system

Abstract

To provide a system capable of easily performing appropriate measures tailored to a physical condition and a health status of an individual user.SOLUTION: A system includes means for inputting user's physical symptoms, means for preparing a prompt sentence to instruct to specify nutrients required to improve the symptoms on the basis of the inputted symptoms, means for specifying the nutrients required to improve the user's physical symptoms by using the prepared prompt sentence and a generative AI model, means for recommending foods or supplements containing specified nutrients, and means for generating a link to purchase the recommended foods or supplements to display them on a user's terminal screen.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, interest in health and beauty is on the rise. However, it is difficult to make appropriate decisions based on one's own physical condition and nutritional status. In addition, there is a lack of information on how to properly consume the necessary nutrients, and there is a lack of ways to directly communicate with medical institutions or doctors when necessary. [Means for solving the problem]

[0005] This invention identifies bodily signs (symptoms) and uses generative AI based on that information to identify nutritional deficiencies and excesses. Based on the results, it then recommends necessary nutrients (foods, supplements, meals, etc.) and allows users to directly purchase the recommended nutrients. Furthermore, it provides a means to directly communicate with medical institutions and doctors as needed. This makes it easy to take appropriate measures tailored to each individual's physical condition and nutritional status. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention is equipped with an interface that allows users to input their own physical condition and symptoms. This interface can be realized, for example, through a smartphone, a PC application, or a website. The user inputs specific details about their physical condition and symptoms. For example, the user can input information such as "I have a headache" or "I get tired easily."

[0029] "Example 2"

[0030] Next, the system of the present invention utilizes generative AI based on the input of the user's physical condition and symptoms. This AI identifies the appropriate nutrients for the user's physical condition and symptoms from online medical information and nutrition databases. For example, if the user says "I have a headache," it determines that the user may be deficient in magnesium or vitamin B2.

[0031] "Example 3"

[0032] Based on the nutrients identified, the system of the present invention recommends foods, supplements, and dishes containing the necessary nutrients. For example, for a user who has a headache, it would recommend foods such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[0033] "Example 4"

[0034] Furthermore, the system of the present invention provides a function to directly purchase the recommended foods and supplements. For example, it provides recipes containing recommended bananas, almonds, and liver along with links to purchase these ingredients online.

[0035] "Example 5"

[0036] The system of the present invention also provides a function to directly communicate with medical institutions or doctors as needed. For example, if your condition does not improve or if certain symptoms persist, the system will refer you to a specialized medical institution or doctor and arrange an online consultation.

[0037] The processing flow of each embodiment will be described below.

[0038] "Example 1"

[0039] Step 1: The user accesses the system of the present invention and specifically inputs their physical condition and symptoms. For example, they input information such as "I have a headache" or "I get tired easily."

[0040] Step 2: The system of the present invention uses generative AI to identify appropriate nutrients based on the input physical condition and symptoms. This AI identifies appropriate nutrients for the user's physical condition and symptoms from online medical information and nutrition databases.

[0041] Step 3: Based on the identified nutrients, the system of the present invention recommends foods, supplements, and recipes that contain the necessary nutrients.

[0042] Step 4: The system of the present invention provides the ability to directly purchase the recommended foods and supplements. Along with recipes containing the recommended bananas, almonds, and liver, it provides links to purchase these ingredients online.

[0043] Step 5: The system of the present invention also provides the ability to directly communicate with medical institutions or doctors as needed. If your condition does not improve or if certain symptoms persist, the system will refer you to a specialized medical institution or doctor and arrange an online consultation.

[0044] Example 1

[0045] Next, a description will be given of Example 1 of Form 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."

[0046] In modern society, many people need to quickly and accurately understand information about their own physical condition and symptoms and receive appropriate advice. However, conventional systems have difficulty providing appropriate advice based on the physical condition and symptoms entered by the user, and do not adequately recommend necessary nutrients or connect with medical institutions. This makes it difficult for users to properly manage their own health condition.

[0047] 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.

[0048] In this invention, the server includes means for inputting physical signs (symptoms), means for transmitting the physical signs (symptoms) to the server, means for generating advice using a generative AI model based on the physical signs (symptoms), means for transmitting the generated advice to a terminal, means for displaying the generated advice on the terminal, means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the generated advice, means for directly purchasing the recommended nutrients, and means for directly communicating with a medical institution or doctor as needed. This allows the user to quickly receive appropriate advice based on their own physical condition and symptoms, and also enables smooth recommendation of necessary nutrients and collaboration with medical institutions.

[0049] "Physical signs (symptoms)" refer to any abnormalities or discomforts that a user feels regarding their physical condition or health.

[0050] "Input means" refers to the interface through which the user inputs physical signs (symptoms) into the system. Specifically, this includes smartphone and PC applications, websites, etc.

[0051] "Means of transmission" refers to the communication means used to send the physical signs (symptoms) entered by the user to the server. Specifically, this includes HTTP requests using an Internet connection.

[0052] "Generative AI models" refer to artificial intelligence models that generate appropriate advice based on user input. Specifically, they include generative AI models that use natural language processing technology.

[0053] "Means for generating advice" refers to the process of using a generative AI model to generate advice based on the user's physical signs (symptoms).

[0054] "Means for sending to the terminal" refers to a communication means for sending the generated advice to the user's terminal. Specifically, this includes HTTP responses, etc.

[0055] "Displaying means" refers to an interface for visually displaying the generated advice to the user on the device, including, for example, a UI component of an application or an element of a web page.

[0056] "Means for recommending necessary nutrients" refers to a process for recommending necessary nutrients (foods, supplements, dishes, etc.) to a user based on the generated advice.

[0057] "Direct purchasing means" refers to an interface through which a user can directly purchase the recommended nutrients, specifically including online shopping functionality.

[0058] "Means for directly communicating with medical institutions or doctors" refers to means by which users can directly communicate with medical institutions or doctors as needed. Specifically, this includes video calls and chat functions.

[0059] MODE FOR CARRYING OUT THE INVENTION

[0060] This invention is a system that allows users to input their own physical condition and symptoms, and then uses a generative AI model to provide appropriate advice based on that information. This system can be implemented via smartphone or PC applications, websites, etc.

[0061] User Input

[0062] Users input their physical condition and symptoms using a smartphone or PC application or website. For example, a user might enter, "I've been having frequent headaches lately." This input is done through a text box or form in the application.

[0063] Sending data

[0064] The device sends the information about the user's physical condition and symptoms to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is encoded in JSON format.

[0065] Receiving and analyzing data

[0066] The server receives the data sent from the device. The server analyzes the received data and extracts the user's input. For example, the server analyzes the text "I've been having frequent headaches lately" and passes it to the next processing step.

[0067] Advice generation using generative AI models

[0068] The server uses a generative AI model (e.g., a generative AI model using natural language processing technology) to generate advice based on the user's input. Specifically, the server inputs the following prompt sentence into the generative AI model:

[0069] User input: I've been having a lot of headaches lately.

[0070] Prompt for generative AI model: User inputs "I've been having a lot of headaches lately." Please provide appropriate advice.

[0071] The generative AI model generates advice based on this prompt, for example, "We recommend you drink plenty of fluids. If symptoms persist, consult your doctor."

[0072] Sending the results

[0073] The server sends the advice generated by the generative AI model to the terminal. Specifically, the server encodes the generated advice in JSON format and sends it as an HTTP response.

[0074] Displaying the results

[0075] The device displays the advice received from the server to the user. Specifically, the device displays the generated advice using the application's UI components (e.g., a text view or a popup message). The user can view the advice through the application.

[0076] Recommendations for necessary nutrients

[0077] Based on the generated advice, the server recommends the necessary nutrients (foods, supplements, dishes, etc.) to the user. For example, it makes a specific recommendation such as "We recommend that you consume foods that are high in vitamin C."

[0078] Direct purchase of nutrients

[0079] Users can directly purchase the recommended nutrients, specifically by using the online shopping function through the application or website to purchase the recommended foods and supplements.

[0080] Cooperation with medical institutions and doctors

[0081] If necessary, users can talk directly to medical institutions and doctors, specifically by using video calls and chat functions to communicate with doctors in real time.

[0082] In this way, the system of the present invention allows users to quickly receive appropriate advice based on their own physical condition and symptoms, and also makes it possible to smoothly recommend necessary nutrients and collaborate with medical institutions.

[0083] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0084] Program processing flow

[0085] Step 1: User Input

[0086] Users input their physical condition and symptoms using a smartphone or PC application or website. For example, a user might enter, "I've been having frequent headaches lately." This input is done through a text box or form in the application.

[0087] Input: Text data of the user's physical condition and symptoms

[0088] Output: The input text data

[0089] Step 2: Sending data

[0090] The device sends the information about the user's physical condition and symptoms to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is encoded in JSON format.

[0091] Input: Text data entered by the user

[0092] Output: JSON formatted data sent to the server

[0093] Step 3: Receiving and analyzing data

[0094] The server receives the data sent from the device. The server analyzes the received data and extracts the user's input. For example, the server analyzes the text "I've been having frequent headaches lately" and passes it to the next processing step.

[0095] Input: JSON format data sent from the terminal

[0096] Output: Parsed text data

[0097] Step 4: Generative AI model generates advice

[0098] The server uses a generative AI model (e.g., a generative AI model using natural language processing technology) to generate advice based on the user's input. Specifically, the server inputs the following prompt sentence into the generative AI model:

[0099] User input: I've been having a lot of headaches lately.

[0100] Prompt for generative AI model: User inputs "I've been having a lot of headaches lately." Please provide appropriate advice.

[0101] The generative AI model generates advice based on this prompt, for example, "We recommend you drink plenty of fluids. If symptoms persist, consult your doctor."

[0102] Input: Parsed text data

[0103] Output: Text data of the generated advice

[0104] Step 5: Sending the results

[0105] The server sends the advice generated by the generative AI model to the terminal. Specifically, the server encodes the generated advice in JSON format and sends it as an HTTP response.

[0106] Input: Text data of generated advice

[0107] Output: Advice data sent to the terminal in JSON format.

[0108] Step 6: View the results

[0109] The device displays the advice received from the server to the user. Specifically, the device displays the generated advice using the application's UI components (e.g., a text view or a popup message). The user can view the advice through the application.

[0110] Input: Advice data received from the server in JSON format

[0111] Output: The text of the advice displayed to the user.

[0112] Step 7: Recommending Nutrient Needs

[0113] Based on the generated advice, the server recommends the necessary nutrients (foods, supplements, dishes, etc.) to the user. For example, it makes a specific recommendation such as "We recommend that you consume foods that are high in vitamin C."

[0114] Input: Text data of generated advice

[0115] Output: Text data of recommended nutrients

[0116] Step 8: Buy nutrients directly

[0117] Users can directly purchase the recommended nutrients, specifically by using the online shopping function through the application or website to purchase the recommended foods and supplements.

[0118] Input: Text data of recommended nutrients

[0119] Output: Purchase completion notification

[0120] Step 9: Collaboration with medical institutions and doctors

[0121] If necessary, users can talk directly to medical institutions and doctors, specifically by using video calls and chat functions to communicate with doctors in real time.

[0122] Input: Information about the user's health and symptoms

[0123] Output: Communication logs with medical institutions and doctors

[0124] (Application example 1)

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

[0126] Conventional health management systems have the problem that users only need to input their own health condition and symptoms, making it difficult to take prompt action when an abnormality is detected. Furthermore, there is a lack of a means to send appropriate notifications when an abnormality is detected, and measures to ensure user safety are insufficient. This makes it difficult for users to quickly access appropriate medical institutions and emergency contacts in the event of an emergency.

[0127] 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.

[0128] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with medical institutions or doctors as needed, means for detecting abnormalities based on the bodily signs (symptoms) and sending notifications, and communication means for sending the notifications. This allows the user not only to input their own physical condition and symptoms, but also to quickly send notifications when abnormalities are detected and take appropriate action.

[0129] "Physical signs (symptoms)" refers to specific information about a user's physical condition or health status.

[0130] "Generative AI" is an artificial intelligence technology that analyzes data on physical condition and symptoms entered by the user and provides appropriate nutritional and medical information.

[0131] "Nutrition deficiency" is information that indicates whether the user is lacking or over-dosing on necessary nutrients based on their physical condition and symptoms.

[0132] "Essential nutrients" are the nutritional components of foods, supplements, dishes, etc. that are recommended to improve the user's health.

[0133] "Recommendation methods" are methods that suggest appropriate nutrients to users based on the results of analysis by generative AI.

[0134] "Direct purchasing means" refers to a method that allows users to purchase the recommended nutrients on-site.

[0135] "Direct communication with healthcare providers and physicians" means a method by which users can communicate with healthcare professionals in real time as needed.

[0136] "Means for detecting abnormalities" refers to a method for analyzing data on physical condition and symptoms entered by the user and determining whether or not there is an abnormality.

[0137] "Means for sending notifications" refers to the method for sending warnings and information to users and emergency contacts when an abnormality is detected.

[0138] "Communication means" refers to the communication technology, such as the internet or mobile network, used to send the notification.

[0139] As an embodiment of the present invention, the following system can be constructed.

[0140] System configuration

[0141] The system consists of a device (such as a smartphone or PC) with an interface for inputting the user's physical condition and symptoms, and a server for analyzing the data. The server uses a generative AI model to analyze the data and detect necessary nutrients and abnormalities.

[0142] Program processing

[0143] Hardware

[0144] Smartphone

[0145] PC

[0146] server

[0147] software

[0148] Python

[0149] The requests library (to send HTTP requests)

[0150] Generative AI Model

[0151] Data processing and calculation

[0152] 1. Data input: Users enter their own physical condition and symptoms through a smartphone or computer interface. For example, they enter specific information such as "I have a headache" or "I get tired easily."

[0153] 2. Data analysis: The server uses a generative AI model to analyze the input data, identify nutritional deficiencies and excesses, and determine the appropriate response if an abnormality is detected.

[0154] 3. Recommendations and Notifications: The server recommends necessary nutrients to the user based on the analysis results. Furthermore, if an abnormality is detected, a notification will be sent to the user or emergency contacts via communication means.

[0155] Specific examples

[0156] For example, if a user types "I have a headache," the server uses a generative AI model to analyze this information and identify possible nutrient deficiencies or excesses that could be causing the headache. It then recommends the necessary nutrients (such as magnesium or B vitamins) to the user. Furthermore, if an abnormality is detected, a notification is sent to emergency contacts to prompt appropriate action.

[0157] Prompt Sentence Examples

[0158] "Write a Python program that analyzes the user's physical condition and symptoms and sends a notification if an abnormality is detected. Anomalies will be detected based on specific keywords (e.g. headache, fatigue, dizziness, chest pain). Notifications will be sent using an HTTP POST request."

[0159] In this way, a system can be realized in which a user simply inputs their own physical condition and symptoms, and if an abnormality is detected, a notification is sent quickly and appropriate action can be taken.

[0160] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0161] Step 1:

[0162] Users input their physical condition and symptoms through a smartphone or computer interface.

[0163] Input: Information about your physical condition or symptoms entered by the user (e.g., "I have a headache" or "I get tired easily").

[0164] Output: Input data on physical condition and symptoms.

[0165] Specific operation: The user launches the application, enters their physical condition and symptoms in the text box, and presses the send button.

[0166] Step 2:

[0167] The device sends the entered data on physical condition and symptoms to the server.

[0168] Input: Physical condition and symptom data entered by the user.

[0169] Output: Health and symptom data sent to the server.

[0170] Specific operation: The device sends the input data to the server using an HTTP POST request.

[0171] Step 3:

[0172] The server inputs the data on physical condition and symptoms received into a generative AI model for analysis.

[0173] Input: Health and symptom data received by the server.

[0174] Output: Analysis results (presence or absence of nutritional deficiency or abnormalities).

[0175] How it works: The server inputs data into a generative AI model, which then analyzes the data to identify any nutritional deficiencies or abnormalities.

[0176] Step 4:

[0177] The server recommends necessary nutrients to the user based on the analysis results.

[0178] Input: Analysis results of a generative AI model.

[0179] Output: A list of recommended nutrients.

[0180] Specific operation: Based on the analysis results, the server generates a message recommending appropriate nutrients (foods, supplements, dishes, etc.) to the user.

[0181] Step 5:

[0182] If the server detects an abnormality, it will send a notification.

[0183] Input: Analysis results of the generative AI model (presence or absence of anomalies).

[0184] Output: Informational message.

[0185] Specific behavior: If the server detects an abnormality, it executes an HTTP POST request to send a notification to the emergency contact or user.

[0186] Step 6:

[0187] The device receives recommended messages and notifications from the server and displays them to the user.

[0188] Input: Recommendation messages and notifications sent by the server.

[0189] Output: The suggested message or notification that will be displayed to the user.

[0190] Specific operation: The device receives the message from the server and displays it on the application interface.

[0191] By following the above steps, a system can be realized in which a user can simply input their own physical condition and symptoms, and if an abnormality is detected, a notification will be sent quickly and appropriate action can be taken.

[0192] Example 2

[0193] Next, a description will be given of Example 2 of Form 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."

[0194] In modern society, it is important to quickly and accurately identify and provide appropriate nutrients based on an individual's physical condition and symptoms. However, conventional systems require users to input their physical condition and symptoms and then identify appropriate nutrients based on that information, which is a cumbersome process. It is also difficult to collect accurate data from the vast amount of information available on the Internet. Furthermore, there is a lack of support for users to take specific actions based on the information they obtain. This limits the means by which users can consume appropriate nutrients.

[0195] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0196] In this invention, the server includes: a means for a user to input their physical condition and symptoms; a means for a terminal to send the input data to the server; a means for the server to receive the data and send a prompt to the generative AI model; a means for the server to receive a response from the generative AI model and refer to an online medical information or nutrition database; a means for the server to identify appropriate nutrients and send the results to the terminal; a means for the terminal to display the results to the user; and a means for the user to check the results and input additional questions or data as necessary. This enables the user to quickly and accurately identify appropriate nutrients based on their physical condition and symptoms and receive support for taking specific actions.

[0197] "Physical signs (symptoms)" refer to abnormalities or discomforts that a user feels regarding their physical condition or health.

[0198] "Generative AI" refers to an artificial intelligence model that generates appropriate responses and information based on input data.

[0199] "Nutrition deficiency" refers to an excess or deficiency of nutrients required based on the user's physical condition or symptoms.

[0200] "Necessary nutrients" refers to nutrients that are recommended for intake to improve the user's physical condition or symptoms.

[0201] "Food, supplements, dishes, etc." refers to ingredients, supplements, or prepared dishes that contain necessary nutrients.

[0202] "Recommendation methods" refer to methods of suggesting foods and supplements containing necessary nutrients to users.

[0203] "Direct purchase method" refers to the way in which users can purchase recommended foods and supplements directly, either online or in-store.

[0204] "Means for direct communication with medical institutions and doctors" refers to methods by which users can communicate directly with medical professionals as needed.

[0205] "Means for users to input their physical condition and symptoms" refers to an interface that allows users to input their own physical condition and symptoms into the system.

[0206] "Means for the terminal to transmit input data to the server" refers to a communication means for transmitting data input by the user to the server.

[0207] "Means by which the server receives data and sends prompts to the generative AI model" refers to the method by which the server receives data from the user and issues instructions to the generative AI model based on that data.

[0208] "Means for the server to receive the response from the generative AI model and refer to medical information and nutrition databases on the Internet" refers to a method for the server to receive the response from the generative AI model and search databases on the Internet to obtain more detailed information.

[0209] "Means for the server to identify appropriate nutrients and send the results to the terminal" refers to a method in which the server identifies nutrients appropriate for the user based on the information collected and sends the results to the user's terminal.

[0210] "Means by which the terminal displays the results to the user" refers to a method for visually displaying the results sent from the server to the user.

[0211] "Means for the user to review the results and enter additional questions or data as needed" refers to an interface that allows the user to review the displayed results and enter more detailed information or additional questions.

[0212] This invention is a system that identifies appropriate nutrients based on the user's physical condition and symptoms and provides them to the user. This system operates in cooperation with a server, a terminal, and the user.

[0213] Hardware and software used

[0214] server

[0215] The server performs the main processing, such as receiving data, using the generative AI model, referencing databases on the Internet, and sending results. The server uses the following software and hardware:

[0216] Generative AI models: Advanced natural language processing models such as GPT-4®

[0217] Database access tools: APIs for accessing online medical information and nutrition databases (e.g., PubMed, USDA Nutrient Database)

[0218] Communication protocol: A secure communication protocol such as HTTPS

[0219] Terminal

[0220] The terminal is a device that allows users to input their physical condition and symptoms and displays the results from the server. The terminal uses the following software and hardware:

[0221] Input interface: A form for users to enter their physical condition and symptoms

[0222] Display interface: A screen for displaying the results from the server.

[0223] Communication module: A module for sending and receiving data with the server

[0224] User

[0225] The user is the entity that inputs their own physical condition and symptoms and takes action based on the information provided by the system.

[0226] Data processing and calculation

[0227] 1. The user enters their physical condition and symptoms.

[0228] The user inputs their physical condition and symptoms into an input form on the device. For example, they might input "I have a headache."

[0229] 2. The device sends the input data to the server.

[0230] The terminal transmits the data entered by the user to the server. At this time, the data is encrypted before transmission.

[0231] 3. The server receives the data and sends prompts to the generative AI model.

[0232] The server receives the data sent from the device, creates a prompt for the generative AI model, and sends it. An example of a prompt might be, "The user is complaining of a headache. Please tell me about nutrients and measures related to headaches."

[0233] 4. The server receives the response from the generative AI model and references medical and nutritional information databases on the Internet.

[0234] The server receives the response from the generative AI model and consults online medical and nutritional databases for further information.

[0235] 5. The server identifies the appropriate nutrients and sends the results to the device.

[0236] The server identifies the nutrients that are suitable for the user based on the collected information and sends the results to the device. For example, it may determine that a person suffering from a headache may be deficient in magnesium or vitamin B2.

[0237] 6. The device displays the results to the user

[0238] The terminal receives the results sent from the server and displays them to the user, including the identified nutrients and how to take them.

[0239] 7. User reviews results and asks additional questions or enters data as needed

[0240] The user reviews the results displayed on the device and enters additional questions or data as needed, for example, "What foods are high in magnesium?"

[0241] Specific examples

[0242] Example 1: If you have a headache

[0243] 1. The user types "I have a headache" into the terminal.

[0244] 2. The device sends this information to the server.

[0245] 3. The server uses a generative AI model (e.g., GPT-4) to analyze the information "I have a headache."

[0246] 4. The server collects relevant information from medical information and nutrition databases on the Internet (e.g., PubMed, USDA Nutrient Database).

[0247] 5. The server determines that the headache may be related to a deficiency of magnesium or vitamin B2.

[0248] 6. The server sends this information back to the device.

[0249] 7. The terminal displays the analysis results to the user.

[0250] 8. The user selects foods and supplements containing magnesium and vitamin B2 based on the displayed information.

[0251] This system supports health management by identifying and providing appropriate nutrients to users based on their physical condition and symptoms.

[0252] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0253] Step 1:

[0254] The user inputs their physical condition and symptoms

[0255] The user inputs their physical condition and symptoms into an input form on the device. For example, they input "I have a headache." The input data is text information about the user's physical condition and symptoms. The device temporarily stores this input data.

[0256] Step 2:

[0257] The terminal sends the input data to the server.

