood test."

[2237] Step 4: Notification of diagnosis and treatment plan

[2238] Input: Diagnosis and treatment plan

[2239] Processing: The server sends the diagnosis results and treatment plan to the device.

[2240] Output: Diagnostic results and treatment plan received by the user

[2241] Specific behavior:

[2242] The server sends the generated diagnosis and treatment plan to the device, which notifies the user and displays on the screen, "Diagnosis: Suspected hypothyroidism" and "Treatment plan: Blood test recommended."

[2243] Step 5: Generate and send emotion data

[2244] Input: User input information

[2245] Processing: The device generates emotion data using the emotion recognition API and sends it to the server.

[2246] Output: Emotion data sent to the server

[2247] Specific behavior:

[2248] The device generates emotional data from the user's input. For example, the system can detect a high stress level based on the frequency of the word "fatigue" and the user's use of the word, and format the emotional data as "Stress level: high." This emotional data is then sent to the server.

[2249] Step 6: Analyze sentiment data and customize diagnosis

[2250] Input: Emotion data

[2251] Processing: The server uses an emotion engine to analyze the emotion data and customize the diagnosis and treatment plan.

[2252] Output: Customized diagnostic results and treatment plans

[2253] Specific behavior:

[2254] The server analyzes the emotion data and updates the diagnosis and treatment plan, for example, customizing it as "Diagnosis: Suspected hypothyroidism, Treatment plan: Recommend blood test + Recommend mental health support for stress management."

[2255] Step 7: Process premium payments

[2256] Input: Diagnosis and treatment plan

[2257] Processing: The server calculates the insurance premium and processes the automatic transfer.

[2258] Output: Notification of transfer completion

[2259] Specific behavior:

[2260] The server calculates the insurance premium based on the diagnosis and treatment plan, and automatically transfers the money to the user's bank account. After the transfer is complete, the result is sent to the terminal. The terminal then notifies the user that "the insurance payment has been transferred."

[2261] Step 8: Specialist referral

[2262] Input: Customized diagnostic results and treatment plans

[2263] Action: The device displays a list of appropriate specialists to the user.

[2264] Output: List of specialists and available appointments

[2265] Specific behavior:

[2266] Based on the information received from the server, the device displays a list of appropriate specialists to the user. For example, the user is provided with information such as "Thyroid specialist: Dr. Smith, available appointments: Monday 14:00-16:00."

[2267] Step 9: Book an appointment with a specialist

[2268] Input: User reservation information

[2269] Processing: The server sends the appointment information to the specialist and confirms it.

[2270] Output: Reservation confirmation information

[2271] Specific behavior:

[2272] A user makes an appointment with a specialist through a terminal. The server sends the appointment information to the specialist's system and receives confirmation from the specialist. Once the appointment is confirmed, the terminal displays a message saying, "Your appointment has been confirmed. Please see Dr. Smith at 2:00 PM on Monday."

[2273] Step 10: Confirm appointment and start treatment

[2274] Input: Reservation confirmation information

[2275] Action: User consults a specialist

[2276] Output: Examination and treatment results

[2277] Specific behavior:

[2278] The user visits the specialist at the scheduled time and receives the consultation and any necessary tests or treatment. The specialist explains the results of the consultation to the user and provides a plan for any further treatment or tests that may be required.

[2279] Through these steps, the system can provide users with fast and accurate medical services and customize the optimal treatment plan according to the user's emotional state.

[2280] (Application example 2)

[2281] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2282] In today's healthcare system, the process of entering diagnostic information, obtaining diagnostic results, receiving treatment plans, paying insurance premiums, and referrals and appointment bookings is often not smooth, resulting in delays and inaccuracies. Properly assessing users' psychological state and providing optimal treatment plans is also a major challenge. While it is particularly important for online healthcare services to properly analyze users' emotions and reflect them in diagnostic results and treatment plans, effective systems for achieving this are currently lacking.

[2283] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2284] In this invention, the server includes a means for transmitting diagnostic information to the server, a means for performing automated review, and a means for utilizing an emotion engine to customize diagnostic results and treatment plans, thereby enabling the provision of highly accurate diagnostic results and treatment plans tailored to the user's emotional state.

[2285] "Diagnostic Information" is data entered by a user about their health condition or symptoms.

[2286] A "server" is a computer system that receives, stores, processes data, and transmits the results to other devices over a network.

[2287] "Automated review" is the process by which the server uses algorithms to reference past diagnostic data and standard treatment protocols based on the diagnostic information received, to generate a diagnostic result and treatment plan.