[0258] The terminal sends the data entered by the user to the server. At this time, the data is encrypted before being sent. The input is text data about the user's physical condition and symptoms, and the output is the encrypted data sent to the server. The terminal notifies the user that the transmission is complete.

[0259] Step 3:

[0260] The server receives the data and sends prompts to the generative AI model.

[0261] The server receives the data sent from the device. Next, it creates a prompt for the generative AI model based on the received data and sends it. The input is encrypted data on physical condition and symptoms, and the output is the prompt text sent to the generative AI model. An example of a prompt text could be, "The user is complaining of a headache. Please tell me about nutrients and measures related to headaches."

[0262] Step 4:

[0263] The server receives the response from the generative AI model and references medical information and nutritional databases on the Internet.

[0264] The server receives the response from the generative AI model. The response includes nutrients and measures related to headaches. The server then references online medical information and nutrition databases to confirm and complement the response. The input is the response data from the generative AI model, and the output is the complemented medical information and nutrition data. The server collects information using a database access tool.

[0265] Step 5:

[0266] The server identifies the appropriate nutrients and sends the results to the device.

[0267] The server uses the collected information to identify the appropriate nutrients for the user's physical condition and symptoms. For example, if a person has a headache, it may determine that they may be deficient in magnesium or vitamin B2. The server then sends the results to the device. The input is supplemented medical information and nutritional data, and the output is information about the identified nutrients. The server encrypts the data when sending the results to the device.

[0268] Step 6:

[0269] The terminal displays the results to the user.

[0270] The terminal receives the results sent from the server and displays them to the user. The displayed content includes the identified nutrients and their intake methods. The input is the encrypted data sent from the server, and the output is the analysis results displayed to the user. The terminal displays the results in a visually easy-to-understand format.

[0271] Step 7:

[0272] The user reviews the results and enters additional questions or data as needed.

[0273] The user checks the results displayed on the terminal. If necessary, they can enter additional questions or data. For example, they can enter "What foods are high in magnesium?" The input is the user's additional question or data, and the output is the new input data stored on the terminal. The terminal prepares to send the additional input data to the server again.

[0274] (Application example 2)

[0275] Next, a description will be given of Application Example 2 of Form 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."

[0276] In modern society, it is important to consume appropriate nutrients based on individual physical condition and symptoms, but it is difficult for the average consumer to determine appropriate nutrients on their own and choose meals based on that. Furthermore, there are limited ways to easily obtain meals containing appropriate nutrients. Furthermore, there is a lack of ways to directly communicate with medical institutions or doctors based on physical condition and symptoms. A system that can solve these issues is needed.

[0277] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for identifying bodily signs (symptoms), a means for identifying nutritional deficiencies or excesses based on the bodily signs (symptoms) using generative AI, a means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the nutritional deficiencies or excesses, a means for proposing a meal menu containing the recommended nutrients, a means for ordering delivery of the proposed meal menu, and a means for directly communicating with a medical institution or doctor as needed. This allows the user to easily select and order delivery of meals containing appropriate nutrients based on their physical condition and symptoms. Furthermore, the ability to directly communicate with a medical institution or doctor as needed enables more appropriate health management.

[0278] "Physical signs (symptoms)" are things that indicate changes in physical condition or discomfort that the user feels.

[0279] "Generative AI" is an artificial intelligence technology that generates appropriate information based on input data.

[0280] "Nutrition deficiency" refers to an excess or deficiency of necessary nutrients, determined based on the user's physical condition and symptoms.

[0281] "Essential nutrients" are nutrients that are recommended for intake to improve the user's physical condition and symptoms.

[0282] A "meal menu" is a list of dishes or foods that contain a particular nutrient.

[0283] A "delivery order" is an ordering procedure for delivering a meal menu selected by the user to a specified location.

[0284] "Direct communication with medical institutions and doctors" means a means for users to communicate with medical professionals in real time.

[0285] The system for implementing this invention suggests appropriate nutrients based on the user's physical condition and symptoms, and enables delivery orders of meal menus containing those nutrients. Specific embodiments of this system are described below.

[0286] Hardware and software used

[0287] Hardware: Smartphone

[0288] Software: Python, transformers library, requests library

[0289] Processing flow

[0290] 1. Enter your physical condition and symptoms:

[0291] Users use a smartphone application to input their current physical condition and symptoms, and this input data is sent to a server.

[0292] 2. Nutrition Suggestions:

[0293] The server uses a generative AI model (e.g., GPT-3®) to suggest necessary nutrients based on the input symptoms, using prompts such as the following:

[0294] Example prompt: "If a user feels like they have a headache, what nutrients do they need?"

[0295] 3. Menu suggestions:

[0296] The server retrieves a meal menu with suggested nutrients from an external API (e.g., foodmenu.com) and displays it to the user.

[0297] 4. Delivery Order:

[0298] The user orders the selected menu through the delivery service's API (e.g., fooddelivery.com). The order data is sent from the server to the delivery service.

[0299] Specific examples

[0300] For example, if a user inputs "I have a headache," the server uses a generative AI model to determine that "I may be deficient in magnesium or vitamin B2." The server then retrieves meal menus containing these nutrients from an external API and suggests them to the user. By ordering delivery for the menu selected by the user, meals containing the appropriate nutrients are delivered to the user's specified location.

[0301] In this way, users can easily select meals containing the right nutrients based on their physical condition and symptoms, and order delivery. They can also directly communicate with medical institutions and doctors as needed, enabling more appropriate health management.

[0302] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0303] Step 1:

[0304] The user uses a smartphone application to input their current physical condition and symptoms. The input data is sent from the user's device to a server. The input data includes specific symptoms, such as "I have a headache."

[0305] Step 2:

[0306] The server uses a generative AI model (e.g., GPT-3) to suggest necessary nutrients based on the received data on physical condition and symptoms. The server inputs the following prompt sentence into the generative AI model:

[0307] Example prompt: "If a user feels like they have a headache, what nutrients do they need?"

[0308] The generative AI model outputs appropriate nutrients (e.g., magnesium or vitamin B2) based on the prompt.

[0309] Step 3:

[0310] Based on the nutrient information obtained from the generative AI model, the server calls an external API (e.g., foodmenu.com) to obtain meal menus containing the relevant nutrients. The server inputs a list of nutrients to the external API and receives a list of corresponding meal menus as output.

[0311] Step 4:

[0312] The server sends the obtained list of meal menus to the user terminal and displays it to the user, who then selects the meal they want from the displayed menu.

[0313] Step 5:

[0314] The information about the meal menu selected by the user is sent from the user's device to the server. The server calls the delivery service's API (e.g., fooddelivery.com) based on the information about the selected menu and places a delivery order. The server inputs the order data (e.g., menu ID, delivery address) into the delivery service's API and receives an order confirmation output.

[0315] Step 6:

[0316] The server sends a confirmation of the delivery order to the user's terminal and notifies the user that the order has been completed. The user receives the order confirmation and waits for the meal to be delivered to the specified location.

[0317] In this way, users can easily select meals containing the right nutrients based on their physical condition and symptoms, and order delivery.

[0318] Example 3

[0319] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0320] In modern society, it is important to consume appropriate nutrients according to individual health conditions and symptoms, but it is difficult for users to understand their own nutritional needs and select appropriate foods and supplements. Furthermore, there is a lack of easy ways to purchase recommended foods and supplements, or to directly communicate with medical institutions or doctors when necessary. Therefore, there is a need for a system that provides comprehensive support for users to improve their health.

[0321] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0322] In this invention, the server includes means for grasping bodily signs (symptoms), means for identifying nutritional deficiencies and excesses based on the bodily signs (symptoms) using generative AI, means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for inputting the bodily signs (symptoms), means for transmitting the input data to the server, means for analyzing the input data using the generative AI model, means for identifying necessary nutrients from the analysis results, means for recommending appropriate foods and supplements by referring to the database, means for generating links to purchase the recommended foods and supplements, and means for introducing the medical institution or doctor and arranging an online consultation. This allows users to support their intake of appropriate nutrients according to their health condition, easily purchase necessary foods and supplements, and even easily connect with medical institutions and doctors.

[0323] "Physical signs (symptoms)" refers to information about the user's health condition and physical condition, and specifically includes symptoms such as headache, fatigue, and loss of appetite.

[0324] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and identify necessary nutrients and recommended foods based on user input.

[0325] "Nutrition deficiency" refers to information indicating whether the user's current nutritional intake is deficient or excessive based on the user's health condition and symptoms.

[0326] "Essential nutrients" refer to specific nutritional components that are recommended for the user to consume in order to improve their health, and are provided in the form of foods, supplements, dishes, etc.

[0327] "Recommendation methods" refers to methods that suggest appropriate foods, supplements, and dishes to users based on the results of analysis by generative AI.

[0328] "Direct purchasing" refers to providing a link or interface that allows users to easily purchase the recommended foods or supplements online.

[0329] "Means for direct communication with medical institutions and doctors" refers to methods that allow users to consult or receive medical advice online from medical professionals as needed.

[0330] "Input means" refers to an interface that allows a user to input their health condition and symptoms into the system.

[0331] "Means for transmitting input data to a server" refers to a communication means for transmitting information input by a user to a server.

[0332] "Means for analyzing input data using a generative AI model" refers to a method in which a server uses a generative AI model to analyze a user's input data and identify necessary nutrients.

[0333] "Means for recommending appropriate foods and supplements by referring to a database" refers to a method in which the server refers to nutritional information stored in a database and suggests appropriate foods and supplements to the user.

[0334] "Means for generating a purchase link" refers to a method by which the server generates a link for purchasing the recommended food or supplement and provides it to the user.

[0335] "Means for introducing medical institutions and doctors and arranging online consultations" refers to a method in which the server introduces appropriate medical institutions and doctors based on the user's health condition and arranges online consultations.

[0336] This invention is a system that recommends appropriate nutrients based on a user's health condition and symptoms, and supports collaboration with medical institutions and doctors as needed. Specific embodiments of this system are described below.

[0337] System configuration

[0338] This system includes a terminal used by the user, a server that processes data, and a generative AI model. The terminal is a device such as a smartphone or PC, and the server is a computer system that analyzes data and makes recommendations. The generative AI model is built using Python libraries (e.g., TENSORFLOW (registered trademark) and PyTorch).

[0339] Program processing

[0340] User Input

[0341] The user enters their health condition and symptoms into an input form on the device. For example, they might enter "I have a headache." This input data is then sent from the device to the server.

[0342] Data analysis

[0343] The server inputs the received data into a generative AI model for analysis. The generative AI model identifies the necessary nutrients from the user's input data. For example, if the user says "I have a headache," it will determine that magnesium and vitamin B2 are necessary.

[0344] Nutrition Recommendations

[0345] Based on the analysis results, the server refers to a database and recommends appropriate foods and supplements, such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[0346] Generate purchase links

[0347] The server generates links to purchase the recommended foods and supplements, allowing users to easily purchase the recommended foods and supplements online. For example, recipes for dishes containing bananas, almonds, and liver are provided along with links to purchase those ingredients.

[0348] Cooperation with medical institutions and doctors

[0349] If necessary, the server will refer users to medical institutions or doctors and arrange online consultations, allowing them to speak directly with specialists if their condition does not improve or if certain symptoms persist.

[0350] Specific examples

[0351] Prompt Sentence Examples

[0352] For a user who inputs "I have a headache," the server performs the following processing:

[0353] 1. The user enters "I have a headache" into the input form on the terminal and clicks the "Submit" button.

[0354] 2. The terminal sends the input data to the server as an HTTP request.

[0355] 3. The server uses a generative AI model to analyze the input "I have a headache" and determine that magnesium and vitamin B2 are needed nutrients.

[0356] 4. The server consults a database and recommends foods like bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[0357] 5. The server generates and provides the user with a link to purchase the recommended food online.

[0358] 6. If necessary, the server will refer you to a medical institution or doctor and arrange an online consultation.

[0359] In this way, the system can support the user in taking appropriate nutrients according to their health condition, and facilitate the purchase of necessary foods and supplements, as well as cooperation with medical institutions and doctors. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0360] Step 1:

[0361] The user inputs their health condition and symptoms.

[0362] The user enters their health condition or symptoms, such as "I have a headache," into the input form on the device and clicks the "Submit" button. The input data is text information about the user's health condition or symptoms. The output is that the input data is saved on the device.

[0363] Step 2:

[0364] The terminal sends the input data to the server.

[0365] The device sends the data entered by the user to the server as an HTTP request. The input is the health condition or symptom data entered by the user. The output is the input data received by the server. Specifically, the device generates an HTTP request and sends a payload containing the input data to the server.

[0366] Step 3:

[0367] The server uses the generative AI model to analyze the input data.

[0368] The server inputs the received data into a generative AI model for analysis. The input is data about the user's health condition and symptoms. The output is information about necessary nutrients. Specifically, the server runs the AI ​​model using Python libraries (e.g., TensorFlow and PyTorch) to extract necessary nutrients from the input data.

[0369] Step 4:

[0370] Know the nutrients your server needs.

[0371] The server determines the nutrients the user needs from the analysis results of the generative AI model. The input is the analysis results of the generative AI model. The output is a list of necessary nutrients. Specifically, the server compares the analysis results with a database to identify necessary nutrients such as magnesium and vitamin B2.

[0372] Step 5:

[0373] The server refers to the database to recommend appropriate foods and supplements.

[0374] The server references a database and recommends foods and supplements rich in necessary nutrients. The input is a list of necessary nutrients. The output is a list of recommended foods and supplements. Specifically, the server executes SQL queries to obtain food information such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[0375] Step 6:

[0376] The server generates links to purchase the recommended foods and supplements.

[0377] The server generates links to purchase the recommended foods and supplements. The input is a list of recommended foods and supplements. The output is a purchase link. Specifically, the server calls the API of the e-commerce site and generates recipes and purchase links for dishes containing bananas, almonds, and liver.

[0378] Step 7:

[0379] The server will refer patients to medical institutions and doctors as needed and arrange online consultations.

[0380] If necessary, the server will refer the user to a medical institution or doctor and arrange an online consultation. The input is data about the user's health condition and symptoms. The output is referral information for the medical institution or doctor and a link to book an appointment. Specifically, the server uses the API of the medical institution's reservation system or video call service to generate the appointment and video call link.

[0381] (Application example 3)

[0382] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0383] In modern society, it is important to take in the right nutrients according to each individual's health condition. However, it is not easy for the average consumer to understand the nutrients they need based on their own physical condition and symptoms, and then select foods and supplements accordingly. Furthermore, if symptoms do not improve even after taking the right nutrients, they are required to promptly see a medical institution or doctor, but arranging this can be cumbersome. A system to solve these problems is needed.

[0384] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0385] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for providing a link for purchasing the recommended nutrients, and means for arranging an online consultation with a medical institution or doctor based on the bodily signs (symptoms).This allows users to easily grasp appropriate nutrients based on their symptoms and quickly purchase the necessary foods and supplements, as well as to quickly consult a medical institution or doctor if symptoms do not improve.

[0386] "Physical signs (symptoms)" are indicators of the user's physical condition or abnormalities, and include specific symptoms such as headaches and fatigue.

[0387] "Generative AI" is a system that uses artificial intelligence technology to analyze data and recommend necessary nutrients based on the user's symptoms.

[0388] "Nutrition deficiency" refers to nutrients that are lacking or being consumed in excess in the user's body.

[0389] "Essential nutrients (foods, supplements, dishes, etc.)" refers to foods, supplements, or dishes that are recommended for the user to consume in order to improve their health.

[0390] "Recommendation methods" are methods that use generative AI to suggest foods, supplements, and dishes that contain appropriate nutrients to users.

[0391] "Direct purchasing methods" are methods that allow users to purchase recommended foods and supplements directly online.

[0392] "Means for direct communication with medical institutions and doctors" refers to methods that allow users to communicate directly with medical institutions and doctors online as needed.

[0393] "Means for providing links to purchase" refers to a method of providing users with web links to purchase foods or supplements containing the recommended nutrients.

[0394] "Means for arranging online consultations" refers to the means for booking and arranging online consultations with medical institutions and doctors based on the user's symptoms.

[0395] The system for implementing this invention is configured as an application installed on a user's smartphone. The system identifies the user's physical signs (symptoms) and, based on those signs, uses generative AI to identify nutritional deficiencies and excesses. It also recommends foods, supplements, and recipes containing necessary nutrients and provides links for directly purchasing the recommended nutrients. It also has a function for directly communicating online with a medical institution or doctor, if necessary.

[0396] Hardware and Software Configuration

[0397] Hardware: Smartphone

[0398] Software: Python, API, generative AI models

[0399] Data processing and calculation

[0400] 1. Understanding physical signs (symptoms): The user inputs their symptoms into the application, for example, "I have a headache."

[0401] 2. Analysis by generative AI: The server sends the user's input data to a generative AI model, which analyzes the nutrient deficiencies and excesses. The generative AI model then recommends nutrients appropriate for the user's symptoms based on information obtained from the internet.

[0402] 3. Nutrient recommendation: Based on the analysis results, the server recommends foods, supplements, and dishes containing the necessary nutrients to the user. For example, if a person has a headache, it will recommend bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[0403] 4. Providing a purchase link: The server generates a link to purchase the recommended foods and supplements and provides it to the user. The user can complete the purchase procedure directly within the application.

[0404] 5. Online consultation with a medical institution or doctor: If necessary, the server will arrange an online consultation with a medical institution or doctor based on the user's symptoms. The user can talk to the doctor directly through the application.

[0405] Specific examples

[0406] For example, if a user complains of a headache, the app will use a generative AI model to analyze their nutritional needs and recommend foods like bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2. It will also provide links to purchase these foods and supplements, and if symptoms do not improve, it will arrange an online consultation with a doctor.

[0407] Prompt Sentence Examples

[0408] If a user complains of a "headache," design your application to recommend foods and supplements containing the necessary nutrients, provide links to purchase them, and, if symptoms persist, arrange an online consultation with a doctor.

[0409] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0410] Step 1:

[0411] The user starts the application and inputs their physical symptoms, for example, "I have a headache."

[0412] Input: User symptom data (e.g. headache)

[0413] Output: Symptom data is sent to the application.

[0414] Step 2:

[0415] The terminal transmits the input symptom data to the server.

[0416] Input: User symptom data

[0417] Output: Symptom data is sent to the server.

[0418] Step 3:

[0419] The server inputs the received symptom data into a generative AI model to analyze excess or deficiency of nutrients. The generative AI model performs analysis based on information obtained from the internet.

[0420] Input: Symptom data

[0421] Output: List of nutrients needed (e.g. magnesium, vitamin B2)

[0422] Step 4:

[0423] The server recommends appropriate foods, supplements, and dishes based on a list of necessary nutrients obtained from a generative AI model.

[0424] Input: List of nutrients needed

[0425] Output: A list of recommended foods, supplements, and dishes (e.g., bananas, almonds, liver)

[0426] Step 5:

[0427] The server generates a link to purchase the recommended foods and supplements and sends it to the device.

[0428] Input: A list of recommended foods, supplements, and recipes

[0429] Output: Purchase link (e.g. Banana purchase link)

[0430] Step 6:

[0431] The device displays the purchase link received from the server to the user, who can click the link to purchase the recommended food or supplement.

[0432] Enter: Purchase Link

[0433] Output: Purchase link shown to the user

[0434] Step 7:

[0435] If the user does not see any improvement in their symptoms, the terminal sends a request to the server to arrange an online consultation with a medical institution or doctor based on the user's request.

[0436] Input: User consultation request

[0437] Output: A consultation request is sent to the server

[0438] Step 8:

[0439] Based on the user's symptom data and consultation request, the server arranges an online consultation with an appropriate medical institution or doctor and sends that information to the terminal.

[0440] Input: Symptom data, consultation request

[0441] Output: Detailed information about the online consultation (e.g., consultation date and time, doctor information)

[0442] Step 9:

[0443] The terminal displays the detailed information of the online consultation received from the server to the user, and the user can receive the online consultation at the specified date and time.

[0444] Input: Online consultation details

[0445] Output: The consultation information displayed to the user

[0446] 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.

[0447] "Example 1"

[0448] A first embodiment of the present invention is a system that combines an emotion engine that recognizes a user's emotions. This system grasps not only the user's physical condition and symptoms, but also the user's emotions. Specifically, the system recognizes the user's emotions from the tone of voice that the user uses when speaking to the system and the phrasing of text input. For example, from the tone of voice of "I'm very tired today" or the text input of "I've been feeling down lately," the emotion engine recognizes that the user is tired or depressed.

[0449] "Example 2"

[0450] A second example is a system in which an emotion engine recommends appropriate nutrients based on the user's emotions. This system recommends nutrients that are believed to help improve the user's emotions, depending on the user's emotions. For example, if the system recognizes that the user is feeling stressed, it recommends foods and supplements containing nutrients that are believed to help relieve stress, such as B vitamins and magnesium.

[0451] "Example 3"

[0452] A third example is a system in which an emotion engine recommends appropriate medical institutions and doctors based on the user's emotions. If the user's emotions deteriorate beyond a certain range, for example, if the system recognizes that the user is showing symptoms of serious depression, it recommends specialized medical institutions and doctors. Specifically, it recommends psychosomatic medicine or psychiatric medical institutions, or doctors specializing in psychotherapy, and encourages the user to receive appropriate medical care.

[0453] The processing flow of each embodiment will be described below.

[0454] "Example 1"

[0455] Step 1: Collect the tone of voice and wording of the text input the user makes when speaking to the system.

[0456] Step 2: Input the collected data into the emotion engine.

[0457] Step 3: The emotion engine recognizes the user's emotion and outputs the result.

[0458] "Example 2"

[0459] Step 1: Recognize the user's emotions with the emotion engine.

[0460] Step 2: Based on the emotion you identify, search the database for nutrients that are known to help improve that emotion.

[0461] Step 3: Present the search results to the user as recommendations.

[0462] "Example 3"

[0463] Step 1: Recognize the user's emotions with the emotion engine.

[0464] Step 2: If the perceived emotion is deemed to have worsened beyond a certain level, a database is searched for specialized medical institutions and doctors.

[0465] Step 3: Present the search results to the user as recommendations, encouraging them to receive appropriate medical care.

[0466] Example 1

[0467] Next, a description will be given of Example 1 of Form 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."

[0468] Conventional health management systems are required to not only understand the user's physical condition and symptoms, but also to take into account emotional changes. However, current systems have difficulty accurately recognizing the user's emotions and providing appropriate advice based on them. Furthermore, they lack the means to analyze the information entered by the user and provide appropriate nutritional information or connect with medical institutions. This can lead to inadequate health management for the user and delay in appropriate responses.

[0469] 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.

[0470] In this invention, the server includes means for providing an interface for the user to input information about their physical condition and symptoms, means for analyzing the data input through the interface, means for recognizing the user's emotions based on the analyzed data, and means for displaying the analysis results to the user. This makes it possible to comprehensively grasp not only the user's physical condition and symptoms but also changes in their emotions, and to quickly provide appropriate advice and support.

[0471] "Physical signs (symptoms)" are specific symptoms or signs that indicate the user's physical condition or health state.

[0472] "Generative AI" is a system that uses artificial intelligence technology to analyze data and provide appropriate advice and information to users.

[0473] "Nutrition deficiency" refers to an excess or deficiency of necessary nutrients, determined based on the user's physical condition and symptoms.

[0474] "Essential nutrients" are foods, supplements, recipes, etc. that are recommended to improve the user's health.

[0475] An "interface" is a means by which a user inputs their physical condition and symptoms, and can take the form of a smartphone app or website.

[0476] "Means of analysis" refers to the technology or method for processing the data entered by the user and analyzing their physical condition, symptoms, emotions, etc.

[0477] "Means for recognizing emotions" refers to techniques and methods for analyzing and recognizing emotions from the tone of a user's voice and the wording of text input.

[0478] "Means for displaying the analysis results" refers to the methods and techniques for visually presenting the results of the analysis performed by the server to the user.

[0479] "Means for direct communication with medical institutions and doctors" refers to methods and technologies that allow users to communicate directly with medical professionals as needed.

[0480] MODE FOR CARRYING OUT THE INVENTION

[0481] The present invention is a system that allows a user to input their own physical condition and symptoms and provides appropriate advice and responses based on the input. A specific embodiment of this system will be described below.

[0482] 1. Program Generation

[0483] The program for this system provides an interface for users to input their physical condition and symptoms. The interface can be implemented as a smartphone, PC application, or website. Users input their physical condition and symptoms through the interface using text or voice.

[0484] 2. Program processing explanation

[0485] When the user enters their physical condition and symptoms through the interface, the device sends the entered data to the server. The data is encrypted and sent securely. The server analyzes the received data. For text data, natural language processing (NLP) technology is used. Specifically, Google (registered trademark) Cloud Natural Language API and IBM Watson (registered trademark) Natural Language Understanding are used. For example, the symptom "headache" is extracted from the text "I have a headache."

[0486] The server then analyzes the voice data to recognize the user's emotions. Using the Microsoft® Azure® Emotion API and Affectiva's SDK, the server analyzes emotions from the tone and phrasing of the voice. For example, if the user says, "I'm very tired today," the server recognizes that the user is tired.

[0487] The server compiles these analysis results and sends them back to the device. The device then displays the received analysis results to the user. For example, it might say, "Headache detected. We recommend you take a rest." Or, it might say, "Fatigue detected. We recommend you take a sufficient rest."

[0488] 3. Examples of concrete examples and prompts

[0489] As a concrete example, consider the case where a user is using a smartphone app. The user opens the app, types in the text "I have a headache," and then types in the voice "I feel very tired today." The app sends this information to a server. The server analyzes the text using the Google Cloud Natural Language API and extracts the symptom "headache." It also analyzes the tone of the voice using the Microsoft Azure Emotion API and recognizes that the user is tired. The server compiles these analysis results and sends them back to the device. The device then displays the analysis results to the user, saying "Headache has been detected. It is recommended that you take a rest." It also displays "Fatigue has been detected. It is recommended that you take sufficient rest."

[0490] Example prompts to input to the generative AI model:

[0491] If a user types "I have a headache" and then speaks "I feel very tired today," how would the system parse this and what results would it return?

[0492] In this way, the system comprehensively grasps the user's physical condition and emotions and provides appropriate responses and advice.

[0493] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0494] Step 1:

[0495] The user inputs their physical condition and symptoms through the interface.

[0496] Specifically, the user opens the interface of a smartphone app or website, enters "I have a headache" as text, and then voice-inputs "I'm very tired today."

[0497] Input: Text and voice data of the user's condition and symptoms.

[0498] Output: The input text and audio data.

[0499] Step 2:

[0500] The terminal transmits the input data to the server.

[0501] Specifically, the terminal encrypts the text and voice data entered by the user and transmits them securely to the server.

[0502] Input: Text and voice data entered by the user.

[0503] Output: Encrypted text and audio data sent to the server.

[0504] Step 3:

[0505] The server receives the data and analyzes it using natural language processing (NLP) techniques.

[0506] Specifically, the server uses Google Cloud Natural Language API and IBM Watson Natural Language Understanding to analyze text data and extract the symptom "headache" from the text "I have a headache."

[0507] Input: The encrypted text data sent to the server.

[0508] Output: Parsed symptom data (e.g., "headache").

[0509] Step 4:

[0510] The server uses an emotion engine to recognize the user's emotion.

[0511] Specifically, the server uses the Microsoft Azure Emotion API and Affectiva's SDK to analyze voice data and recognize that the user is tired from the voice saying, "I'm very tired today."

[0512] Input: Encrypted audio data sent to the server.

[0513] Output: Parsed emotion data (e.g. "fatigue").

[0514] Step 5:

[0515] The server compiles the analysis results and sends them back to the device.

[0516] Specifically, the server integrates the analyzed symptom data and emotion data to generate appropriate advice for the user, such as a message like "Headache detected. We recommend you take a rest."

[0517] Input: Parsed symptom data and emotion data.

[0518] Output: Consolidated analysis results and advice messages.

[0519] Step 6:

[0520] The terminal displays the analysis results to the user.

[0521] Specifically, the device visually displays the analysis results received from the server to the user, for example, displaying a message such as "Headache detected. We recommend you take a rest."

[0522] Input: Analysis results and advice messages received from the server.

[0523] Output: Analysis results and advice messages displayed to the user.

[0524] (Application example 1)

[0525] Next, a description will be given of Application Example 1 of Embodiment 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."

[0526] While conventional health management systems can grasp a user's physical condition and symptoms, they are unable to take into account the user's emotional state. This makes it difficult to properly monitor the user's mental health and take necessary measures. Furthermore, they lack the functionality to issue appropriate warnings when the user's emotions worsen, which can delay early response.

[0527] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, recipes, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for grasping the user's emotions using an emotion engine that recognizes the user's emotions, and means for issuing an alert when the user's emotions fall below a certain threshold. This makes it possible to comprehensively monitor not only the user's physical condition but also their emotional state, and to respond quickly if an abnormality is detected.

[0528] "Physical signs (symptoms)" are information that indicates the user's physical condition or abnormalities, such as specific symptoms such as headaches or fatigue.

[0529] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and evaluate a user's physical condition and nutritional status.

[0530] "Nutrition deficiency" refers to a state in which necessary nutrients are lacking or being consumed in excess, as determined based on the user's physical condition and symptoms.

[0531] "Essential nutrients" refers to the nutritional components of foods, supplements, dishes, etc. that are necessary to maintain the user's health.

[0532] An "emotion engine" is a technology for analyzing a user's emotional state, and refers to a system that recognizes emotions from the tone of voice and the wording of text.

[0533] The "threshold" is a reference value for evaluating the user's emotional state, and anything below this value is deemed abnormal.

[0534] "Means for issuing warnings" refers to a function that alerts the user or relevant parties when an abnormality is detected in the user's physical condition or emotional state.

[0535] "Direct communication with medical institutions and doctors" refers to the ability for users to communicate with medical professionals in real time as needed.

[0536] As an embodiment of the present invention, a system is provided that comprehensively monitors the physical condition and emotions of a user and takes necessary measures. A specific embodiment of this system will be described below.

[0537] System Configuration

[0538] The system consists of a device (smartphone or PC) equipped with an interface for understanding the user's physical condition and emotions, and a server for analyzing the data. The device includes a microphone for voice input and a keyboard for text input. The server analyzes the data using a generative AI model and an emotion engine.

[0539] Hardware and software used

[0540] Hardware: Smartphone, PC, microphone

[0541] Software: Python, SpeechRecognition library, TextBlob library, requests library

[0542] Data processing and calculation

[0543] 1. Enter your physical condition and symptoms:

[0544] Users input their physical condition and symptoms through the device's interface, either by text or voice input.

[0545] 2. Speech Recognition:

[0546] For voice input, the device uses the SpeechRecognition library to convert speech to text, which sends the user's voice data to the server as text data.

[0547] 3. Emotion analysis:

[0548] The server analyzes the sentiment of the text data using the TextBlob library. As a result, a sentiment score is generated. If this score falls below a certain threshold, the user's sentiment is considered to be negative.

[0549] 4. Issuance of a warning:

[0550] If the emotion score falls below a threshold, the server uses the requests library to issue a warning, which is then sent to the user's device.

[0551] Specific examples

[0552] For example, if a user types "I've been feeling depressed lately," the server analyzes this text data and calculates an emotion score. If the emotion score is low, the system notifies the user with "Warning: It seems you are feeling depressed."

[0553] Prompt Sentence Examples

[0554] An example of a prompt to input to a generative AI model is as follows:

[0555] If a user types "I've been feeling depressed lately," write a Python program that analyzes the sentiment score and issues a warning if the score is low.

[0556] In this way, it is possible to monitor the user's physical condition and emotions in real time and respond quickly if an abnormality is detected.

[0557] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0558] Step 1:

[0559] The user inputs their physical condition and symptoms. The input method is either text input or voice input. The input data is sent to the server through the device interface. Specifically, the user inputs information such as "I have a headache" or "I've been feeling depressed lately."

[0560] Input: Text or voice data of the user's physical condition and symptoms

[0561] Output: Text data from the terminal to the server

[0562] Step 2:

[0563] In the case of voice input, the device converts the voice to text using the SpeechRecognition library. This process sends the user's voice data to the server as text data. Specifically, the voice data collected by the microphone is converted to text using Google's speech recognition API.

[0564] Input: User's voice data

[0565] Output: Text data

[0566] Step 3:

[0567] The server uses the TextBlob library to analyze the received text data. The TextBlob library analyzes the sentiment of the text data and generates a sentiment score. Specifically, the text data is input into a sentiment analysis model to calculate a positive or negative sentiment score.

[0568] Input: Text data

[0569] Output: Sentiment score

[0570] Step 4:

[0571] The server evaluates the generated emotion scores and issues a warning if the score falls below a certain threshold. Specifically, if the emotion score is -0.5 or less, a warning message is sent to the user's device using the requests library.

[0572] Input: Sentiment score

[0573] Output: Warning message

[0574] Step 5:

[0575] The user's device receives the warning message sent from the server and notifies the user. Specifically, the notification function of the smartphone is used to display the message "Warning: Your emotions seem to be depressed."

[0576] Input: warning message

[0577] Output: User notification

[0578] In this way, it is possible to monitor the user's physical condition and emotions in real time and respond quickly if an abnormality is detected.

[0579] Example 2

[0580] Next, a description will be given of Example 2 of Form 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."

[0581] In modern society, it is important to consume appropriate nutrients based on individual physical condition and emotions, but it is difficult for users to understand and appropriately consume nutrients that are appropriate for their own physical condition and emotions. Furthermore, there is a lack of ways for users to quickly and accurately obtain information to select appropriate nutrients based on their physical condition and emotions. Furthermore, there is a need for a way for users to easily purchase recommended nutrients and, if necessary, to directly communicate with a medical institution or doctor.

[0582] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0583] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies or excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the nutritional deficiencies or excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for utilizing generative AI to recommend nutrients that will help improve the user's emotions based on the user's emotions, and means for displaying recommended nutrient information based on the emotions to the user. This enables the user to quickly and accurately grasp appropriate nutrients based on their physical condition and emotions and take them appropriately.

[0584] "Physical signs (symptoms)" is information that a user inputs to indicate their physical condition or health status.

[0585] "Generative AI" is an artificial intelligence technology that refers to medical information and nutrition databases on the Internet and identifies appropriate nutrients based on the user's physical condition and emotions.

[0586] "Excess or deficiency of nutrition" refers to a state in which the current amount of nutritional intake is inappropriate based on the user's physical condition or emotions.

[0587] "Necessary nutrients (foods, supplements, dishes, etc.)" refers to foods, supplements, dishes, etc. that contain the nutrients necessary to maintain or improve health, and are recommended based on the user's physical condition and emotions.

[0588] "Recommendation methods" are methods that suggest to users the necessary nutrients identified by the generative AI.

[0589] "Direct purchase methods" are methods that allow users to directly purchase foods or supplements containing the recommended nutrients, either online or offline.

[0590] "Means for directly communicating with medical institutions and doctors" refers to a method by which a user can directly communicate with medical institutions and doctors as needed.

[0591] "Means of utilizing generative AI based on emotions" refers to a method in which a generative AI uses a user's emotional state as input data to identify the appropriate nutrients to improve that emotion.

[0592] The "means of displaying emotion-based nutrient recommendation information to the user" is a method of visually providing the user with information on nutrients that are useful for improving emotions, as identified by the generative AI.

[0593] MODE FOR CARRYING OUT THE INVENTION

[0594] The present invention is a system for recommending appropriate nutrients based on a user's physical condition and emotions. Specific embodiments of this system will be described below.

[0595] System configuration

[0596] This system consists of three main components: a server, a device, and a user. The server analyzes data using a generative AI model to identify appropriate nutrients. The device receives input from the user and communicates with the server. The user inputs their physical condition and emotions and receives information on recommended nutrients.

[0597] Hardware and software used

[0598] Server: Use a server machine equipped with a high-performance processor and large memory capacity. Use a machine learning framework such as TensorFlow or PyTorch to run the generative AI model.

[0599] Terminal: User devices such as smartphones, tablets, and PCs are used to access the system through dedicated applications or web browsers.

[0600] Databases: Consult online medical and nutrition databases (e.g., PubMed, USDA Nutrient Database).

[0601] Program processing

[0602] The server receives data on physical condition and emotions input by the user. This data is provided by the user through an input form on the device. The server uses the generative AI model based on the received data to search online medical information and nutrition databases. For example, if the user inputs "I have a headache," the server uses the generative AI model to determine that the user may be deficient in magnesium or vitamin B2.

[0603] The server generates nutritional recommendations for the user based on the analysis results obtained using the generative AI model. For example, it generates specific advice such as, "We recommend that you take foods and supplements containing magnesium and vitamin B2." The generated recommendations are sent from the server to the device and displayed to the user.

[0604] Specific examples

[0605] The user types "I have a headache" into the device. The device sends that data to a server, which uses a generative AI model to search online medical and nutrition databases and determine that the patient may be deficient in magnesium or vitamin B2. The information is then sent back to the device and displayed to the user.

[0606] Example prompt sentence:

[0607] If a user types in "I have a headache," use a generative AI model to determine which nutrients they may be deficient in.

[0608] Or, if a user types "I'm feeling stressed" into their device, the device sends that data to a server, which uses a generative AI model to determine that B vitamins and magnesium can help relieve stress. That information is sent back to the device and displayed to the user.

[0609] Example prompt sentence:

[0610] If a user types in "I'm feeling stressed," use a generative AI model to determine which nutrients would help relieve stress.

[0611] In this way, the server, terminal, and user work together to create a system that recommends appropriate nutrients based on the user's physical condition and emotions.

[0612] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0613] Program processing flow

[0614] Step 1: User Input

[0615] The user inputs their physical condition and emotions into an input form on the device. For example, the user inputs "I have a headache." This input data is sent to the server through the device interface.

[0616] Input: Physical condition or emotional data entered by the user into an input form (e.g., "I have a headache").

[0617] Output: The input data is sent to the server.

[0618] Step 2: Sending data

[0619] The terminal transmits the data on physical condition and emotions input by the user to the server, which receives the transmitted data and proceeds to the next processing step.

[0620] Input: Physical and emotional data entered by the user.

[0621] Output: The data received by the server.

[0622] Step 3: Analyze the data

[0623] The server analyzes the received data. This analysis is performed using a generative AI model. The generative AI model refers to online medical information and nutrition databases to identify the appropriate nutrients for the user's physical condition and emotions. For example, if the user says "I have a headache," the model might determine that the user is likely deficient in magnesium or vitamin B2.

[0624] Input: User's physical condition and emotional state data received by the server.

[0625] Output: Analysis results from the generative AI model (e.g., possible deficiency of magnesium or vitamin B2).

[0626] Step 4: Generate recommendations

[0627] The server generates nutritional recommendations for the user based on the analysis results obtained using the generative AI model. For example, it generates specific advice such as, "We recommend that you take foods and supplements containing magnesium and vitamin B2."

[0628] Input: Analysis results from a generative AI model.

[0629] Output: Nutrition recommendations for the user.

[0630] Step 5: Submit your recommendations

[0631] The server transmits the generated recommendation information to the terminal, which receives the information and displays it to the user.

[0632] Input: Nutrition recommendations for the user.

[0633] Output: The recommendations received by the device.

[0634] Step 6: View recommendations

[0635] The device displays the recommended information received from the server to the user. The user can select appropriate foods and supplements based on the displayed information. For example, the device may display a message saying, "We recommend that you take foods and supplements containing magnesium and vitamin B2."

[0636] Input: Recommendations received by the device.

[0637] Output: The recommendation displayed to the user.

[0638] Specific actions

[0639] Step 1: User Input

[0640] The user accesses a dedicated application or website using a device such as a smartphone or PC, enters "I have a headache" into the input form, and clicks the submit button.

[0641] Step 2: Sending data

[0642] The terminal sends the data entered by the user, such as "I have a headache," to the server using the HTTPS protocol. The sent data is received by the server.

[0643] Step 3: Analyze the data

[0644] The server then calls a generative AI model to analyze the received data. The generative AI model consults online medical information and nutrition databases (e.g., PubMed and the USDA Nutrient Database) and determines that the symptom "headache" may be due to a deficiency of magnesium or vitamin B2.

[0645] Step 4: Generate recommendations

[0646] The server generates specific nutritional recommendations for the user based on the analysis results obtained from the generative AI model, such as "We recommend taking foods and supplements containing magnesium and vitamin B2."

[0647] Step 5: Submit your recommendations

[0648] The server transmits the generated recommendation information to the terminal, which receives the information.

[0649] Step 6: View recommendations

[0650] The device displays the recommended information received from the server to the user. The user can select appropriate foods and supplements based on the displayed information. For example, the device may display a message saying, "We recommend that you take foods and supplements containing magnesium and vitamin B2."

[0651] (Application example 2)

[0652] Next, a description will be given of Application Example 2 of Form 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."

[0653] In modern society, it is difficult to understand the appropriate nutrients based on individual physical condition and symptoms and to select foods and supplements based on that. It is also difficult to find a place where you can quickly purchase products containing the recommended nutrients. Furthermore, there is a lack of means to directly communicate with medical institutions or doctors when necessary, making comprehensive health management difficult.

[0654] 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.

[0655] In this invention, the server includes a means for identifying bodily signs (symptoms), a means for identifying nutritional deficiencies or excesses based on the bodily signs (symptoms) using generative AI, a means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies or excesses, a means for directly purchasing the recommended nutrients, a means for directly communicating with a medical institution or doctor as needed, and a means for guiding users to stores selling products containing the recommended nutrients. This allows users to identify appropriate nutrients based on their physical condition and symptoms and quickly find places where they can purchase them. Furthermore, the ability to directly communicate with a medical institution or doctor as needed facilitates comprehensive health management.

[0656] "Physical signs (symptoms)" are specific symptoms or sensations that indicate the user's physical condition or health status.

[0657] "Generative AI" is an artificial intelligence that obtains information from medical and nutritional databases on the Internet and recommends appropriate nutrients based on the user's physical condition and symptoms.

[0658] "Nutrient deficiency" refers to nutrients that are lacking or in excess in the body, as determined based on the user's physical condition and symptoms.

[0659] "Essential nutrients (foods, supplements, meals, etc.)" refers to foods, supplements, or meals containing nutrients necessary for maintaining or improving health that are recommended based on the user's physical condition and symptoms.

[0660] "Direct purchasing of nutrient recommendations" means a method that enables a user to quickly purchase a product containing the nutrient recommendations.

[0661] "Means for communicating directly with medical institutions and doctors" refers to means by which users can communicate directly with medical institutions and doctors as needed.

[0662] "Store navigation" means a means that enables a user to find stores that sell products containing the nutrient recommendations.

[0663] The system for implementing this invention recommends appropriate nutrients based on the user's physical condition and symptoms, and supports purchasing in physical stores. Specific embodiments of the system are described below.

[0664] System configuration

[0665] The system consists of the following main components:

[0666] 1. User device: A device such as a smartphone or tablet that provides an interface for users to input their physical condition and symptoms.

[0667] 2. Generative AI model: Obtains information from online medical and nutrition databases and recommends appropriate nutrients based on the user's physical condition and symptoms.

[0668] 3. Database: Stores information about stores that sell products containing the recommended nutrients.

[0669] 4. Communication module: Handles data communication between the user device, the generative AI model, and the database.

[0670] Program processing

[0671] Hardware and Software

[0672] Hardware: smartphones, tablets, servers

[0673] Software: Python, OpenAI® API, database management system (e.g., MySQL®)

[0674] Data processing and calculation

[0675] 1. User device: The user inputs their physical condition and symptoms. For example, they input "I have a headache."

[0676] 2. Generative AI model: Receives user input, generates a prompt, and sends it to the OpenAI API. An example of a prompt is as follows:

[0677] "If a user has a headache, what are the appropriate nutrients?"

[0678] 3. Generative AI model: receives the response from the OpenAI API and identifies the appropriate nutrients, for example, determining that "you may be deficient in magnesium or vitamin B2."

[0679] 4. Database: Search for stores that sell products containing the recommended nutrients. For example, provide information such as "Products containing magnesium can be purchased at Drugstore A."

[0680] 5. User device: Display recommended nutrients and store information to the user.

[0681] Specific examples

[0682] If a user types in "I have a headache," the generative AI model will determine that "you may be deficient in magnesium or vitamin B2," and will then direct them to stores that sell products containing these nutrients. For example, it will display "Products containing magnesium can be purchased at Drugstore A."

[0683] In this way, users can identify the right nutrients based on their physical condition and symptoms, quickly find where to buy them, and, if necessary, communicate directly with a medical institution or doctor, making overall health management easier.

[0684] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0685] Step 1:

[0686] The user inputs their physical condition and symptoms on the user device. For example, they input "I have a headache."

[0687] Input: Text input of user's condition and symptoms

[0688] Output: Input data on physical condition and symptoms

[0689] Specific operation: On the smartphone application screen, the user enters symptoms in the text box and presses the send button.

[0690] Step 2:

[0691] The server receives the entered data on physical condition and symptoms, generates a prompt sentence, and sends it to the generative AI model.

[0692] Input: User's physical condition and symptoms data

[0693] Output: Prompt to send to the generative AI model

[0694] Specific behavior: The server generates a prompt sentence, "If the user has a headache, what are the appropriate nutrients?" and sends it to the OpenAI API.

[0695] Step 3:

[0696] The generative AI model identifies the appropriate nutrients based on the prompt and returns a response to the server.

[0697] Input: prompt statement

[0698] Output: Pertinent nutrition information

[0699] What it does: The OpenAI API parses the prompt, generates a response saying "You may be deficient in magnesium or vitamin B2," and returns it to the server.

[0700] Step 4:

[0701] The server receives the response from the generative AI model and searches its database for stores that sell products containing the recommended nutrients.

[0702] Input: Appropriate nutrition information

[0703] Output: Information about stores that sell products containing the recommended nutrients

[0704] Specific operation: The server retrieves information from the database that "products containing magnesium can be purchased at drugstore A."

[0705] Step 5:

[0706] The server sends the recommended nutrients and information on where they can be purchased to the user's device.

[0707] Input: Store information that sells products containing the recommended nutrients

[0708] Output: Information to display on the user's terminal

[0709] Specific operation: The server sends information to the user's terminal that "products containing magnesium can be purchased at Drugstore A."

[0710] Step 6:

[0711] The user's device displays recommended nutrients and information on where they can be purchased.

[0712] Input: Information sent from the server

[0713] Output: Information displayed to the user

[0714] Specific operation: The smartphone application screen displays the information, "Products containing magnesium can be purchased at Drugstore A."