[2288] A "treatment plan" is a set of medical procedures or instructions provided to a user based on a diagnosis.

[2289] "Premium" means money paid to cover a user's medical expenses and treatment costs.

[2290] The "emotion engine" is part of a system that analyzes emotional data based on user input and customizes diagnostic results and treatment plans.

[2291] A "specialist" is a doctor who has advanced knowledge and skills in a particular medical field.

[2292] A "user" is a person who uses the diagnostic system to input information about their health condition and receive diagnostic results and treatment plans.

[2293] This invention is a system that efficiently inputs, transmits, and automatically reviews diagnostic information, notifies users of diagnostic results and treatment plans, processes insurance premium payments, and provides referrals and appointment procedures to specialists, while also providing optimal medical services that reflect the user's feelings.

[2294] System configuration

[2295] 1. Server

[2296] A server is a computer system that receives, stores, and processes data over a network. The specific software used is the Django framework.

[2297] Diagnostic information is received and automatically reviewed using algorithms (e.g., machine learning models) that reference previous diagnostic data and standard treatment protocols.

[2298] It generates diagnostic results and treatment plans, and also customizes them based on the user's emotional data using an emotion engine, which uses generative AI models such as TensorFlow.

[2299] The insurance premium payment is automatically made and the user is notified of the result.

[2300] An appropriate specialist will be selected from the list and referred to the user.

[2301] 2. Terminal

[2302] The terminal is a smartphone or PC that provides an interface for the user to input diagnostic information.

[2303] The diagnostic information is formatted and sent to the server, and the processing results are received and notified to the user. The specific software is a smartphone app developed using React Native.

[2304] It displays diagnostic results and treatment plans and suggests next actions for the user (such as scheduling an appointment with a specialist).

[2305] The emotion data generated by the emotion engine is transmitted to the server.

[2306] 3. Users

[2307] Users enter information about their health condition and symptoms through the device.

[2308] Review the provided diagnosis and treatment plan, select the appropriate specialist, and schedule an appointment.

[2309] Treatment is provided based on the results of insurance payment processing and treatment plan.

[2310] The emotional data is evaluated by the system and a customized treatment plan is given.

[2311] Specific examples of processing and prompt statements

[2312] As a concrete example, consider the case where a user enters into a device, "I've been feeling tired and stressed recently." The device formalizes this information and sends it to the server. The server then performs an automatic review based on the received data and generates a diagnosis of "suspected hypothyroidism." At the same time, the emotion engine recognizes high stress levels and generates a treatment plan of "blood tests, hormone therapy, and stress management advice," and notifies the user.

[2313] Example prompt sentence:

[2314] "Take user input: 'I've been feeling tired and stressed lately,' and use an emotion engine to analyze their stress level and generate a corresponding diagnosis and customized treatment plan."

[2315] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2316] Step 1:

[2317] The user inputs their health condition and symptoms into the device.

[2318] Type: "I've been feeling tired and stressed lately."

[2319] The device receives information about the user's health condition and symptoms, formats this information, and prepares it as data to send to the server.

[2320] Output: Formatted diagnostic information

[2321] Step 2:

[2322] The device sends formatted diagnostic information to the server

[2323] Input: Formatted diagnostic information

[2324] The terminal establishes a network connection to transmit the formatted diagnostic information to the server, and upon completion of the transmission, the terminal receives a transmission completion status.

[2325] Output: Diagnostic information sending completion status

[2326] Step 3:

[2327] The server performs an automatic review based on the diagnostic information received.

[2328] Input: Formatted diagnostic information

[2329] The server inputs the received diagnostic information into an algorithm and automatically diagnoses the patient by referencing past diagnostic data and standard treatment protocols. Specifically, it performs pattern recognition and comparison ...

Claims

1. a means for inputting diagnostic information; means for transmitting the diagnostic information to a server; means for performing an automatic examination based on the diagnostic information in the server; means for receiving and communicating the diagnosis and treatment plan generated by said automated review; means for processing insurance payments based on said treatment plan; a means for notifying the result of said insurance premium payment; a means for referring a patient to a specialist based on said treatment plan; a means for assisting in the appointment process with the specialist; A system including:

2. 10. The system of claim 1, wherein the automated review means uses an algorithm that references past diagnostic data and standard treatment protocols.

3. 2. The system according to claim 1, wherein the insurance premium payment means is an automatic transfer procedure to a bank account.

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