[0715] Example 3

[0716] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0717] In modern society, it is important to consume appropriate nutrients according to individual health conditions and symptoms. However, it is difficult for ordinary people to accurately understand their nutritional needs and select appropriate foods and supplements. Furthermore, there are limited ways to quickly access medical institutions and doctors if their health does not improve. This can lead to inadequate health management, which can worsen or chronicate symptoms. Furthermore, purchasing foods and supplements online is complicated, resulting in poor user convenience.

[0718] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0719] In this invention, the server includes a means for identifying bodily signs (symptoms), a means for identifying nutritional deficiencies and excesses based on the bodily signs (symptoms) using generative AI, a means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, a means for directly purchasing the recommended nutrients, a means for directly communicating with a medical institution or doctor if necessary, a means for analyzing data based on the bodily signs (symptoms) using natural language processing technology, a means for providing links to purchase foods and supplements containing the recommended nutrients, and a means for introducing a medical institution or doctor and arranging an online consultation if the bodily signs (symptoms) do not improve. This allows users to easily identify the appropriate nutrients for their health condition and quickly purchase the necessary foods and supplements. Furthermore, if their health condition does not improve, they can quickly access a medical institution or doctor and receive appropriate medical care.

[0720] "Physical signs (symptoms)" refer to physical abnormalities or discomforts experienced by the user, and specifically include symptoms such as headaches, fatigue, and stomach aches.

[0721] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and generate information for specific purposes.

[0722] "Nutrient deficiency or oversupply" refers to an excess or deficiency of a nutrient required based on the user's health condition or symptoms.

[0723] "Necessary nutrients (foods, supplements, meals, etc.)" refers to foods, supplements, or meals containing nutrients recommended based on the user's health condition and symptoms.

[0724] "Direct means to purchase nutrient recommendations" refers to a feature that provides a link or interface for users to purchase recommended foods or supplements directly online.

[0725] "Means for communicating directly with medical institutions and doctors" refers to a function that allows users to communicate directly with medical institutions and doctors online as needed.

[0726] "Natural language processing technology" refers to technology that enables computers to understand and analyze human language, and specifically includes text analysis and keyword extraction.

[0727] "Purchase Link" refers to a URL or button that allows users to purchase the recommended food or supplement online.

[0728] "Means for arranging online consultations" refers to the function that allows a user to book and arrange an online consultation with an appropriate medical institution or doctor if their condition does not improve.

[0729] The present invention is a system that recommends necessary nutrients based on the user's health condition and symptoms, and also provides a function to purchase foods and supplements containing those nutrients online. It also provides a function to directly communicate with medical institutions and doctors as needed.

[0730] System configuration

[0731] This system consists of the following main components:

[0732] 1. User device: A device such as a smartphone or computer that allows users to input their health status and symptoms.

[0733] 2. Server: Receives input data from the user, analyzes it, identifies necessary nutrients, and recommends foods and supplements.

[0734] 3. Generative AI model: Artificial intelligence technology that analyzes user input data and identifies necessary nutrients.

[0735] 4. Natural language processing technology: Technology for analyzing user input data. Specifically, it uses the Python NLTK library, etc.

[0736] 5. Database: A database for storing food and nutrient information.

[0737] 6. Online Purchase Links: Links to purchase the recommended foods and supplements online.

[0738] 7. Medical institution referral function: If your condition does not improve, this function will refer you to an appropriate medical institution or doctor and arrange an online consultation.

[0739] System Operation

[0740] User terminal

[0741] Users use their smartphones or computers to input their health conditions and symptoms. For example, they might input "I have a headache." The input data is then sent from the device to the server.

[0742] server

[0743] The server analyzes the data received from the user using natural language processing technology. Specifically, it uses Python's NLTK library to analyze the text and extract relevant keywords. For example, it extracts the keyword "headache" from the input "I have a headache."

[0744] The server then uses a generative AI model to identify necessary nutrients based on the extracted keywords—for example, magnesium and vitamin B2, which are associated with headaches—by referencing a pre-built nutrient database.

[0745] The server then selects appropriate foods and supplements based on the identified nutrients, such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2, using a food database.

[0746] Generate and send a recommendation list

[0747] The server generates a list of selected foods and supplements and sends it to the user's device, including the food's name, nutrient content, and a link to purchase it.

[0748] User operations

[0749] The user checks the recommendation list on the device and sees that bananas, almonds, and liver are recommended. The user clicks on the provided purchase link to purchase food or supplements online. For example, the user is redirected to a purchase page on an e-commerce site and purchases bananas and almonds.

[0750] Medical institution introduction function

[0751] If the user's condition does not improve, the device application can use a function to refer them to a medical institution or doctor. For example, they can be referred to a psychosomatic or psychiatric medical institution and arrange an online consultation.

[0752] Examples of concrete examples and prompts

[0753] Specific examples

[0754] 1. The user types, "I have a headache."

[0755] 2. The server recommends foods high in magnesium and vitamin B2.

[0756] 3. The server recommends bananas, almonds, and liver and provides recipes for dishes that include them and links to purchase them online.

[0757] 4. The user uses the provided link to purchase the recommended food.

[0758] 5. If the user's condition does not improve, the server will refer them to a psychosomatic or psychiatric medical institution and arrange for an online consultation.

[0759] Prompt Sentence Examples

[0760] "What foods and supplements do you recommend for headaches? Also, provide links to buy them online."

[0761] "If my condition does not improve, please introduce me to an appropriate medical institution or doctor." The flow of the identification process in the third embodiment will be described with reference to FIG.

[0762] Step 1:

[0763] Users input their health status and symptoms

[0764] The user opens the application on their smartphone or computer and inputs their health condition and symptoms. For example, they might input "I have a headache." The input data is in text format, and is sent from the device to the server by pressing the send button.

[0765] Input: User's health condition or symptoms (e.g., "I have a headache")

[0766] Output: The input data is sent to the server

[0767] Step 2:

[0768] The device sends the input data to the server

[0769] The terminal encrypts the data entered by the user and sends it to the server using the HTTPS protocol, ensuring the security of the data.

[0770] Input: User-entered health and symptom data

[0771] Output: The encrypted data is sent to the server

[0772] Step 3:

[0773] The server parses the input data

[0774] The server analyzes the received data using natural language processing technology. Specifically, it uses Python's NLTK library to analyze the text and extract relevant keywords. For example, it extracts the keyword "headache" from the input "I have a headache."

[0775] Input: Encrypted user health and symptom data

[0776] Output: Parsed keywords (e.g. "headache")

[0777] Step 4:

[0778] Identify the nutrients your server needs

[0779] The server identifies the necessary nutrients based on the analysis results. For example, it identifies magnesium and vitamin B2 as nutrients related to headaches. This process refers to a pre-built nutrient database.

[0780] Input: Parsed keyword (e.g. "headache")

[0781] Output: Identified required nutrients (e.g., magnesium, vitamin B2)

[0782] Step 5:

[0783] Select foods and supplements recommended by the server

[0784] The server then selects appropriate foods and supplements based on the identified nutrients, such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2, using a food database.

[0785] Input: Identified nutrient needs (e.g., magnesium, vitamin B2)

[0786] Output: A list of recommended foods and supplements (e.g. bananas, almonds, liver)

[0787] Step 6:

[0788] The server sends the recommendation list to the device.

[0789] The server generates a list of selected foods and supplements and sends it to the device, including the name of the food, its nutrient content, and a link to purchase it.

[0790] Input: A list of recommended foods and supplements

[0791] Output: The recommendation list is sent to the terminal.

[0792] Step 7:

[0793] The user reviews the recommendations list

[0794] The user checks the recommendation list on the device, and sees that, for example, bananas, almonds, and liver are recommended.

[0795] Input: Recommendation list

[0796] Output: User reviews the recommendation list

[0797] Step 8:

[0798] A user purchases food and supplements online.

[0799] The user clicks on a purchase link included in the recommendation list to purchase food or supplements online. For example, they are taken to a purchase page on an e-commerce site to purchase bananas or almonds.

[0800] Input: Recommended List Purchase Link

[0801] Output: The user purchases food and supplements.

[0802] Step 9:

[0803] If the user's condition does not improve, the function to refer them to a medical institution or doctor can be used.

[0804] If the user's condition does not improve, the device application can use a function to refer them to a medical institution or doctor. For example, they can be referred to a psychosomatic or psychiatric medical institution and arrange an online consultation.

[0805] Input: User's health information

[0806] Output: Referrals to medical institutions and doctors, and arrangements for online consultations

[0807] (Application example 3)

[0808] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0809] In modern society, it is important to take in appropriate nutrients based on individual physical condition and emotions, but it is difficult for users to select appropriate foods and supplements based on their own symptoms and emotions. Furthermore, there is a lack of means to directly communicate with medical institutions or doctors when necessary, making it difficult to receive prompt and appropriate medical support. Furthermore, there is a lack of easy means to purchase recommended nutrients, which reduces user convenience.

[0810] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0811] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with medical institutions or doctors as needed, means for utilizing an emotion engine to recommend appropriate medical institutions or doctors based on the bodily signs (symptoms), and means for generating links to purchase the recommended nutrients. This allows users to easily consume appropriate nutrients based on their symptoms and emotions, as well as receive prompt and appropriate medical support as needed.

[0812] "Physical signs (symptoms)" are indicators that show the user's physical condition or discomfort.

[0813] "Generative AI" is a system that uses artificial intelligence technology to analyze data and generate appropriate information.

[0814] "Nutrition deficiency" refers to nutrients that are lacking in the user's body or that are being consumed in excess.

[0815] "Essential nutrients" refers to foods, supplements, dishes, etc. that are recommended for users to consume in order to improve their health.

[0816] A "recommendation means" is a method or system for suggesting appropriate nutrients and medical institutions to a user.

[0817] A "direct purchasing method" is a method or system that allows users to easily purchase recommended nutrients.

[0818] "Means for direct communication with medical institutions and doctors" refers to methods and systems that allow users to communicate directly with medical professionals as needed.

[0819] The "Emotion Engine" is an artificial intelligence technology that analyzes the user's emotional state and suggests appropriate responses based on that.

[0820] A "means for generating a purchase link" is a method or system that creates a link for a user to purchase the recommended nutrients online.

[0821] The system for implementing this invention identifies the user's physical signs (symptoms) and, based on those signs, utilizes generative AI to identify nutritional deficiencies and excesses. Furthermore, it recommends necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, and generates links to directly purchase the recommended nutrients. It also provides a means for direct communication with medical institutions and doctors as needed, and uses an emotion engine to recommend appropriate medical institutions and doctors.

[0822] 1. System Program

[0823] This system is realized using the following hardware and software.

[0824] Hardware: Smartphone

[0825] Software: Python, requests library

[0826] 2. Program Processing

[0827] The server receives the user's physical signs (symptoms) and uses generative AI to identify nutritional deficiencies and excesses. It then recommends necessary nutrients based on the nutritional deficiencies and excesses, and generates links to purchase the recommended nutrients. It also analyzes the user's emotional state and recommends appropriate medical institutions and doctors as needed.

[0828] For example, if a user types "I have a headache," the system will recommend bananas, almonds, and liver and provide links to buy them. If a user types "severe depression," the system will recommend psychosomatic or psychiatric care.

[0829] 3. Examples of concrete examples and prompts

[0830] For example, if a user types "I have a headache," the system will recommend bananas, almonds, and liver and provide links to buy them. If a user types "severe depression," the system will recommend psychosomatic or psychiatric care.

[0831] Prompt Sentence Examples

[0832] If a user types "I have a headache," the system will recommend bananas, almonds, and liver and provide links to buy them. If a user types "severe depression," the system will recommend psychosomatic or psychiatric care.

[0833] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0834] Step 1:

[0835] The user inputs physical signs (symptoms) using a smartphone device.

[0836] Input: Symptoms entered by the user (e.g., "I have a headache")

[0837] Output: Input symptom data

[0838] Specific operation: The user starts the application and enters the symptoms in text format into the symptom input screen.

[0839] Step 2:

[0840] The server receives the input symptom data and uses a generative AI model to analyze nutritional deficiencies and excesses.

[0841] Input: Symptom data

[0842] Output: Nutritional data that is insufficient or excessive (e.g. magnesium deficiency)

[0843] Specific operation: The server passes symptom data to the generative AI model, which then retrieves relevant information from the internet and analyzes nutritional deficiencies and excesses.

[0844] Step 3:

[0845] The server recommends necessary nutrients (foods, supplements, dishes, etc.) based on nutritional data on excess and deficiency.

[0846] Input: Excessive or insufficient nutrition data

[0847] Output: Recommended nutrient list (e.g. bananas, almonds, liver)

[0848] Specific operation: The server searches a nutrient database based on the nutritional data of excess and deficiency, and lists appropriate foods and supplements.

[0849] Step 4:

[0850] The server generates links to purchase the recommended nutrients.

[0851] Input: Recommended Nutrition List

[0852] Output: A list of purchase links (e.g. https: / / example.com / purchase / banana)

[0853] Specific operation: Based on the recommended nutrient list, the server generates purchase links for each nutrient and compiles them into a list.

[0854] Step 5:

[0855] The server sends the user a list of recommended nutrients and a list of purchase links.

[0856] Input: Recommended nutrition list, purchase link list

[0857] Output: Nutrition recommendations and purchase links displayed on the user's smartphone

[0858] Specific operation: The server sends a list of recommended nutrients and a list of purchase links to the user's smartphone and displays them on the application screen.

[0859] Step 6:

[0860] Users can send requests to speak directly with medical institutions or doctors as needed.

[0861] Input: User request (e.g., "I want to speak to a doctor")

[0862] Output: Links to medical institutions and doctor conversations

[0863] What happens: The user selects an option within the application and submits a request to speak directly with a healthcare provider or doctor.

[0864] Step 7:

[0865] The server uses an emotion engine to analyze the user's emotional state and recommend appropriate medical institutions and doctors.

[0866] Input: User emotion data (e.g., "severe depression")

[0867] Output: Recommended medical institutions and doctors list (e.g., psychosomatic medicine, psychiatry)

[0868] Specific operation: The server passes the user's emotional data to the emotion engine, which then lists appropriate medical institutions and doctors.

[0869] Step 8:

[0870] The server sends the user a list of recommended medical institutions and doctors.

[0871] Input: Recommended medical institutions and doctor list

[0872] Output: A list of medical institutions and doctors displayed on the user's smartphone

[0873] Specific operation: The server sends a list of recommended medical institutions and doctors to the user's smartphone and displays it on the application screen.

[0874] 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.

[0875] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[0876] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[0877] 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.

[0878] [Second embodiment]

[0879] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0880] 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.

[0881] 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).

[0882] 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.

[0883] 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.

[0884] 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).

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0891] "Example 1"

[0892] The system of the present invention is equipped with an interface that allows users to input their own physical condition and symptoms. This interface can be realized, for example, through a smartphone, a PC application, or a website. The user inputs specific details about their physical condition and symptoms. For example, the user can input information such as "I have a headache" or "I get tired easily."

[0893] "Example 2"

[0894] Next, the system of the present invention utilizes generative AI based on the input of the user's physical condition and symptoms. This AI identifies the appropriate nutrients for the user's physical condition and symptoms from online medical information and nutrition databases. For example, if the user says "I have a headache," it determines that the user may be deficient in magnesium or vitamin B2.

[0895] "Example 3"

[0896] Based on the nutrients identified, the system of the present invention recommends foods, supplements, and dishes containing the necessary nutrients. For example, for a user who has a headache, it would recommend foods such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[0897] "Example 4"

[0898] Furthermore, the system of the present invention provides a function to directly purchase the recommended foods and supplements. For example, it provides recipes containing recommended bananas, almonds, and liver along with links to purchase these ingredients online.

[0899] "Example 5"

[0900] The system of the present invention also provides a function to directly communicate with medical institutions or doctors as needed. For example, if your condition does not improve or if certain symptoms persist, the system will refer you to a specialized medical institution or doctor and arrange an online consultation.

[0901] The processing flow of each embodiment will be described below.

[0902] "Example 1"

[0903] Step 1: The user accesses the system of the present invention and specifically inputs their physical condition and symptoms. For example, they input information such as "I have a headache" or "I get tired easily."

[0904] Step 2: The system of the present invention uses generative AI to identify appropriate nutrients based on the input physical condition and symptoms. This AI identifies appropriate nutrients for the user's physical condition and symptoms from online medical information and nutrition databases.

[0905] Step 3: Based on the identified nutrients, the system of the present invention recommends foods, supplements, and recipes that contain the necessary nutrients.

[0906] Step 4: The system of the present invention provides the ability to directly purchase the recommended foods and supplements. Along with recipes containing the recommended bananas, almonds, and liver, it provides links to purchase these ingredients online.

[0907] Step 5: The system of the present invention also provides the ability to directly communicate with medical institutions or doctors as needed. If your condition does not improve or if certain symptoms persist, the system will refer you to a specialized medical institution or doctor and arrange an online consultation.

[0908] Example 1

[0909] Next, a description will be given of Example 1 of Form 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."

[0910] In modern society, many people need to quickly and accurately understand information about their own physical condition and symptoms and receive appropriate advice. However, conventional systems have difficulty providing appropriate advice based on the physical condition and symptoms entered by the user, and do not adequately recommend necessary nutrients or connect with medical institutions. This makes it difficult for users to properly manage their own health condition.

[0911] 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.

[0912] In this invention, the server includes means for inputting physical signs (symptoms), means for transmitting the physical signs (symptoms) to the server, means for generating advice using a generative AI model based on the physical signs (symptoms), means for transmitting the generated advice to a terminal, means for displaying the generated advice on the terminal, means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the generated advice, means for directly purchasing the recommended nutrients, and means for directly communicating with a medical institution or doctor as needed. This allows the user to quickly receive appropriate advice based on their own physical condition and symptoms, and also enables smooth recommendation of necessary nutrients and collaboration with medical institutions.

[0913] "Physical signs (symptoms)" refer to any abnormalities or discomforts that a user feels regarding their physical condition or health.

[0914] "Input means" refers to the interface through which the user inputs physical signs (symptoms) into the system. Specifically, this includes smartphone and PC applications, websites, etc.

[0915] "Means of transmission" refers to the communication means used to send the physical signs (symptoms) entered by the user to the server. Specifically, this includes HTTP requests using an Internet connection.

[0916] "Generative AI models" refer to artificial intelligence models that generate appropriate advice based on user input. Specifically, they include generative AI models that use natural language processing technology.

[0917] "Means for generating advice" refers to the process of using a generative AI model to generate advice based on the user's physical signs (symptoms).

[0918] "Means for sending to the terminal" refers to a communication means for sending the generated advice to the user's terminal. Specifically, this includes HTTP responses, etc.

[0919] "Displaying means" refers to an interface for visually displaying the generated advice to the user on the device, including, for example, a UI component of an application or an element of a web page.

[0920] "Means for recommending necessary nutrients" refers to a process for recommending necessary nutrients (foods, supplements, dishes, etc.) to a user based on the generated advice.

[0921] "Direct purchasing means" refers to an interface through which a user can directly purchase the recommended nutrients, specifically including online shopping functionality.

[0922] "Means for directly communicating with medical institutions or doctors" refers to means by which users can directly communicate with medical institutions or doctors as needed. Specifically, this includes video calls and chat functions.

[0923] MODE FOR CARRYING OUT THE INVENTION

[0924] This invention is a system that allows users to input their own physical condition and symptoms, and then uses a generative AI model to provide appropriate advice based on that information. This system can be implemented via smartphone or PC applications, websites, etc.

[0925] User Input

[0926] Users input their physical condition and symptoms using a smartphone or PC application or website. For example, a user might enter, "I've been having frequent headaches lately." This input is done through a text box or form in the application.

[0927] Sending data

[0928] The device sends the information about the user's physical condition and symptoms to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is encoded in JSON format.

[0929] Receiving and analyzing data

[0930] The server receives the data sent from the device. The server analyzes the received data and extracts the user's input. For example, the server analyzes the text "I've been having frequent headaches lately" and passes it to the next processing step.

[0931] Advice generation using generative AI models

[0932] The server uses a generative AI model (e.g., a generative AI model using natural language processing technology) to generate advice based on the user's input. Specifically, the server inputs the following prompt sentence into the generative AI model:

[0933] User input: I've been having a lot of headaches lately.

[0934] Prompt for generative AI model: User inputs "I've been having a lot of headaches lately." Please provide appropriate advice.

[0935] The generative AI model generates advice based on this prompt, for example, "We recommend you drink plenty of fluids. If symptoms persist, consult your doctor."

[0936] Sending the results

[0937] The server sends the advice generated by the generative AI model to the terminal. Specifically, the server encodes the generated advice in JSON format and sends it as an HTTP response.

[0938] Displaying the results

[0939] The device displays the advice received from the server to the user. Specifically, the device displays the generated advice using the application's UI components (e.g., a text view or a popup message). The user can view the advice through the application.

[0940] Recommendations for necessary nutrients

[0941] Based on the generated advice, the server recommends the necessary nutrients (foods, supplements, dishes, etc.) to the user. For example, it makes a specific recommendation such as "We recommend that you consume foods that are high in vitamin C."

[0942] Direct purchase of nutrients

[0943] Users can directly purchase the recommended nutrients, specifically by using the online shopping function through the application or website to purchase the recommended foods and supplements.

[0944] Cooperation with medical institutions and doctors

[0945] If necessary, users can talk directly to medical institutions and doctors, specifically by using video calls and chat functions to communicate with doctors in real time.

[0946] In this way, the system of the present invention allows users to quickly receive appropriate advice based on their own physical condition and symptoms, and also makes it possible to smoothly recommend necessary nutrients and collaborate with medical institutions.

[0947] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0948] Program processing flow

[0949] Step 1: User Input

[0950] Users input their physical condition and symptoms using a smartphone or PC application or website. For example, a user might enter, "I've been having frequent headaches lately." This input is done through a text box or form in the application.

[0951] Input: Text data of the user's physical condition and symptoms

[0952] Output: The input text data

[0953] Step 2: Sending data

[0954] The device sends the information about the user's physical condition and symptoms to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is encoded in JSON format.

[0955] Input: Text data entered by the user

[0956] Output: JSON formatted data sent to the server

[0957] Step 3: Receiving and analyzing data

[0958] The server receives the data sent from the device. The server analyzes the received data and extracts the user's input. For example, the server analyzes the text "I've been having frequent headaches lately" and passes it to the next processing step.

[0959] Input: JSON format data sent from the terminal

[0960] Output: Parsed text data

[0961] Step 4: Generative AI model generates advice

[0962] The server uses a generative AI model (e.g., a generative AI model using natural language processing technology) to generate advice based on the user's input. Specifically, the server inputs the following prompt sentence into the generative AI model:

[0963] User input: I've been having a lot of headaches lately.

[0964] Prompt for generative AI model: User inputs "I've been having a lot of headaches lately." Please provide appropriate advice.

[0965] The generative AI model generates advice based on this prompt, for example, "We recommend you drink plenty of fluids. If symptoms persist, consult your doctor."

[0966] Input: Parsed text data

[0967] Output: Text data of the generated advice

[0968] Step 5: Sending the results

[0969] The server sends the advice generated by the generative AI model to the terminal. Specifically, the server encodes the generated advice in JSON format and sends it as an HTTP response.

[0970] Input: Text data of generated advice

[0971] Output: Advice data sent to the terminal in JSON format.

[0972] Step 6: View the results

[0973] The device displays the advice received from the server to the user. Specifically, the device displays the generated advice using the application's UI components (e.g., a text view or a popup message). The user can view the advice through the application.

[0974] Input: Advice data received from the server in JSON format

[0975] Output: The text of the advice displayed to the user

[0976] Step 7: Recommending Nutrient Needs

[0977] Based on the generated advice, the server recommends the necessary nutrients (foods, supplements, dishes, etc.) to the user. For example, it makes a specific recommendation such as "We recommend that you consume foods that are high in vitamin C."

[0978] Input: Text data of generated advice

[0979] Output: Text data of recommended nutrients

[0980] Step 8: Buy nutrients directly

[0981] Users can directly purchase the recommended nutrients, specifically by using the online shopping function through the application or website to purchase the recommended foods and supplements.

[0982] Input: Text data of recommended nutrients

[0983] Output: Purchase completion notification

[0984] Step 9: Collaboration with medical institutions and doctors

[0985] If necessary, users can talk directly to medical institutions and doctors, specifically by using video calls and chat functions to communicate with doctors in real time.

[0986] Input: Information about the user's health and symptoms

[0987] Output: Communication logs with medical institutions and doctors

[0988] (Application example 1)

[0989] Next, a description will be given of Application Example 1 of Form 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."

[0990] Conventional health management systems have the problem that users only need to input their own health condition and symptoms, making it difficult to take prompt action when an abnormality is detected. Furthermore, there is a lack of a means to send appropriate notifications when an abnormality is detected, and measures to ensure user safety are insufficient. This makes it difficult for users to quickly access appropriate medical institutions and emergency contacts in the event of an emergency.

[0991] 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.

[0992] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with medical institutions or doctors as needed, means for detecting abnormalities based on the bodily signs (symptoms) and sending notifications, and communication means for sending the notifications. This allows the user not only to input their own physical condition and symptoms, but also to quickly send notifications when abnormalities are detected and take appropriate action.

[0993] "Physical signs (symptoms)" refers to specific information about a user's physical condition or health status.

[0994] "Generative AI" is an artificial intelligence technology that analyzes data on physical condition and symptoms entered by users and provides appropriate nutritional and medical information.

[0995] "Nutrition deficiency" is information that indicates whether the user is lacking or over-dosing on necessary nutrients based on their physical condition and symptoms.

[0996] "Essential nutrients" are the nutritional components of foods, supplements, dishes, etc. that are recommended to improve the user's health.

[0997] "Recommendation methods" are methods that suggest appropriate nutrients to users based on the results of analysis by generative AI.

[0998] "Direct purchasing means" refers to a method that allows users to purchase the recommended nutrients on-site.

[0999] "Direct communication with healthcare providers and physicians" means a method by which users can communicate with healthcare professionals in real time as needed.

[1000] "Means for detecting abnormalities" refers to a method for analyzing data on physical condition and symptoms entered by the user and determining whether or not there is an abnormality.

[1001] "Means for sending notifications" refers to the method for sending warnings and information to users and emergency contacts when an abnormality is detected.

[1002] "Communication means" refers to the communication technology, such as the internet or mobile network, used to send the notification.

[1003] As an embodiment of the present invention, the following system can be constructed.

[1004] System configuration

[1005] The system consists of a device (such as a smartphone or PC) with an interface for inputting the user's physical condition and symptoms, and a server for analyzing the data. The server uses a generative AI model to analyze the data and detect necessary nutrients and abnormalities.

[1006] Program processing

[1007] Hardware

[1008] Smartphone

[1009] PC

[1010] server

[1011] software

[1012] Python

[1013] The requests library (to send HTTP requests)

[1014] Generative AI Model

[1015] Data processing and calculation

[1016] 1. Data input: Users enter their own physical condition and symptoms through a smartphone or computer interface. For example, they enter specific information such as "I have a headache" or "I get tired easily."

[1017] 2. Data analysis: The server uses a generative AI model to analyze the input data, identify nutritional deficiencies and excesses, and determine the appropriate response if an abnormality is detected.

[1018] 3. Recommendations and Notifications: The server recommends necessary nutrients to the user based on the analysis results. Furthermore, if an abnormality is detected, a notification will be sent to the user or emergency contacts via communication means.

[1019] Specific examples

[1020] For example, if a user types "I have a headache," the server uses a generative AI model to analyze this information and identify possible nutrient deficiencies or excesses that could be causing the headache. It then recommends the necessary nutrients (such as magnesium or B vitamins) to the user. Furthermore, if an abnormality is detected, a notification is sent to emergency contacts to prompt appropriate action.

[1021] Prompt Sentence Examples

[1022] "Write a Python program that analyzes the user's physical condition and symptoms and sends a notification if an abnormality is detected. Anomalies will be detected based on specific keywords (e.g. headache, fatigue, dizziness, chest pain). Notifications will be sent using an HTTP POST request."

[1023] In this way, a system can be realized in which a user simply inputs their own physical condition and symptoms, and if an abnormality is detected, a notification is sent quickly and appropriate action can be taken.

[1024] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1025] Step 1:

[1026] Users input their physical condition and symptoms through a smartphone or computer interface.

[1027] Input: Information about your physical condition or symptoms entered by the user (e.g., "I have a headache" or "I get tired easily").

[1028] Output: Input data on physical condition and symptoms.

[1029] Specific operation: The user launches the application, enters their physical condition and symptoms in the text box, and presses the send button.

[1030] Step 2:

[1031] The device sends the entered data on physical condition and symptoms to the server.

[1032] Input: Physical condition and symptom data entered by the user.

[1033] Output: Health and symptom data sent to the server.

[1034] Specific operation: The device sends the input data to the server using an HTTP POST request.

[1035] Step 3:

[1036] The server inputs the data on physical condition and symptoms received into a generative AI model for analysis.

[1037] Input: Health and symptom data received by the server.

[1038] Output: Analysis results (presence or absence of nutritional deficiency or abnormalities).

[1039] How it works: The server inputs data into a generative AI model, which then analyzes the data to identify any nutritional deficiencies or abnormalities.

[1040] Step 4:

[1041] The server recommends necessary nutrients to the user based on the analysis results.

[1042] Input: Analysis results of a generative AI model.

[1043] Output: A list of recommended nutrients.

[1044] Specific operation: Based on the analysis results, the server generates a message recommending appropriate nutrients (foods, supplements, dishes, etc.) to the user.

[1045] Step 5:

[1046] If the server detects an abnormality, it will send a notification.

[1047] Input: Analysis results of the generative AI model (presence or absence of anomalies).

[1048] Output: Informational message.

[1049] Specific behavior: If the server detects an abnormality, it executes an HTTP POST request to send a notification to the emergency contact or user.

[1050] Step 6:

[1051] The device receives recommended messages and notifications from the server and displays them to the user.

[1052] Input: Recommendation messages and notifications sent by the server.

[1053] Output: The suggested message or notification that will be displayed to the user.

[1054] Specific operation: The device receives the message from the server and displays it on the application interface.

[1055] By following the above steps, a system can be realized in which a user can simply input their own physical condition and symptoms, and if an abnormality is detected, a notification will be sent quickly and appropriate action can be taken.

[1056] Example 2

[1057] Next, a description will be given of Example 2 of Form 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."

[1058] In modern society, it is important to quickly and accurately identify and provide appropriate nutrients based on an individual's physical condition and symptoms. However, conventional systems require users to input their physical condition and symptoms and then identify appropriate nutrients based on that information, which is a cumbersome process. It is also difficult to collect accurate data from the vast amount of information available on the Internet. Furthermore, there is a lack of support for users to take specific actions based on the information they obtain. This limits the means by which users can consume appropriate nutrients.

[1059] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1060] In this invention, the server includes: a means for a user to input their physical condition and symptoms; a means for a terminal to send the input data to the server; a means for the server to receive the data and send a prompt to the generative AI model; a means for the server to receive a response from the generative AI model and refer to an online medical information or nutrition database; a means for the server to identify appropriate nutrients and send the results to the terminal; a means for the terminal to display the results to the user; and a means for the user to check the results and input additional questions or data as necessary. This enables the user to quickly and accurately identify appropriate nutrients based on their physical condition and symptoms and receive support for taking specific actions.

[1061] "Physical signs (symptoms)" refer to abnormalities or discomforts that a user feels regarding their physical condition or health.

[1062] "Generative AI" refers to an artificial intelligence model that generates appropriate responses and information based on input data.

[1063] "Nutrition deficiency" refers to an excess or deficiency of nutrients required based on the user's physical condition or symptoms.

[1064] "Necessary nutrients" refers to nutrients that are recommended for intake to improve the user's physical condition or symptoms.

[1065] "Food, supplements, dishes, etc." refers to ingredients, supplements, or prepared dishes that contain necessary nutrients.

[1066] "Recommendation methods" refer to methods of suggesting foods and supplements containing necessary nutrients to users.

[1067] "Direct purchase method" refers to the way in which users can purchase recommended foods and supplements directly, either online or in-store.

[1068] "Means for direct communication with medical institutions and doctors" refers to methods by which users can communicate directly with medical professionals as needed.

[1069] "Means for users to input their physical condition and symptoms" refers to an interface that allows users to input their own physical condition and symptoms into the system.

[1070] "Means for the terminal to transmit input data to the server" refers to a communication means for transmitting data input by the user to the server.

[1071] "Means by which the server receives data and sends prompts to the generative AI model" refers to the method by which the server receives data from the user and issues instructions to the generative AI model based on that data.

[1072] "Means for the server to receive the response from the generative AI model and refer to medical information and nutrition databases on the Internet" refers to a method for the server to receive the response from the generative AI model and search databases on the Internet to obtain more detailed information.

[1073] "Means for the server to identify appropriate nutrients and send the results to the terminal" refers to a method in which the server identifies nutrients appropriate for the user based on the information collected and sends the results to the user's terminal.

[1074] "Means by which the terminal displays the results to the user" refers to a method for visually displaying the results sent from the server to the user.

[1075] "Means for the user to review the results and enter additional questions or data as needed" refers to an interface that allows the user to review the displayed results and enter more detailed information or additional questions.

[1076] This invention is a system that identifies appropriate nutrients based on the user's physical condition and symptoms and provides them to the user. This system operates in cooperation with a server, a terminal, and the user.

[1077] Hardware and software used

[1078] server

[1079] The server performs the main processing, such as receiving data, using the generative AI model, referencing databases on the Internet, and sending results. The server uses the following software and hardware:

[1080] Generative AI models: Advanced natural language processing models such as GPT-4

[1081] Database access tools: APIs for accessing online medical information and nutrition databases (e.g., PubMed, USDA Nutrient Database)

[1082] Communication protocol: A secure communication protocol such as HTTPS

[1083] Terminal

[1084] The terminal is a device that allows users to input their physical condition and symptoms and displays the results from the server. The terminal uses the following software and hardware:

[1085] Input interface: A form for users to enter their physical condition and symptoms

[1086] Display interface: A screen for displaying the results from the server.

[1087] Communication module: A module for sending and receiving data with the server

[1088] User

[1089] The user is the entity that inputs their own physical condition and symptoms and takes action based on the information provided by the system.

[1090] Data processing and calculation

[1091] 1. The user inputs their physical condition and symptoms

[1092] The user inputs their physical condition and symptoms into an input form on the device. For example, they might input "I have a headache."

[1093] 2. The device sends the input data to the server

[1094] The terminal transmits the data entered by the user to the server. At this time, the data is encrypted before transmission.

[1095] 3. The server receives the data and sends prompts to the generative AI model

[1096] The server receives the data sent from the device, creates a prompt for the generative AI model, and sends it. An example of a prompt might be, "The user is complaining of a headache. Please tell me about nutrients and measures related to headaches."

[1097] 4. The server receives the response from the generative AI model and references medical and nutritional information databases on the Internet.

[1098] The server receives the response from the generative AI model and consults online medical and nutritional databases for further information.

[1099] 5. The server identifies the appropriate nutrients and sends the results to the device.

[1100] The server identifies the nutrients that are suitable for the user based on the collected information and sends the results to the device. For example, it may determine that a person suffering from a headache may be deficient in magnesium or vitamin B2.

[1101] 6. The terminal displays the results to the user.

[1102] The terminal receives the results sent from the server and displays them to the user, including the identified nutrients and how to take them.

[1103] 7. The user reviews the results and enters additional questions or data as needed.

[1104] The user reviews the results displayed on the device and enters additional questions or data as needed, for example, "What foods are high in magnesium?"

[1105] Specific examples

[1106] Example 1: If you have a headache

[1107] 1. The user types "I have a headache" into the terminal.

[1108] 2. The device sends this information to the server.

[1109] 3. The server uses a generative AI model (e.g., GPT-4) to analyze the information "I have a headache."

[1110] 4. The server collects relevant information from medical information and nutrition databases on the Internet (e.g., PubMed, USDA Nutrient Database).

[1111] 5. The server determines that the headache may be related to a deficiency of magnesium or vitamin B2.

[1112] 6. The server sends this information back to the device.

[1113] 7. The terminal displays the analysis results to the user.

[1114] 8. The user selects foods and supplements containing magnesium and vitamin B2 based on the displayed information.

[1115] This system supports health management by identifying and providing appropriate nutrients to users based on their physical condition and symptoms.

[1116] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1117] Step 1:

[1118] The user inputs their physical condition and symptoms.

[1119] The user inputs their physical condition and symptoms into an input form on the device. For example, they input "I have a headache." The input data is text information about the user's physical condition and symptoms. The device temporarily stores this input data.

[1120] Step 2:

[1121] The terminal sends the input data to the server.

[1122] The terminal sends the data entered by the user to the server. At this time, the data is encrypted before being sent. The input is text data about the user's physical condition and symptoms, and the output is the encrypted data sent to the server. The terminal notifies the user that the transmission is complete.

[1123] Step 3:

[1124] The server receives the data and sends prompts to the generative AI model.

[1125] The server receives the data sent from the device. Next, it creates a prompt for the generative AI model based on the received data and sends it. The input is encrypted data on physical condition and symptoms, and the output is the prompt text sent to the generative AI model. An example of a prompt text could be, "The user is complaining of a headache. Please tell me about nutrients and measures related to headaches."

[1126] Step 4:

[1127] The server receives the response from the generative AI model and references medical information and nutritional databases on the Internet.

[1128] The server receives the response from the generative AI model. The response includes nutrients and measures related to headaches. The server then references online medical information and nutrition databases to confirm and complement the response. The input is the response data from the generative AI model, and the output is the complemented medical information and nutrition data. The server collects information using a database access tool.

[1129] Step 5:

[1130] The server identifies the appropriate nutrients and sends the results to the device.

[1131] The server uses the collected information to identify the appropriate nutrients for the user's physical condition and symptoms. For example, if a person has a headache, it may determine that they may be deficient in magnesium or vitamin B2. The server then sends the results to the device. The input is supplemented medical information and nutritional data, and the output is information about the identified nutrients. The server encrypts the data when sending the results to the device.

[1132] Step 6:

[1133] The terminal displays the results to the user.

[1134] The terminal receives the results sent from the server and displays them to the user. The displayed content includes the identified nutrients and their intake methods. The input is the encrypted data sent from the server, and the output is the analysis results displayed to the user. The terminal displays the results in a visually easy-to-understand format.

[1135] Step 7:

[1136] The user reviews the results and enters additional questions or data as needed.

[1137] The user checks the results displayed on the terminal. If necessary, they can enter additional questions or data. For example, they can enter "What foods are high in magnesium?" The input is the user's additional question or data, and the output is the new input data stored on the terminal. The terminal prepares to send the additional input data to the server again.

[1138] (Application example 2)

[1139] Next, a description will be given of Application Example 2 of Form 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."

[1140] In modern society, it is important to consume appropriate nutrients based on individual physical condition and symptoms, but it is difficult for the average consumer to determine appropriate nutrients on their own and choose meals based on that. Furthermore, there are limited ways to easily obtain meals containing appropriate nutrients. Furthermore, there is a lack of ways to directly communicate with medical institutions or doctors based on physical condition and symptoms. A system that can solve these issues is needed.

[1141] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for identifying bodily signs (symptoms), a means for identifying nutritional deficiencies or excesses based on the bodily signs (symptoms) using generative AI, a means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the nutritional deficiencies or excesses, a means for proposing a meal menu containing the recommended nutrients, a means for ordering delivery of the proposed meal menu, and a means for directly communicating with a medical institution or doctor as needed. This allows the user to easily select and order delivery of meals containing appropriate nutrients based on their physical condition and symptoms. Furthermore, the ability to directly communicate with a medical institution or doctor as needed enables more appropriate health management.

[1142] "Physical signs (symptoms)" are things that indicate changes in physical condition or discomfort that the user feels.

[1143] "Generative AI" is an artificial intelligence technology that generates appropriate information based on input data.

[1144] "Nutrition deficiency" refers to an excess or deficiency of necessary nutrients, determined based on the user's physical condition and symptoms.

[1145] "Essential nutrients" are nutrients that are recommended for intake to improve the user's physical condition and symptoms.

[1146] A "meal menu" is a list of dishes or foods that contain a particular nutrient.

[1147] A "delivery order" is an ordering procedure for delivering a meal menu selected by the user to a specified location.

[1148] "Direct communication with medical institutions and doctors" means a means for users to communicate with medical professionals in real time.

[1149] The system for implementing this invention suggests appropriate nutrients based on the user's physical condition and symptoms, and enables delivery orders of meal menus containing those nutrients. Specific embodiments of this system are described below.

[1150] Hardware and software used

[1151] Hardware: Smartphone

[1152] Software: Python, transformers library, requests library

[1153] Processing flow

[1154] 1. Enter your physical condition and symptoms:

[1155] Users use a smartphone application to input their current physical condition and symptoms, and this input data is sent to a server.

[1156] 2. Nutrition Suggestions:

[1157] The server uses a generative AI model (e.g., GPT-3) to suggest necessary nutrients based on the input symptoms, using prompts such as the following:

[1158] Example prompt: "If a user feels like they have a headache, what nutrients do they need?"

[1159] 3. Menu suggestions:

[1160] The server retrieves a meal menu with suggested nutrients from an external API (e.g., foodmenu.com) and displays it to the user.

[1161] 4. Delivery Order:

[1162] The user orders the selected menu through the delivery service's API (e.g., fooddelivery.com). The order data is sent from the server to the delivery service.

[1163] Specific examples

[1164] For example, if a user inputs "I have a headache," the server uses a generative AI model to determine that "I may be deficient in magnesium or vitamin B2." The server then retrieves meal menus containing these nutrients from an external API and suggests them to the user. By ordering delivery for the menu selected by the user, meals containing the appropriate nutrients are delivered to the user's specified location.

[1165] In this way, users can easily select meals containing the right nutrients based on their physical condition and symptoms, and order delivery. They can also directly communicate with medical institutions and doctors as needed, enabling more appropriate health management.

[1166] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1167] Step 1:

[1168] The user uses a smartphone application to input their current physical condition and symptoms. The input data is sent from the user's device to a server. The input data includes specific symptoms, such as "I have a headache."

[1169] Step 2:

[1170] The server uses a generative AI model (e.g., GPT-3) to suggest necessary nutrients based on the received data on physical condition and symptoms. The server inputs the following prompt sentence into the generative AI model:

[1171] Example prompt: "If a user feels like they have a headache, what nutrients do they need?"

[1172] The generative AI model outputs appropriate nutrients (e.g., magnesium or vitamin B2) based on the prompt.

[1173] Step 3:

[1174] Based on the nutrient information obtained from the generative AI model, the server calls an external API (e.g., foodmenu.com) to obtain meal menus containing the relevant nutrients. The server inputs a list of nutrients to the external API and receives a list of corresponding meal menus as output.

[1175] Step 4:

[1176] The server sends the obtained list of meal menus to the user terminal and displays it to the user, who then selects the meal they want from the displayed menu.

[1177] Step 5:

[1178] The information about the meal menu selected by the user is sent from the user's device to the server. The server calls the delivery service's API (e.g., fooddelivery.com) based on the information about the selected menu and places a delivery order. The server inputs the order data (e.g., menu ID, delivery address) into the delivery service's API and receives an order confirmation output.

[1179] Step 6:

[1180] The server sends a confirmation of the delivery order to the user's terminal and notifies the user that the order has been completed. The user receives the order confirmation and waits for the meal to be delivered to the specified location.

[1181] In this way, users can easily select meals containing the right nutrients based on their physical condition and symptoms, and order delivery.

[1182] Example 3

[1183] Next, a description will be given of Example 3 of Form Example 3. 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."

[1184] In modern society, it is important to consume appropriate nutrients according to individual health conditions and symptoms, but it is difficult for users to understand their own nutritional needs and select appropriate foods and supplements. Furthermore, there is a lack of easy ways to purchase recommended foods and supplements, or to directly communicate with medical institutions or doctors when necessary. Therefore, there is a need for a system that provides comprehensive support for users to improve their health.

[1185] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1186] In this invention, the server includes means for grasping bodily signs (symptoms), means for identifying nutritional deficiencies and excesses based on the bodily signs (symptoms) using generative AI, means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for inputting the bodily signs (symptoms), means for transmitting the input data to the server, means for analyzing the input data using the generative AI model, means for identifying necessary nutrients from the analysis results, means for recommending appropriate foods and supplements by referring to the database, means for generating links to purchase the recommended foods and supplements, and means for introducing the medical institution or doctor and arranging an online consultation. This allows users to support their intake of appropriate nutrients according to their health condition, easily purchase necessary foods and supplements, and even easily connect with medical institutions and doctors.

[1187] "Physical signs (symptoms)" refers to information about the user's health condition and physical condition, and specifically includes symptoms such as headache, fatigue, and loss of appetite.

[1188] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and identify necessary nutrients and recommended foods based on user input.

[1189] "Nutrition deficiency" refers to information indicating whether the user's current nutritional intake is deficient or excessive based on the user's health condition and symptoms.

[1190] "Essential nutrients" refer to specific nutritional components that are recommended for the user to consume in order to improve their health, and are provided in the form of foods, supplements, dishes, etc.

[1191] "Recommendation methods" refers to methods that suggest appropriate foods, supplements, and dishes to users based on the results of analysis by generative AI.

[1192] "Direct purchasing" refers to providing a link or interface that allows users to easily purchase the recommended foods or supplements online.

[1193] "Means for direct communication with medical institutions and doctors" refers to methods that allow users to consult or receive medical advice online from medical professionals as needed.

[1194] "Input means" refers to an interface that allows a user to input their health condition and symptoms into the system.

[1195] "Means for transmitting input data to a server" refers to a communication means for transmitting information input by a user to a server.

[1196] "Means for analyzing input data using a generative AI model" refers to a method in which a server uses a generative AI model to analyze a user's input data and identify necessary nutrients.

[1197] "Means for recommending appropriate foods and supplements by referring to a database" refers to a method in which the server refers to nutritional information stored in a database and suggests appropriate foods and supplements to the user.

[1198] "Means for generating a purchase link" refers to a method by which the server generates a link for purchasing the recommended food or supplement and provides it to the user.

[1199] "Means for introducing medical institutions and doctors and arranging online consultations" refers to a method in which the server introduces appropriate medical institutions and doctors based on the user's health condition and arranges online consultations.

[1200] This invention is a system that recommends appropriate nutrients based on a user's health condition and symptoms, and supports collaboration with medical institutions and doctors as needed. Specific embodiments of this system are described below.

[1201] System configuration

[1202] This system includes a terminal used by the user, a server that processes data, and a generative AI model. The terminal is a device such as a smartphone or PC, and the server is a computer system that analyzes data and makes recommendations. The generative AI model is built using Python libraries (e.g., TensorFlow and PyTorch).

[1203] Program processing

[1204] User Input

[1205] The user enters their health condition and symptoms into an input form on the device. For example, they might enter "I have a headache." This input data is then sent from the device to the server.

[1206] Data analysis

[1207] The server inputs the received data into a generative AI model for analysis. The generative AI model identifies the necessary nutrients from the user's input data. For example, if the user says "I have a headache," it will determine that magnesium and vitamin B2 are necessary.

[1208] Nutrition Recommendations

[1209] Based on the analysis results, the server refers to a database and recommends appropriate foods and supplements, such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[1210] Generate purchase links

[1211] The server generates links to purchase the recommended foods and supplements, allowing users to easily purchase the recommended foods and supplements online. For example, recipes for dishes containing bananas, almonds, and liver are provided along with links to purchase those ingredients.

[1212] Cooperation with medical institutions and doctors

[1213] If necessary, the server will refer users to medical institutions or doctors and arrange online consultations, allowing them to speak directly with specialists if their condition does not improve or if certain symptoms persist.

[1214] Specific examples

[1215] Prompt Sentence Examples

[1216] For a user who inputs "I have a headache," the server performs the following processing:

[1217] 1. The user enters "I have a headache" into the input form on the terminal and clicks the "Submit" button.

[1218] 2. The terminal sends the input data to the server as an HTTP request.

[1219] 3. The server uses a generative AI model to analyze the input "I have a headache" and determine that magnesium and vitamin B2 are needed nutrients.

[1220] 4. The server consults a database and recommends foods like bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[1221] 5. The server generates and provides the user with a link to purchase the recommended food online.

[1222] 6. If necessary, the server will refer you to a medical institution or doctor and arrange an online consultation.

[1223] In this way, the system can support the user in taking appropriate nutrients according to their health condition, and facilitate the purchase of necessary foods and supplements, as well as cooperation with medical institutions and doctors. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1224] Step 1:

[1225] The user inputs their health condition and symptoms.

[1226] The user enters their health condition or symptoms, such as "I have a headache," into the input form on the device and clicks the "Submit" button. The input data is text information about the user's health condition or symptoms. The output is that the input data is saved on the device.

[1227] Step 2:

[1228] The terminal sends the input data to the server.

[1229] The device sends the data entered by the user to the server as an HTTP request. The input is the health condition or symptom data entered by the user. The output is the input data received by the server. Specifically, the device generates an HTTP request and sends a payload containing the input data to the server.

[1230] Step 3:

[1231] The server uses the generative AI model to analyze the input data.

[1232] The server inputs the received data into a generative AI model for analysis. The input is data about the user's health condition and symptoms. The output is information about necessary nutrients. Specifically, the server runs the AI ​​model using Python libraries (e.g., TensorFlow and PyTorch) to extract necessary nutrients from the input data.

[1233] Step 4:

[1234] Know the nutrients your server needs.

[1235] The server determines the nutrients the user needs from the analysis results of the generative AI model. The input is the analysis results of the generative AI model. The output is a list of necessary nutrients. Specifically, the server compares the analysis results with a database to identify necessary nutrients such as magnesium and vitamin B2.

[1236] Step 5:

[1237] The server refers to the database to recommend appropriate foods and supplements.

[1238] The server references a database and recommends foods and supplements rich in necessary nutrients. The input is a list of necessary nutrients. The output is a list of recommended foods and supplements. Specifically, the server executes SQL queries to obtain food information such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[1239] Step 6:

[1240] The server generates links to purchase the recommended foods and supplements.

[1241] The server generates links to purchase the recommended foods and supplements. The input is a list of recommended foods and supplements. The output is a purchase link. Specifically, the server calls the API of the e-commerce site and generates recipes and purchase links for dishes containing bananas, almonds, and liver.

[1242] Step 7:

[1243] The server will refer patients to medical institutions and doctors as needed and arrange online consultations.

[1244] If necessary, the server will refer the user to a medical institution or doctor and arrange an online consultation. The input is data about the user's health condition and symptoms. The output is referral information for the medical institution or doctor and a link to book an appointment. Specifically, the server uses the API of the medical institution's reservation system or video call service to generate the appointment and video call link.

[1245] (Application example 3)

[1246] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1247] In modern society, importance is placed on consuming the appropriate nutrients according to each individual's health condition. However, it is not easy for the average consumer to understand the nutrients they need based on their own physical condition and symptoms, and then select foods and supplements accordingly. Furthermore, if symptoms do not improve even after consuming the appropriate nutrients, they are required to promptly consult a medical institution or doctor, but arranging this can be complicated. A system to solve these issues is needed.

[1248] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1249] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for providing a link for purchasing the recommended nutrients, and means for arranging an online consultation with a medical institution or doctor based on the bodily signs (symptoms).This allows users to easily grasp appropriate nutrients based on their symptoms and quickly purchase the necessary foods and supplements, as well as to quickly consult a medical institution or doctor if symptoms do not improve.

[1250] "Physical signs (symptoms)" are indicators of the user's physical condition or abnormalities, and include specific symptoms such as headaches and fatigue.

[1251] "Generative AI" is a system that uses artificial intelligence technology to analyze data and recommend necessary nutrients based on the user's symptoms.

[1252] "Nutrition deficiency" refers to nutrients that are lacking or being consumed in excess in the user's body.

[1253] "Essential nutrients (foods, supplements, dishes, etc.)" refers to foods, supplements, or dishes that are recommended for the user to consume in order to improve their health.

[1254] "Recommendation methods" are methods that use generative AI to suggest foods, supplements, and dishes that contain appropriate nutrients to users.

[1255] "Direct purchasing methods" are methods that allow users to purchase recommended foods and supplements directly online.

[1256] "Means for direct communication with medical institutions and doctors" refers to methods that allow users to communicate directly with medical institutions and doctors online as needed.

[1257] "Means for providing links to purchase" refers to a method of providing users with web links to purchase foods or supplements containing the recommended nutrients.

[1258] "Means for arranging online consultations" refers to the means for booking and arranging online consultations with medical institutions and doctors based on the user's symptoms.

[1259] The system for implementing this invention is configured as an application installed on a user's smartphone. The system identifies the user's physical signs (symptoms) and, based on those signs, uses generative AI to identify nutritional deficiencies and excesses. It also recommends foods, supplements, and recipes containing necessary nutrients and provides links for directly purchasing the recommended nutrients. It also has a function for directly communicating online with a medical institution or doctor, if necessary.

[1260] Hardware and Software Configuration

[1261] Hardware: Smartphone

[1262] Software: Python, API, generative AI models

[1263] Data processing and calculation

[1264] 1. Understanding physical signs (symptoms): The user inputs their symptoms into the application, for example, "I have a headache."

[1265] 2. Analysis by generative AI: The server sends the user's input data to a generative AI model, which analyzes the nutrient deficiencies and excesses. The generative AI model then recommends nutrients appropriate for the user's symptoms based on information obtained from the internet.

[1266] 3. Nutrient recommendation: Based on the analysis results, the server recommends foods, supplements, and dishes containing the necessary nutrients to the user. For example, if a person has a headache, it will recommend bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[1267] 4. Providing a purchase link: The server generates a link to purchase the recommended foods and supplements and provides it to the user. The user can complete the purchase procedure directly within the application.

[1268] 5. Online consultation with a medical institution or doctor: If necessary, the server will arrange an online consultation with a medical institution or doctor based on the user's symptoms. The user can talk to the doctor directly through the application.

[1269] Specific examples

[1270] For example, if a user complains of a headache, the app will use a generative AI model to analyze their nutritional needs and recommend foods like bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2. It will also provide links to purchase these foods and supplements, and if symptoms do not improve, it will arrange an online consultation with a doctor.

[1271] Prompt Sentence Examples

[1272] If a user complains of a "headache," design your application to recommend foods and supplements containing the necessary nutrients, provide links to purchase them, and, if symptoms persist, arrange an online consultation with a doctor.

[1273] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1274] Step 1:

[1275] The user starts the application and inputs their physical symptoms, for example, "I have a headache."

[1276] Input: User symptom data (e.g. headache)

[1277] Output: Symptom data is sent to the application.

[1278] Step 2:

[1279] The terminal transmits the input symptom data to the server.

[1280] Input: User symptom data

[1281] Output: Symptom data is sent to the server.

[1282] Step 3:

[1283] The server inputs the received symptom data into a generative AI model to analyze excess or deficiency of nutrients. The generative AI model performs analysis based on information obtained from the internet.

[1284] Input: Symptom data

[1285] Output: List of nutrients needed (e.g. magnesium, vitamin B2)

[1286] Step 4:

[1287] The server recommends appropriate foods, supplements, and dishes based on a list of necessary nutrients obtained from a generative AI model.

[1288] Input: List of nutrients needed

[1289] Output: A list of recommended foods, supplements, and dishes (e.g., bananas, almonds, liver)

[1290] Step 5:

[1291] The server generates a link to purchase the recommended foods and supplements and sends it to the device.

[1292] Input: A list of recommended foods, supplements, and recipes

[1293] Output: Purchase link (e.g. Banana purchase link)

[1294] Step 6:

[1295] The device displays the purchase link received from the server to the user, who can click the link to purchase the recommended food or supplement.

[1296] Enter: Purchase Link

[1297] Output: Purchase link shown to the user

[1298] Step 7:

[1299] If the user does not see any improvement in their symptoms, the terminal sends a request to the server to arrange an online consultation with a medical institution or doctor based on the user's request.

[1300] Input: User consultation request

[1301] Output: A consultation request is sent to the server.

[1302] Step 8:

[1303] Based on the user's symptom data and consultation request, the server arranges an online consultation with an appropriate medical institution or doctor and sends that information to the terminal.

[1304] Input: Symptom data, consultation request

[1305] Output: Detailed information about the online consultation (e.g., consultation date and time, doctor information)

[1306] Step 9:

[1307] The terminal displays the detailed information of the online consultation received from the server to the user, and the user can receive the online consultation at the specified date and time.

[1308] Input: Online consultation details

[1309] Output: The consultation information displayed to the user

[1310] 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.

[1311] "Example 1"

[1312] A first embodiment of the present invention is a system that combines an emotion engine that recognizes a user's emotions. This system grasps not only the user's physical condition and symptoms, but also the user's emotions. Specifically, the system recognizes the user's emotions from the tone of voice that the user uses when speaking to the system and the phrasing of text input. For example, from the tone of voice of "I'm very tired today" or the text input of "I've been feeling down lately," the emotion engine recognizes that the user is tired or depressed.

[1313] "Example 2"

[1314] A second example is a system in which an emotion engine recommends appropriate nutrients based on the user's emotions. This system recommends nutrients that are believed to help improve the user's emotions, depending on the user's emotions. For example, if the system recognizes that the user is feeling stressed, it recommends foods and supplements containing nutrients that are believed to help relieve stress, such as B vitamins and magnesium.

[1315] "Example 3"

[1316] A third example is a system in which an emotion engine recommends appropriate medical institutions and doctors based on the user's emotions. If the user's emotions deteriorate beyond a certain range, for example, if the system recognizes that the user is showing symptoms of serious depression, it recommends specialized medical institutions and doctors. Specifically, it recommends psychosomatic medicine or psychiatric medical institutions, or doctors specializing in psychotherapy, and encourages the user to receive appropriate medical care.

[1317] The processing flow of each embodiment will be described below.

[1318] "Example 1"

[1319] Step 1: Collect the tone of voice and wording of the text input the user makes when speaking to the system.

[1320] Step 2: Input the collected data into the emotion engine.

[1321] Step 3: The emotion engine recognizes the user's emotion and outputs the result.

[1322] "Example 2"

[1323] Step 1: Recognize the user's emotions with the emotion engine.

[1324] Step 2: Based on the emotion you identify, search the database for nutrients that are known to help improve that emotion.

[1325] Step 3: Present the search results to the user as recommendations.

[1326] "Example 3"

[1327] Step 1: Recognize the user's emotions with the emotion engine.

[1328] Step 2: If the perceived emotion is deemed to have worsened beyond a certain level, a database is searched for specialized medical institutions and doctors.

[1329] Step 3: Present the search results to the user as recommendations, encouraging them to receive appropriate medical care.

[1330] Example 1

[1331] Next, a description will be given of Example 1 of Form 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."

[1332] Conventional health management systems are required to not only understand the user's physical condition and symptoms, but also to take into account emotional changes. However, current systems have difficulty accurately recognizing the user's emotions and providing appropriate advice based on them. Furthermore, they lack the means to analyze the information entered by the user and provide appropriate nutritional information or connect with medical institutions. This can lead to inadequate health management for the user and delay in appropriate responses.

[1333] 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.

[1334] In this invention, the server includes means for providing an interface for the user to input information about their physical condition and symptoms, means for analyzing the data input through the interface, means for recognizing the user's emotions based on the analyzed data, and means for displaying the analysis results to the user. This makes it possible to comprehensively grasp not only the user's physical condition and symptoms but also changes in their emotions, and to quickly provide appropriate advice and support.

[1335] "Physical signs (symptoms)" are specific symptoms or signs that indicate the user's physical condition or health state.

[1336] "Generative AI" is a system that uses artificial intelligence technology to analyze data and provide appropriate advice and information to users.

[1337] "Nutrition deficiency" refers to an excess or deficiency of necessary nutrients, determined based on the user's physical condition and symptoms.

[1338] "Essential nutrients" are foods, supplements, recipes, etc. that are recommended to improve the user's health.

[1339] An "interface" is a means by which a user inputs their physical condition and symptoms, and can take the form of a smartphone app or website.

[1340] "Means of analysis" refers to the technology or method for processing the data entered by the user and analyzing their physical condition, symptoms, emotions, etc.

[1341] "Means for recognizing emotions" refers to techniques and methods for analyzing and recognizing emotions from the tone of a user's voice and the wording of text input.

[1342] "Means for displaying the analysis results" refers to the methods and techniques for visually presenting the results of the analysis performed by the server to the user.

[1343] "Means for direct communication with medical institutions and doctors" refers to methods and technologies that allow users to communicate directly with medical professionals as needed.

[1344] MODE FOR CARRYING OUT THE INVENTION

[1345] The present invention is a system that allows a user to input their own physical condition and symptoms and provides appropriate advice and responses based on the input. A specific embodiment of this system will be described below.

[1346] 1. Program Generation

[1347] The program for this system provides an interface for users to input their physical condition and symptoms. The interface can be implemented as a smartphone, PC application, or website. Users input their physical condition and symptoms through the interface using text or voice.

[1348] 2. Program processing explanation

[1349] When the user enters their physical condition and symptoms through the interface, the device sends the entered data to the server. The data is encrypted and sent securely. The server analyzes the received data. For text data, natural language processing (NLP) technology is used. Specifically, Google Cloud Natural Language API and IBM Watson Natural Language Understanding are used. For example, the symptom "headache" is extracted from the text "I have a headache."

[1350] The server then analyzes the voice data to identify the user's emotions. Using the Microsoft Azure Emotion API and Affectiva's SDK, the server analyzes emotions from the tone and phrasing of the voice. For example, if the user says, "I'm very tired today," the server can identify that the user is tired.

[1351] The server compiles these analysis results and sends them back to the device. The device then displays the received analysis results to the user. For example, it might say, "Headache detected. We recommend you take a rest." Or, it might say, "Fatigue detected. We recommend you take a sufficient rest."

[1352] 3. Examples of concrete examples and prompts

[1353] As a concrete example, consider the case where a user is using a smartphone app. The user opens the app, types in the text "I have a headache," and then types in the voice "I feel very tired today." The app sends this information to a server. The server analyzes the text using the Google Cloud Natural Language API and extracts the symptom "headache." It also analyzes the tone of the voice using the Microsoft Azure Emotion API and recognizes that the user is tired. The server compiles these analysis results and sends them back to the device. The device then displays the analysis results to the user, saying "Headache has been detected. It is recommended that you take a rest." It also displays "Fatigue has been detected. It is recommended that you take sufficient rest."

[1354] Example prompts to input to the generative AI model:

[1355] If a user types "I have a headache" and then speaks "I feel very tired today," how would the system parse this and what results would it return?

[1356] In this way, the system comprehensively grasps the user's physical condition and emotions and provides appropriate responses and advice.

[1357] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1358] Step 1:

[1359] The user inputs their physical condition and symptoms through the interface.

[1360] Specifically, the user opens the interface of a smartphone app or website, enters "I have a headache" as text, and then voice-inputs "I'm very tired today."

[1361] Input: Text and voice data of the user's condition and symptoms.

[1362] Output: The input text and audio data.

[1363] Step 2:

[1364] The terminal transmits the input data to the server.

[1365] Specifically, the terminal encrypts the text and voice data entered by the user and transmits them securely to the server.

[1366] Input: Text and voice data entered by the user.

[1367] Output: Encrypted text and audio data sent to the server.

[1368] Step 3:

[1369] The server receives the data and analyzes it using natural language processing (NLP) techniques.

[1370] Specifically, the server uses Google Cloud Natural Language API and IBM Watson Natural Language Understanding to analyze text data and extract the symptom "headache" from the text "I have a headache."

[1371] Input: The encrypted text data sent to the server.

[1372] Output: Parsed symptom data (e.g., "headache").

[1373] Step 4:

[1374] The server uses an emotion engine to recognize the user's emotion.

[1375] Specifically, the server uses the Microsoft Azure Emotion API and Affectiva's SDK to analyze voice data and recognize that the user is tired from the voice saying, "I'm very tired today."

[1376] Input: Encrypted audio data sent to the server.

[1377] Output: Parsed emotion data (e.g. "fatigue").

[1378] Step 5:

[1379] The server compiles the analysis results and sends them back to the device.

[1380] Specifically, the server integrates the analyzed symptom data and emotion data to generate appropriate advice for the user, such as a message like "Headache detected. We recommend you take a rest."

[1381] Input: Parsed symptom data and emotion data.

[1382] Output: Consolidated analysis results and advice messages.

[1383] Step 6:

[1384] The terminal displays the analysis results to the user.

[1385] Specifically, the device visually displays the analysis results received from the server to the user, for example, displaying a message such as "Headache detected. We recommend you take a rest."

[1386] Input: Analysis results and advice messages received from the server.

[1387] Output: Analysis results and advice messages displayed to the user.

[1388] (Application example 1)

[1389] Next, a description will be given of Application Example 1 of Form 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."

[1390] While conventional health management systems can grasp a user's physical condition and symptoms, they are unable to take into account the user's emotional state. This makes it difficult to properly monitor the user's mental health and take necessary measures. Furthermore, they lack the functionality to issue appropriate warnings when the user's emotions worsen, which can delay early response.

[1391] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, recipes, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for grasping the user's emotions using an emotion engine that recognizes the user's emotions, and means for issuing an alert when the user's emotions fall below a certain threshold. This makes it possible to comprehensively monitor not only the user's physical condition but also their emotional state, and to respond quickly if an abnormality is detected.

[1392] "Physical signs (symptoms)" are information that indicates the user's physical condition or abnormalities, such as specific symptoms such as headaches or fatigue.

[1393] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and evaluate a user's physical condition and nutritional status.

[1394] "Nutrition deficiency" refers to a state in which necessary nutrients are lacking or being consumed in excess, as determined based on the user's physical condition and symptoms.

[1395] "Essential nutrients" refers to the nutritional components of foods, supplements, dishes, etc. that are necessary to maintain the user's health.

[1396] An "emotion engine" is a technology for analyzing a user's emotional state, and refers to a system that recognizes emotions from the tone of voice and the wording of text.

[1397] The "threshold" is a reference value for evaluating the user's emotional state, and anything below this value is deemed abnormal.

[1398] "Means for issuing warnings" refers to a function that alerts the user or relevant parties when an abnormality is detected in the user's physical condition or emotional state.

[1399] "Direct communication with medical institutions and doctors" refers to the ability for users to communicate with medical professionals in real time as needed.

[1400] As an embodiment of the present invention, a system is provided that comprehensively monitors the physical condition and emotions of a user and takes necessary measures. A specific embodiment of this system will be described below.

[1401] System Configuration

[1402] The system consists of a device (smartphone or PC) equipped with an interface for understanding the user's physical condition and emotions, and a server for analyzing the data. The device includes a microphone for voice input and a keyboard for text input. The server analyzes the data using a generative AI model and an emotion engine.

[1403] Hardware and software used

[1404] Hardware: Smartphone, PC, microphone

[1405] Software: Python, SpeechRecognition library, TextBlob library, requests library

[1406] Data processing and calculation

[1407] 1. Enter your physical condition and symptoms:

[1408] Users input their physical condition and symptoms through the device's interface, either by text or voice input.

[1409] 2. Speech Recognition:

[1410] For voice input, the device uses the SpeechRecognition library to convert speech to text, which sends the user's voice data to the server as text data.

[1411] 3. Emotion analysis:

[1412] The server analyzes the sentiment of the text data using the TextBlob library. As a result, a sentiment score is generated. If this score falls below a certain threshold, the user's sentiment is considered to be negative.

[1413] 4. Issuance of a warning:

[1414] If the emotion score falls below a threshold, the server uses the requests library to issue a warning, which is then sent to the user's device.

[1415] Specific examples

[1416] For example, if a user types "I've been feeling depressed lately," the server analyzes this text data and calculates an emotion score. If the emotion score is low, the system notifies the user with "Warning: It seems you are feeling depressed."

[1417] Prompt Sentence Examples

[1418] An example of a prompt to input to a generative AI model is as follows:

[1419] If a user types "I've been feeling depressed lately," write a Python program that analyzes the sentiment score and issues a warning if the score is low.

[1420] In this way, it is possible to monitor the user's physical condition and emotions in real time and respond quickly if an abnormality is detected.

[1421] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1422] Step 1:

[1423] The user inputs their physical condition and symptoms. The input method is either text input or voice input. The input data is sent to the server through the device interface. Specifically, the user inputs information such as "I have a headache" or "I've been feeling depressed lately."

[1424] Input: Text or voice data of the user's physical condition and symptoms

[1425] Output: Text data from the terminal to the server

[1426] Step 2:

[1427] In the case of voice input, the device converts the voice to text using the SpeechRecognition library. This process sends the user's voice data to the server as text data. Specifically, the voice data collected by the microphone is converted to text using Google's speech recognition API.

[1428] Input: User's voice data

[1429] Output: Text data

[1430] Step 3:

[1431] The server uses the TextBlob library to analyze the received text data. The TextBlob library analyzes the sentiment of the text data and generates a sentiment score. Specifically, the text data is input into a sentiment analysis model to calculate a positive or negative sentiment score.

[1432] Input: Text data

[1433] Output: Sentiment score

[1434] Step 4:

[1435] The server evaluates the generated emotion scores and issues a warning if the score falls below a certain threshold. Specifically, if the emotion score is -0.5 or less, a warning message is sent to the user's device using the requests library.

[1436] Input: Sentiment score

[1437] Output: Warning message

[1438] Step 5:

[1439] The user's device receives the warning message sent from the server and notifies the user. Specifically, the notification function of the smartphone is used to display the message "Warning: Your emotions seem to be depressed."

[1440] Input: warning message

[1441] Output: User notification

[1442] In this way, it is possible to monitor the user's physical condition and emotions in real time and respond quickly if an abnormality is detected.

[1443] Example 2

[1444] Next, a description will be given of Example 2 of Form 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."

[1445] In modern society, it is important to consume appropriate nutrients based on individual physical condition and emotions, but it is difficult for users to understand and appropriately consume nutrients that are appropriate for their own physical condition and emotions. Furthermore, there is a lack of ways for users to quickly and accurately obtain information to select appropriate nutrients based on their physical condition and emotions. Furthermore, there is a need for a way for users to easily purchase recommended nutrients and, if necessary, to directly communicate with a medical institution or doctor.

[1446] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1447] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies or excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the nutritional deficiencies or excesses, means for directly purchasing the recommended nutrients, means for directly communicating with a medical institution or doctor as needed, means for utilizing generative AI to recommend nutrients that will help improve the user's emotions based on the user's emotions, and means for displaying recommended nutrient information based on the emotions to the user. This enables the user to quickly and accurately grasp appropriate nutrients based on their physical condition and emotions and take them appropriately.

[1448] "Physical signs (symptoms)" is information that a user inputs to indicate their physical condition or health status.

[1449] "Generative AI" is an artificial intelligence technology that refers to medical information and nutrition databases on the Internet and identifies appropriate nutrients based on the user's physical condition and emotions.

[1450] "Excess or deficiency of nutrition" refers to a state in which the current amount of nutritional intake is inappropriate based on the user's physical condition or emotions.

[1451] "Necessary nutrients (foods, supplements, dishes, etc.)" refers to foods, supplements, dishes, etc. that contain the nutrients necessary to maintain or improve health, and are recommended based on the user's physical condition and emotions.

[1452] "Recommendation methods" are methods that suggest to users the necessary nutrients identified by the generative AI.

[1453] "Direct purchase methods" are methods that allow users to directly purchase foods or supplements containing the recommended nutrients, either online or offline.

[1454] "Means for directly communicating with medical institutions and doctors" refers to a method by which a user can directly communicate with medical institutions and doctors as needed.

[1455] "Means of utilizing generative AI based on emotions" refers to a method in which a generative AI uses a user's emotional state as input data to identify the appropriate nutrients to improve that emotion.

[1456] The "means of displaying emotion-based nutrient recommendation information to the user" is a method of visually providing the user with information on nutrients that are useful for improving emotions, as identified by the generative AI.

[1457] MODE FOR CARRYING OUT THE INVENTION

[1458] The present invention is a system for recommending appropriate nutrients based on a user's physical condition and emotions. Specific embodiments of this system will be described below.

[1459] System configuration

[1460] This system consists of three main components: a server, a device, and a user. The server analyzes data using a generative AI model to identify appropriate nutrients. The device receives input from the user and communicates with the server. The user inputs their physical condition and emotions and receives information on recommended nutrients.

[1461] Hardware and software used

[1462] Server: Use a server machine equipped with a high-performance processor and large memory capacity. Use a machine learning framework such as TensorFlow or PyTorch to run the generative AI model.

[1463] Terminal: User devices such as smartphones, tablets, and PCs are used to access the system through dedicated applications or web browsers.

[1464] Databases: Consult online medical and nutrition databases (e.g., PubMed, USDA Nutrient Database).

[1465] Program processing

[1466] The server receives data on physical condition and emotions input by the user. This data is provided by the user through an input form on the device. The server uses the generative AI model based on the received data to search online medical information and nutrition databases. For example, if the user inputs "I have a headache," the server uses the generative AI model to determine that the user may be deficient in magnesium or vitamin B2.

[1467] The server generates nutritional recommendations for the user based on the analysis results obtained using the generative AI model. For example, it generates specific advice such as, "We recommend that you take foods and supplements containing magnesium and vitamin B2." The generated recommendations are sent from the server to the device and displayed to the user.

[1468] Specific examples

[1469] The user types "I have a headache" into the device. The device sends that data to a server, which uses a generative AI model to search online medical and nutrition databases and determine that the patient may be deficient in magnesium or vitamin B2. The information is then sent back to the device and displayed to the user.

[1470] Example prompt sentence:

[1471] If a user types in "I have a headache," use a generative AI model to determine which nutrients they may be deficient in.

[1472] Or, if a user types "I'm feeling stressed" into their device, the device sends that data to a server, which uses a generative AI model to determine that B vitamins and magnesium can help relieve stress. That information is sent back to the device and displayed to the user.

[1473] Example prompt sentence:

[1474] If a user types in "I'm feeling stressed," use a generative AI model to determine which nutrients would help relieve stress.

[1475] In this way, the server, terminal, and user work together to create a system that recommends appropriate nutrients based on the user's physical condition and emotions.

[1476] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1477] Program processing flow

[1478] Step 1: User Input

[1479] The user inputs their physical condition and emotions into an input form on the device. For example, the user inputs "I have a headache." This input data is sent to the server through the device interface.

[1480] Input: Physical condition or emotional data entered by the user into an input form (e.g., "I have a headache").

[1481] Output: The input data is sent to the server.

[1482] Step 2: Sending data

[1483] The terminal transmits the data on physical condition and emotions input by the user to the server, which receives the transmitted data and proceeds to the next processing step.

[1484] Input: Physical and emotional data entered by the user.

[1485] Output: The data received by the server.

[1486] Step 3: Analyze the data

[1487] The server analyzes the received data. This analysis is performed using a generative AI model. The generative AI model refers to online medical information and nutrition databases to identify the appropriate nutrients for the user's physical condition and emotions. For example, if the user says "I have a headache," the model might determine that the user is likely deficient in magnesium or vitamin B2.

[1488] Input: User's physical condition and emotional state data received by the server.

[1489] Output: Analysis results from the generative AI model (e.g., possible deficiency of magnesium or vitamin B2).

[1490] Step 4: Generate recommendations

[1491] The server generates nutritional recommendations for the user based on the analysis results obtained using the generative AI model. For example, it generates specific advice such as, "We recommend that you take foods and supplements containing magnesium and vitamin B2."

[1492] Input: Analysis results from a generative AI model.

[1493] Output: Nutrition recommendations for the user.

[1494] Step 5: Submit your recommendations

[1495] The server transmits the generated recommendation information to the terminal, which receives the information and displays it to the user.

[1496] Input: Nutrition recommendations for the user.

[1497] Output: The recommendations received by the device.

[1498] Step 6: View recommendations

[1499] The device displays the recommended information received from the server to the user. The user can select appropriate foods and supplements based on the displayed information. For example, the device may display a message saying, "We recommend that you take foods and supplements containing magnesium and vitamin B2."

[1500] Input: Recommendations received by the device.

[1501] Output: The recommendation displayed to the user.

[1502] Specific actions

[1503] Step 1: User Input

[1504] The user accesses a dedicated application or website using a device such as a smartphone or PC, enters "I have a headache" into the input form, and clicks the submit button.

[1505] Step 2: Sending data

[1506] The terminal sends the data entered by the user, such as "I have a headache," to the server using the HTTPS protocol. The sent data is received by the server.

[1507] Step 3: Analyze the data

[1508] The server then calls a generative AI model to analyze the received data. The generative AI model consults online medical information and nutrition databases (e.g., PubMed and the USDA Nutrient Database) and determines that the symptom "headache" may be due to a deficiency of magnesium or vitamin B2.

[1509] Step 4: Generate recommendations

[1510] The server generates specific nutritional recommendations for the user based on the analysis results obtained from the generative AI model, such as "We recommend taking foods and supplements containing magnesium and vitamin B2."

[1511] Step 5: Submit your recommendations

[1512] The server transmits the generated recommendation information to the terminal, which receives the information.

[1513] Step 6: View recommendations

[1514] The device displays the recommended information received from the server to the user. The user can select appropriate foods and supplements based on the displayed information. For example, the device may display a message saying, "We recommend that you take foods and supplements containing magnesium and vitamin B2."

[1515] (Application example 2)

[1516] Next, a description will be given of Application Example 2 of Form 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."

[1517] In modern society, it is difficult to understand the appropriate nutrients based on individual physical condition and symptoms and to select foods and supplements based on that. It is also difficult to find a place where you can quickly purchase products containing the recommended nutrients. Furthermore, there is a lack of means to directly communicate with medical institutions or doctors when necessary, making comprehensive health management difficult.

[1518] 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.

[1519] In this invention, the server includes a means for identifying bodily signs (symptoms), a means for identifying nutritional deficiencies or excesses based on the bodily signs (symptoms) using generative AI, a means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies or excesses, a means for directly purchasing the recommended nutrients, a means for directly communicating with a medical institution or doctor as needed, and a means for guiding users to stores selling products containing the recommended nutrients. This allows users to identify appropriate nutrients based on their physical condition and symptoms and quickly find places where they can purchase them. Furthermore, the ability to directly communicate with a medical institution or doctor as needed facilitates comprehensive health management.

[1520] "Physical signs (symptoms)" are specific symptoms or sensations that indicate the user's physical condition or health status.

[1521] "Generative AI" is an artificial intelligence that obtains information from medical and nutritional databases on the Internet and recommends appropriate nutrients based on the user's physical condition and symptoms.

[1522] "Nutrient deficiency" refers to nutrients that are lacking or in excess in the body, as determined based on the user's physical condition and symptoms.

[1523] "Essential nutrients (foods, supplements, meals, etc.)" refers to foods, supplements, or meals containing nutrients necessary for maintaining or improving health that are recommended based on the user's physical condition and symptoms.

[1524] "Direct purchasing of nutrient recommendations" means a method that enables a user to quickly purchase a product containing the nutrient recommendations.

[1525] "Means for communicating directly with medical institutions and doctors" refers to means by which users can communicate directly with medical institutions and doctors as needed.

[1526] "Store navigation" means a means that enables a user to find stores that sell products containing the nutrient recommendations.

[1527] The system for implementing this invention recommends appropriate nutrients based on the user's physical condition and symptoms, and supports purchasing in physical stores. Specific embodiments of the system are described below.

[1528] System configuration

[1529] The system consists of the following main components:

[1530] 1. User device: A device such as a smartphone or tablet that provides an interface for users to input their physical condition and symptoms.

[1531] 2. Generative AI model: Obtains information from online medical and nutrition databases and recommends appropriate nutrients based on the user's physical condition and symptoms.

[1532] 3. Database: Stores information about stores that sell products containing the recommended nutrients.

[1533] 4. Communication module: Handles data communication between the user device, the generative AI model, and the database.

[1534] Program processing

[1535] Hardware and Software

[1536] Hardware: smartphones, tablets, servers

[1537] Software: Python, OpenAI API, database management system (e.g., MySQL)

[1538] Data processing and calculation

[1539] 1. User device: The user inputs their physical condition and symptoms. For example, they input "I have a headache."

[1540] 2. Generative AI model: Receives user input, generates a prompt, and sends it to the OpenAI API. An example of a prompt is as follows:

[1541] "If a user has a headache, what are the appropriate nutrients?"

[1542] 3. Generative AI model: receives the response from the OpenAI API and identifies the appropriate nutrients, for example, determining that "you may be deficient in magnesium or vitamin B2."

[1543] 4. Database: Search for stores that sell products containing the recommended nutrients. For example, provide information such as "Products containing magnesium can be purchased at Drugstore A."

[1544] 5. User device: Display recommended nutrients and store information to the user.

[1545] Specific examples

[1546] If a user types in "I have a headache," the generative AI model will determine that "you may be deficient in magnesium or vitamin B2," and will then direct them to stores that sell products containing these nutrients. For example, it will display "Products containing magnesium can be purchased at Drugstore A."

[1547] In this way, users can identify the right nutrients based on their physical condition and symptoms, quickly find where to buy them, and, if necessary, communicate directly with a medical institution or doctor, making overall health management easier.

[1548] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1549] Step 1:

[1550] The user inputs their physical condition and symptoms on the user device. For example, they input "I have a headache."

[1551] Input: Text input of user's condition and symptoms

[1552] Output: Input data on physical condition and symptoms

[1553] Specific operation: On the smartphone application screen, the user enters symptoms in the text box and presses the send button.

[1554] Step 2:

[1555] The server receives the entered data on physical condition and symptoms, generates a prompt sentence, and sends it to the generative AI model.

[1556] Input: User's physical condition and symptoms data

[1557] Output: Prompt to send to the generative AI model

[1558] Specific behavior: The server generates a prompt sentence, "If the user has a headache, what are the appropriate nutrients?" and sends it to the OpenAI API.

[1559] Step 3:

[1560] The generative AI model identifies the appropriate nutrients based on the prompt and returns a response to the server.

[1561] Input: prompt statement

[1562] Output: Pertinent nutrition information

[1563] What it does: The OpenAI API parses the prompt, generates a response saying "You may be deficient in magnesium or vitamin B2," and returns it to the server.

[1564] Step 4:

[1565] The server receives the response from the generative AI model and searches its database for stores that sell products containing the recommended nutrients.

[1566] Input: Appropriate nutrition information

[1567] Output: Information about stores that sell products containing the recommended nutrients

[1568] Specific operation: The server retrieves information from the database that "products containing magnesium can be purchased at drugstore A."

[1569] Step 5:

[1570] The server sends the recommended nutrients and information on where they can be purchased to the user's device.

[1571] Input: Store information that sells products containing the recommended nutrients

[1572] Output: Information to display on the user's terminal

[1573] Specific operation: The server sends information to the user's terminal that "products containing magnesium can be purchased at Drugstore A."

[1574] Step 6:

[1575] The user's device displays recommended nutrients and information on where they can be purchased.

[1576] Input: Information sent from the server

[1577] Output: Information displayed to the user

[1578] Specific operation: The smartphone application screen displays the information, "Products containing magnesium can be purchased at Drugstore A."

[1579] Example 3

[1580] Next, a description will be given of Example 3 of Form Example 3. 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."

[1581] In modern society, it is important to consume appropriate nutrients according to individual health conditions and symptoms. However, it is difficult for ordinary people to accurately understand their nutritional needs and select appropriate foods and supplements. Furthermore, there are limited ways to quickly access medical institutions and doctors if their health does not improve. This can lead to inadequate health management, which can worsen or chronicate symptoms. Furthermore, purchasing foods and supplements online is complicated, resulting in poor user convenience.

[1582] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1583] In this invention, the server includes a means for identifying bodily signs (symptoms), a means for identifying nutritional deficiencies and excesses based on the bodily signs (symptoms) using generative AI, a means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, a means for directly purchasing the recommended nutrients, a means for directly communicating with a medical institution or doctor if necessary, a means for analyzing data based on the bodily signs (symptoms) using natural language processing technology, a means for providing links to purchase foods and supplements containing the recommended nutrients, and a means for introducing a medical institution or doctor and arranging an online consultation if the bodily signs (symptoms) do not improve. This allows users to easily identify the appropriate nutrients for their health condition and quickly purchase the necessary foods and supplements. Furthermore, if their health condition does not improve, they can quickly access a medical institution or doctor and receive appropriate medical care.

[1584] "Physical signs (symptoms)" refer to physical abnormalities or discomforts experienced by the user, and specifically include symptoms such as headaches, fatigue, and stomach aches.

[1585] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and generate information for specific purposes.

[1586] "Nutrient deficiency or oversupply" refers to an excess or deficiency of a nutrient required based on the user's health condition or symptoms.

[1587] "Necessary nutrients (foods, supplements, meals, etc.)" refers to foods, supplements, or meals containing nutrients recommended based on the user's health condition and symptoms.

[1588] "Direct means to purchase nutrient recommendations" refers to a feature that provides a link or interface for users to purchase recommended foods or supplements directly online.

[1589] "Means for communicating directly with medical institutions and doctors" refers to a function that allows users to communicate directly with medical institutions and doctors online as needed.

[1590] "Natural language processing technology" refers to technology that enables computers to understand and analyze human language, and specifically includes text analysis and keyword extraction.

[1591] "Purchase Link" refers to a URL or button that allows users to purchase the recommended food or supplement online.

[1592] "Means for arranging online consultations" refers to the function that allows a user to book and arrange an online consultation with an appropriate medical institution or doctor if their condition does not improve.

[1593] The present invention is a system that recommends necessary nutrients based on the user's health condition and symptoms, and also provides a function to purchase foods and supplements containing those nutrients online. It also provides a function to directly communicate with medical institutions and doctors as needed.

[1594] System configuration

[1595] This system consists of the following main components:

[1596] 1. User device: A device such as a smartphone or computer that allows users to input their health status and symptoms.

[1597] 2. Server: Receives input data from the user, analyzes it, identifies necessary nutrients, and recommends foods and supplements.

[1598] 3. Generative AI model: Artificial intelligence technology that analyzes user input data and identifies necessary nutrients.

[1599] 4. Natural language processing technology: Technology for analyzing user input data. Specifically, it uses the Python NLTK library, etc.

[1600] 5. Database: A database for storing food and nutrient information.

[1601] 6. Online Purchase Links: Links to purchase the recommended foods and supplements online.

[1602] 7. Medical institution referral function: If your condition does not improve, this function will refer you to an appropriate medical institution or doctor and arrange an online consultation.

[1603] System Operation

[1604] User terminal

[1605] Users use their smartphones or computers to input their health conditions and symptoms. For example, they might input "I have a headache." The input data is then sent from the device to the server.

[1606] server

[1607] The server analyzes the data received from the user using natural language processing technology. Specifically, it uses Python's NLTK library to analyze the text and extract relevant keywords. For example, it extracts the keyword "headache" from the input "I have a headache."

[1608] The server then uses a generative AI model to identify necessary nutrients based on the extracted keywords—for example, magnesium and vitamin B2, which are associated with headaches—by referencing a pre-built nutrient database.

[1609] The server then selects appropriate foods and supplements based on the identified nutrients, such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2, using a food database.

[1610] Generate and send a recommendation list

[1611] The server generates a list of selected foods and supplements and sends it to the user's device, including the food's name, nutrient content, and a link to purchase it.

[1612] User operations

[1613] The user checks the recommendation list on the device and sees that bananas, almonds, and liver are recommended. The user clicks on the provided purchase link to purchase food or supplements online. For example, the user is redirected to a purchase page on an e-commerce site and purchases bananas and almonds.

[1614] Medical institution introduction function

[1615] If the user's condition does not improve, the device application can use a function to refer them to a medical institution or doctor. For example, they can be referred to a psychosomatic or psychiatric medical institution and arrange an online consultation.

[1616] Examples of concrete examples and prompts

[1617] Specific examples

[1618] 1. The user types, "I have a headache."

[1619] 2. The server recommends foods high in magnesium and vitamin B2.

[1620] 3. The server recommends bananas, almonds, and liver and provides recipes for dishes that include them and links to purchase them online.

[1621] 4. The user uses the provided link to purchase the recommended food.

[1622] 5. If the user's condition does not improve, the server will refer them to a psychosomatic or psychiatric medical institution and arrange for an online consultation.

[1623] Prompt Sentence Examples

[1624] "What foods and supplements do you recommend for headaches? Also, provide links to buy them online."

[1625] "If my condition does not improve, please introduce me to an appropriate medical institution or doctor." The flow of the identification process in the third embodiment will be described with reference to FIG.

[1626] Step 1:

[1627] The user inputs their health condition and symptoms.

[1628] The user opens the application on their smartphone or computer and inputs their health condition and symptoms. For example, they might input "I have a headache." The input data is in text format, and is sent from the device to the server by pressing the send button.

[1629] Input: User's health condition or symptoms (e.g., "I have a headache")

[1630] Output: The input data is sent to the server.

[1631] Step 2:

[1632] The terminal sends the input data to the server.

[1633] The terminal encrypts the data entered by the user and sends it to the server using the HTTPS protocol, ensuring the security of the data.

[1634] Input: User-entered health and symptom data

[1635] Output: The encrypted data is sent to the server.

[1636] Step 3:

[1637] The server parses the input data.

[1638] The server analyzes the received data using natural language processing technology. Specifically, it uses Python's NLTK library to analyze the text and extract relevant keywords. For example, it extracts the keyword "headache" from the input "I have a headache."

[1639] Input: Encrypted user health and symptom data

[1640] Output: Parsed keywords (e.g. "headache")

[1641] Step 4:

[1642] Identify the nutrients your server needs

[1643] The server identifies the necessary nutrients based on the analysis results. For example, it identifies magnesium and vitamin B2 as nutrients related to headaches. This process refers to a pre-built nutrient database.

[1644] Input: Parsed keyword (e.g. "headache")

[1645] Output: Identified required nutrients (e.g., magnesium, vitamin B2)

[1646] Step 5:

[1647] Select foods and supplements recommended by the server

[1648] The server then selects appropriate foods and supplements based on the identified nutrients, such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2, using a food database.

[1649] Input: Identified nutrient needs (e.g., magnesium, vitamin B2)

[1650] Output: A list of recommended foods and supplements (e.g. bananas, almonds, liver)

[1651] Step 6:

[1652] The server sends the recommendation list to the device.

[1653] The server generates a list of selected foods and supplements and sends it to the device, including the name of the food, its nutrient content, and a link to purchase it.

[1654] Input: A list of recommended foods and supplements

[1655] Output: The recommendation list is sent to the terminal.

[1656] Step 7:

[1657] The user reviews the recommendations list

[1658] The user checks the recommendation list on the device, and sees that, for example, bananas, almonds, and liver are recommended.

[1659] Input: Recommendation list

[1660] Output: User reviews the recommendation list

[1661] Step 8:

[1662] Users purchase food and supplements online

[1663] The user clicks on a purchase link included in the recommendation list to purchase food or supplements online. For example, they are taken to a purchase page on an e-commerce site to purchase bananas or almonds.

[1664] Input: Recommended List Purchase Link

[1665] Output: User purchases food and supplements

[1666] Step 9:

[1667] If the user's condition does not improve, the function to refer them to a medical institution or doctor can be used.

[1668] If the user's condition does not improve, the device application can use a function to refer them to a medical institution or doctor. For example, they can be referred to a psychosomatic or psychiatric medical institution and arrange an online consultation.

[1669] Input: User's health information

[1670] Output: Referrals to medical institutions and doctors, and arrangements for online consultations

[1671] (Application example 3)

[1672] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1673] In modern society, it is important to take in appropriate nutrients based on individual physical condition and emotions, but it is difficult for users to select appropriate foods and supplements based on their own symptoms and emotions. Furthermore, the lack of direct access to medical institutions and doctors when needed makes it difficult to receive prompt and appropriate medical support. Furthermore, the lack of an easy way to purchase recommended nutrients creates a problem of inconvenience for users.

[1674] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1675] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with medical institutions or doctors as needed, means for utilizing an emotion engine to recommend appropriate medical institutions or doctors based on the bodily signs (symptoms), and means for generating links to purchase the recommended nutrients. This allows users to easily consume appropriate nutrients based on their symptoms and emotions, as well as receive prompt and appropriate medical support as needed.

[1676] "Physical signs (symptoms)" are indicators that show the user's physical condition or discomfort.

[1677] "Generative AI" is a system that uses artificial intelligence technology to analyze data and generate appropriate information.

[1678] "Nutrition deficiency" refers to nutrients that are lacking in the user's body or that are being consumed in excess.

[1679] "Essential nutrients" refers to foods, supplements, dishes, etc. that are recommended for users to consume in order to improve their health.

[1680] A "recommendation means" is a method or system for suggesting appropriate nutrients and medical institutions to a user.

[1681] A "direct purchasing method" is a method or system that allows users to easily purchase recommended nutrients.

[1682] "Means for direct communication with medical institutions and doctors" refers to methods and systems that allow users to communicate directly with medical professionals as needed.

[1683] The "Emotion Engine" is an artificial intelligence technology that analyzes the user's emotional state and suggests appropriate responses based on that.

[1684] A "means for generating a purchase link" is a method or system that creates a link for a user to purchase the recommended nutrients online.

[1685] The system for implementing this invention identifies the user's physical signs (symptoms) and, based on those signs, utilizes generative AI to identify nutritional deficiencies and excesses. Furthermore, it recommends necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, and generates links to directly purchase the recommended nutrients. It also provides a means for direct communication with medical institutions and doctors as needed, and uses an emotion engine to recommend appropriate medical institutions and doctors.

[1686] 1. System Program

[1687] This system is realized using the following hardware and software.

[1688] Hardware: Smartphone

[1689] Software: Python, requests library

[1690] 2. Program Processing

[1691] The server receives the user's physical signs (symptoms) and uses generative AI to identify nutritional deficiencies and excesses. It then recommends necessary nutrients based on the nutritional deficiencies and excesses, and generates links to purchase the recommended nutrients. It also analyzes the user's emotional state and recommends appropriate medical institutions and doctors as needed.

[1692] For example, if a user types "I have a headache," the system will recommend bananas, almonds, and liver and provide links to buy them. If a user types "severe depression," the system will recommend psychosomatic or psychiatric care.

[1693] 3. Examples of concrete examples and prompts

[1694] For example, if a user types "I have a headache," the system will recommend bananas, almonds, and liver and provide links to buy them. If a user types "severe depression," the system will recommend psychosomatic or psychiatric care.

[1695] Prompt Sentence Examples

[1696] If a user types "I have a headache," the system will recommend bananas, almonds, and liver and provide links to buy them. If a user types "severe depression," the system will recommend psychosomatic or psychiatric care.

[1697] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1698] Step 1:

[1699] The user inputs physical signs (symptoms) using a smartphone device.

[1700] Input: Symptoms entered by the user (e.g., "I have a headache")

[1701] Output: Input symptom data

[1702] Specific operation: The user starts the application and enters the symptoms in text format into the symptom input screen.

[1703] Step 2:

[1704] The server receives the input symptom data and uses a generative AI model to analyze nutritional deficiencies and excesses.

[1705] Input: Symptom data

[1706] Output: Nutritional data that is insufficient or excessive (e.g. magnesium deficiency)

[1707] Specific operation: The server passes symptom data to the generative AI model, which then retrieves relevant information from the internet and analyzes nutritional deficiencies and excesses.

[1708] Step 3:

[1709] The server recommends necessary nutrients (foods, supplements, dishes, etc.) based on nutritional data on excess and deficiency.

[1710] Input: Excessive or insufficient nutrition data

[1711] Output: Recommended nutrient list (e.g. bananas, almonds, liver)

[1712] Specific operation: The server searches a nutrient database based on the nutritional data of excess and deficiency, and lists appropriate foods and supplements.

[1713] Step 4:

[1714] The server generates links to purchase the recommended nutrients.

[1715] Input: Recommended Nutrition List

[1716] Output: A list of purchase links (e.g. https: / / example.com / purchase / banana)

[1717] Specific operation: Based on the recommended nutrient list, the server generates purchase links for each nutrient and compiles them into a list.

[1718] Step 5:

[1719] The server sends the user a list of recommended nutrients and a list of purchase links.

[1720] Input: Recommended nutrition list, purchase link list

[1721] Output: Nutrition recommendations and purchase links displayed on the user's smartphone

[1722] Specific operation: The server sends a list of recommended nutrients and a list of purchase links to the user's smartphone and displays them on the application screen.

[1723] Step 6:

[1724] Users can send requests to speak directly with medical institutions or doctors as needed.

[1725] Input: User request (e.g., "I want to speak to a doctor")

[1726] Output: Links to medical institutions and doctor conversations

[1727] What happens: The user selects an option within the application and submits a request to speak directly with a healthcare provider or doctor.

[1728] Step 7:

[1729] The server uses an emotion engine to analyze the user's emotional state and recommend appropriate medical institutions and doctors.

[1730] Input: User emotion data (e.g., "severe depression")

[1731] Output: Recommended medical institutions and doctors list (e.g., psychosomatic medicine, psychiatry)

[1732] Specific operation: The server passes the user's emotional data to the emotion engine, which then lists appropriate medical institutions and doctors.

[1733] Step 8:

[1734] The server sends the user a list of recommended medical institutions and doctors.

[1735] Input: Recommended medical institutions and doctor list

[1736] Output: A list of medical institutions and doctors displayed on the user's smartphone

[1737] Specific operation: The server sends a list of recommended medical institutions and doctors to the user's smartphone and displays it on the application screen.

[1738] 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.

[1739] 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> ) 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.

[1740] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1741] 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.

[1742] [Third embodiment]

[1743] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1744] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1745] 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).

[1746] 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.

[1747] 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.

[1748] 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).

[1749] 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.

[1750] 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.

[1751] 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.

[1752] 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.

[1753] 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.

[1754] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1755] "Example 1"

[1756] The system of the present invention is equipped with an interface that allows users to input their own physical condition and symptoms. This interface can be realized, for example, through a smartphone, a PC application, or a website. The user inputs specific details about their physical condition and symptoms. For example, the user can input information such as "I have a headache" or "I get tired easily."

[1757] "Example 2"

[1758] Next, the system of the present invention utilizes generative AI based on the input of the user's physical condition and symptoms. This AI identifies the appropriate nutrients for the user's physical condition and symptoms from online medical information and nutrition databases. For example, if the user says "I have a headache," it determines that the user may be deficient in magnesium or vitamin B2.

[1759] "Example 3"

[1760] Based on the nutrients identified, the system of the present invention recommends foods, supplements, and dishes containing the necessary nutrients. For example, for a user who has a headache, it would recommend foods such as bananas and almonds, which are rich in magnesium, and liver, which is rich in vitamin B2.

[1761] "Example 4"

[1762] Furthermore, the system of the present invention provides a function to directly purchase the recommended foods and supplements. For example, it provides recipes containing recommended bananas, almonds, and liver along with links to purchase these ingredients online.

[1763] "Example 5"

[1764] The system of the present invention also provides a function to directly communicate with medical institutions or doctors as needed. For example, if your condition does not improve or if certain symptoms persist, the system will refer you to a specialized medical institution or doctor and arrange an online consultation.

[1765] The processing flow of each embodiment will be described below.

[1766] "Example 1"

[1767] Step 1: The user accesses the system of the present invention and specifically inputs their physical condition and symptoms. For example, they input information such as "I have a headache" or "I get tired easily."

[1768] Step 2: The system of the present invention uses generative AI to identify appropriate nutrients based on the input physical condition and symptoms. This AI identifies appropriate nutrients for the user's physical condition and symptoms from online medical information and nutrition databases.

[1769] Step 3: Based on the identified nutrients, the system of the present invention recommends foods, supplements, and recipes that contain the necessary nutrients.

[1770] Step 4: The system of the present invention provides the ability to directly purchase the recommended foods and supplements. Along with recipes containing the recommended bananas, almonds, and liver, it provides links to purchase these ingredients online.

[1771] Step 5: The system of the present invention also provides the ability to directly communicate with medical institutions or doctors as needed. If your condition does not improve or if certain symptoms persist, the system will refer you to a specialized medical institution or doctor and arrange an online consultation.

[1772] Example 1

[1773] Next, a description will be given of Example 1 of Form 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."

[1774] In modern society, many people need to quickly and accurately understand information about their own physical condition and symptoms, and receive appropriate advice. However, conventional systems have difficulty providing appropriate advice based on the physical condition and symptoms entered by the user, and do not adequately recommend necessary nutrients or collaborate with medical institutions. This makes it difficult for users to properly manage their own health condition.

[1775] 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.

[1776] In this invention, the server includes means for inputting physical signs (symptoms), means for transmitting the physical signs (symptoms) to the server, means for generating advice using a generative AI model based on the physical signs (symptoms), means for transmitting the generated advice to a terminal, means for displaying the generated advice on the terminal, means for recommending necessary nutrients (foods, supplements, dishes, etc.) based on the generated advice, means for directly purchasing the recommended nutrients, and means for directly communicating with a medical institution or doctor as needed. This allows the user to quickly receive appropriate advice based on their own physical condition and symptoms, and also enables smooth recommendation of necessary nutrients and collaboration with medical institutions.

[1777] "Physical signs (symptoms)" refer to any abnormalities or discomforts that a user feels regarding their physical condition or health.

[1778] "Input means" refers to the interface through which the user inputs physical signs (symptoms) into the system. Specifically, this includes smartphone and PC applications, websites, etc.

[1779] "Means of transmission" refers to the communication means used to send the physical signs (symptoms) entered by the user to the server. Specifically, this includes HTTP requests using an Internet connection.

[1780] "Generative AI models" refer to artificial intelligence models that generate appropriate advice based on user input. Specifically, they include generative AI models that use natural language processing technology.

[1781] "Means for generating advice" refers to the process of using a generative AI model to generate advice based on the user's physical signs (symptoms).

[1782] "Means for sending to the terminal" refers to a communication means for sending the generated advice to the user's terminal. Specifically, this includes HTTP responses, etc.

[1783] "Displaying means" refers to an interface for visually displaying the generated advice to the user on the device, including, for example, a UI component of an application or an element of a web page.

[1784] "Means for recommending necessary nutrients" refers to a process for recommending necessary nutrients (foods, supplements, dishes, etc.) to a user based on the generated advice.

[1785] "Direct purchasing means" refers to an interface through which a user can directly purchase the recommended nutrients, specifically including online shopping functionality.

[1786] "Means for directly communicating with medical institutions or doctors" refers to means by which users can directly communicate with medical institutions or doctors as needed. Specifically, this includes video calls and chat functions.

[1787] MODE FOR CARRYING OUT THE INVENTION

[1788] This invention is a system that allows users to input their own physical condition and symptoms, and then uses a generative AI model to provide appropriate advice based on that information. This system can be implemented via smartphone or PC applications, websites, etc.

[1789] User Input

[1790] Users input their physical condition and symptoms using a smartphone or PC application or website. For example, a user might enter, "I've been having frequent headaches lately." This input is done through a text box or form in the application.

[1791] Sending data

[1792] The device sends the information about the user's physical condition and symptoms to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is encoded in JSON format.

[1793] Receiving and analyzing data

[1794] The server receives the data sent from the device. The server analyzes the received data and extracts the user's input. For example, the server analyzes the text "I've been having frequent headaches lately" and passes it to the next processing step.

[1795] Advice generation using generative AI models

[1796] The server uses a generative AI model (e.g., a generative AI model using natural language processing technology) to generate advice based on the user's input. Specifically, the server inputs the following prompt sentence into the generative AI model:

[1797] User input: I've been having a lot of headaches lately.

[1798] Prompt for generative AI model: User inputs "I've been having a lot of headaches lately." Please provide appropriate advice.

[1799] The generative AI model generates advice based on this prompt, for example, "We recommend you drink plenty of fluids. If symptoms persist, consult your doctor."

[1800] Sending the results

[1801] The server sends the advice generated by the generative AI model to the terminal. Specifically, the server encodes the generated advice in JSON format and sends it as an HTTP response.

[1802] Displaying the results

[1803] The device displays the advice received from the server to the user. Specifically, the device displays the generated advice using the application's UI components (e.g., a text view or a popup message). The user can view the advice through the application.

[1804] Recommendations for necessary nutrients

[1805] Based on the generated advice, the server recommends the necessary nutrients (foods, supplements, dishes, etc.) to the user. For example, it makes a specific recommendation such as "We recommend that you consume foods that are high in vitamin C."

[1806] Direct purchase of nutrients

[1807] Users can directly purchase the recommended nutrients, specifically by using the online shopping function through the application or website to purchase the recommended foods and supplements.

[1808] Collaboration with medical institutions and doctors

[1809] If necessary, users can talk directly to medical institutions and doctors, specifically by using video calls and chat functions to communicate with doctors in real time.

[1810] In this way, the system of the present invention allows users to quickly receive appropriate advice based on their own physical condition and symptoms, and also makes it possible to smoothly recommend necessary nutrients and collaborate with medical institutions.

[1811] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1812] Program processing flow

[1813] Step 1: User Input

[1814] Users input their physical condition and symptoms using a smartphone or PC application or website. For example, a user might enter, "I've been having frequent headaches lately." This input is done through a text box or form in the application.

[1815] Input: Text data of the user's physical condition and symptoms

[1816] Output: The input text data

[1817] Step 2: Sending data

[1818] The device sends the information about the user's physical condition and symptoms to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is encoded in JSON format.

[1819] Input: Text data entered by the user

[1820] Output: JSON formatted data sent to the server

[1821] Step 3: Receiving and analyzing data

[1822] The server receives the data sent from the device. The server analyzes the received data and extracts the user's input. For example, the server analyzes the text "I've been having frequent headaches lately" and passes it to the next processing step.

[1823] Input: JSON format data sent from the terminal

[1824] Output: Parsed text data

[1825] Step 4: Generative AI model generates advice

[1826] The server uses a generative AI model (e.g., a generative AI model using natural language processing technology) to generate advice based on the user's input. Specifically, the server inputs the following prompt sentence into the generative AI model:

[1827] User input: I've been having a lot of headaches lately.

[1828] Prompt for generative AI model: User inputs "I've been having a lot of headaches lately." Please provide appropriate advice.

[1829] The generative AI model generates advice based on this prompt, for example, "We recommend you drink plenty of fluids. If symptoms persist, consult your doctor."

[1830] Input: Parsed text data

[1831] Output: Text data of the generated advice

[1832] Step 5: Sending the results

[1833] The server sends the advice generated by the generative AI model to the terminal. Specifically, the server encodes the generated advice in JSON format and sends it as an HTTP response.

[1834] Input: Text data of generated advice

[1835] Output: Advice data sent to the terminal in JSON format.

[1836] Step 6: View the results

[1837] The device displays the advice received from the server to the user. Specifically, the device displays the generated advice using the application's UI components (e.g., a text view or a popup message). The user can view the advice through the application.

[1838] Input: Advice data received from the server in JSON format

[1839] Output: The text of the advice displayed to the user.

[1840] Step 7: Recommending Nutrient Needs

[1841] Based on the generated advice, the server recommends the necessary nutrients (foods, supplements, dishes, etc.) to the user. For example, it makes a specific recommendation such as "We recommend that you consume foods that are high in vitamin C."

[1842] Input: Text data of generated advice

[1843] Output: Text data of recommended nutrients

[1844] Step 8: Buy nutrients directly

[1845] Users can directly purchase the recommended nutrients, specifically by using the online shopping function through the application or website to purchase the recommended foods and supplements.

[1846] Input: Text data of recommended nutrients

[1847] Output: Purchase completion notification

[1848] Step 9: Collaboration with medical institutions and doctors

[1849] If necessary, users can talk directly to medical institutions and doctors, specifically by using video calls and chat functions to communicate with doctors in real time.

[1850] Input: Information about the user's health and symptoms

[1851] Output: Communication logs with medical institutions and doctors

[1852] (Application example 1)

[1853] Next, a description will be given of Application Example 1 of Form 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."

[1854] Conventional health management systems have the problem that users only need to input their own health condition and symptoms, making it difficult to take prompt action when an abnormality is detected. Furthermore, there is a lack of a means to send appropriate notifications when an abnormality is detected, and measures to ensure user safety are insufficient. This makes it difficult for users to quickly access appropriate medical institutions and emergency contacts in the event of an emergency.

[1855] 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.

[1856] In this invention, the server includes means for grasping bodily signs (symptoms), means for utilizing generative AI to grasp nutritional deficiencies and excesses based on the bodily signs (symptoms), means for recommending necessary nutrients (foods, supplements, meals, etc.) based on the nutritional deficiencies and excesses, means for directly purchasing the recommended nutrients, means for directly communicating with medical institutions or doctors as needed, means for detecting abnormalities based on the bodily signs (symptoms) and sending notifications, and communication means for sending the notifications. This allows the user not only to input their own physical condition and symptoms, but also to quickly send notifications when abnormalities are detected and take appropriate action.

[1857] "Physical signs (symptoms)" refers to specific information about a user's physical condition or health status.

[1858] "Generative AI" is an artificial intelligence technology that analyzes data on physical condition and symptoms entered by the user and provides appropriate nutritional and medical information.

[1859] "Nutrition deficiency" is information that indicates whether the user is lacking or over-dosing on necessary nutrients based on their physical condition and symptoms.

[1860] "Essential nutrients" are the nutritional components of foods, supplements, dishes, etc. that are recommended to improve the user's health.

[1861] "Recommendation methods" are methods that suggest appropriate nutrients to users based on the results of analysis by generative AI.

[1862] "Direct purchasing means" refers to a method that allows users to purchase the recommended nutrients on-site.

[1863] "Direct communication with healthcare providers and physicians" means a method by which users can communicate with healthcare professionals in real time as needed.

[1864] "Means for detecting abnormalities" refers to a method for analyzing data on physical condition and symptoms entered by the user and determining whether or not there is an abnormality.

[1865] "Means for sending notifications" refers to the method for sending warnings and information to users and emergency contacts when an abnormality is detected.

[1866] "Communication means" refers to the communication technology, such as the internet or mobile network, used to send the notification.

[1867] As an embodiment of the present invention, the following system can be constructed.

[1868] System configuration

[1869] The system consists of a device (such as a smartphone or PC) with an interface for inputting the user's physical condition and symptoms, and a server for analyzing the data. The server uses a generative AI model to analyze the data and detect necessary nutrients and abnormalities.

[1870] Program processing

[1871] Hardware

[1872] Smartphone

[1873] PC

[1874] server

[1875] software

[1876] Python

[1877] The requests library (to send HTTP requests)

[1878] Generative AI Model

[1879] Data processing and calculation

[1880] 1. Data input: Users enter their own physical condition and symptoms through a smartphone or computer interface. For example, they enter specific information such as "I have a headache" or "I get tired easily."

[1881] 2. Data analysis: The server uses a generative AI model to analyze the input data, identify nutritional deficiencies and excesses, and determine the appropriate response if an abnormality is detected.

[1882] 3. Recommendations and Notifications: The server recommends necessary nutrients to the user based on the analysis results. Furthermore, if an abnormality is detected, a notification will be sent to the user or emergency contacts via communication means.

[1883] Specific examples

[1884] For example, if a user types "I have a headache," the server uses a generative AI model to analyze this information and identify possible nutrient deficiencies or excesses that could be causing the headache. It then recommends the necessary nutrients (such as magnesium or B vitamins) to the user. Furthermore, if an abnormality is detected, a notification is sent to emergency contacts to prompt appropriate action.

[1885] Prompt Sentence Examples

[1886] "Write a Python program that analyzes the user's physical condition and symptoms and sends a notification if an abnormality is detected. Anomalies will be detected based on specific keywords (e.g. headache, fatigue, dizziness, chest pain). Notifications will be sent using an HTTP POST request."

[1887] In this way, a system can be realized in which a user simply inputs their own physical condition and symptoms, and if an abnormality is detected, a notification is sent quickly and appropriate action can be taken.

[1888] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1889] Step 1:

[1890] Users input their physical condition and symptoms through a smartphone or computer interface.

[1891] Input: Information about your physical condition or symptoms entered by the user (e.g., "I have a headache" or "I get tired easily").

[1892] Output: Input data on physical condition and symptoms.

[1893] Specific operation: The user launches the application, enters their physical condition and symptoms in the text box, and presses the send button.

[1894] Step 2:

[1895] The device sends the entered data on physical condition and symptoms to the server.

[1896] Input: Physical condition and symptom data entered by the user.

[1897] Output: Health and symptom data sent to the server.

[1898] Specific operation: The device sends the input data to the server using an HTTP POST request.

[1899] Step 3:

[1900] The server inputs the data on physical condition and symptoms received into a generative AI model for analysis.

[1901] Input: Health and symptom data received by the server.

[1902] Output: Analysis results (presence or absence of nutritional deficiency or abnormalities).

[1903] How it works: The server inputs data into a generative AI model, which then analyzes the data to identify any nutritional deficiencies or abnormalities.

[1904] Step 4:

[1905] The server recommends necessary nutrients to the user based on the analysis results.

[1906] Input: Analysis results of a generative AI model.

[1907] Output: A list of recommended nutrients.

[1908] Specific operation: Based on the analysis results, the server generates a message recommending appropriate nutrients (foods, supplements, dishes, etc.) to the user.

[1909] Step 5:

[1910] If the server detects an abnormality, it will send a notification.

[1911] Input: Analysis results of the generative AI model (presence or absence of anomalies).

[1912] Output: Informational message.

[1913] Specific behavior: If the server detects an abnormality, it executes an HTTP POST request to send a notification to the emergency contact or user.

[1914] Step 6:

[1915] The device receives recommended messages and notifications from the server and displays them to the user.

[1916] Input: Recommendation messages and notifications sent by the server.

[1917] Output: The suggested message or notification that will be displayed to the user.

[1918] Specific operation: The device receives the message from the server and displays it on the application interface.

[1919] By following the above steps, a system can be realized in which a user can simply input their own physical condition and symptoms, and if an abnormality is detected, a notification will be sent quickly and appropriate action can be taken.

[1920] Example 2

[1921] Next, a description will be given of Example 2 of Form 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."

[1922] In modern society, it is important to quickly and accurately identify and provide appropriate nutrients based on an individual's physical condition and symptoms. However, conventional systems require users to input their physical condition and symptoms and then identify appropriate nutrients based on that information, which is a cumbersome process. It is also difficult to collect accurate data from the vast amount of information available on the Internet. Furthermore, there is a lack of support for users to take specific actions based on the information they obtain. This limits the means by which users can consume appropriate nutrients.

[1923] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1924] In this invention, the server includes: a means for a user to input their physical condition and symptoms; a means for a terminal to send the input data to the server; a means for the server to receive the data and send a prompt to the generative AI model; a means for the server to receive a response from the generative AI model and refer to an online medical information or nutrition database; a means for the server to identify appropriate nutrients and send the results to the terminal; a means for the terminal to display the results to the user; and a means for the user to check the results and input additional questions or data as necessary. This enables the user to quickly and accurately identify appropriate nutrients based on their physical condition and symptoms and receive support for taking specific actions.

[1925] "Physical signs (symptoms)" refer to abnormalities or discomforts that a user feels regarding their physical condition or health.

[1926] "Generative AI" refers to an artificial intelligence model that generates appropriate responses and information based on input data.

[1927] "Nutrition deficiency" refers to an excess or deficiency of nutrients required based on the user's physical condition or symptoms.

[1928] "Necessary nutrients" refers to nutrients that are recommended for intake to improve the user's physical condition or symptoms.

[1929] "Food, supplements, dishes, etc." refers to ingredients, supplements, or prepared dishes that contain necessary nutrients.

[1930] "Recommendation methods" refer to methods of suggesting foods and supplements containing necessary nutrients to users.

[1931] "Direct purchase ...

Claims

1. An information processing device comprising at least a processor, RAM, storage, and a communication interface, wherein the processor executes a program stored in the storage, receiving symptom text transmitted from the terminal, storing the symptom text in the RAM, analyzing the symptom text using natural language processing to extract keywords corresponding to the symptoms; Identifying the user's emotional state by using an emotion engine to recognize the user's emotional state based on the symptom text or the voice data transmitted from the terminal and calculating an emotion score; In addition to identifying nutrients based on the extracted keywords, by identifying nutrients that contribute to improving the emotional state according to the emotional state, candidates of nutrients necessary for the user are generated; Generate recommendations including a list of foods or supplements containing the nutrient and a link to purchase them; The generated recommendation information is transmitted to the terminal via the communication interface and displayed on a display device of the terminal. Information processing device.

2. The processor further includes means for providing cosmetic information.

2. The information processing device according to claim 1.

Images