System

Abstract

A system is provided.SOLUTION: This system is provided with a means for receiving data related with symptoms from a user terminal, a means for analyzing the received data, and for generating inquiry information, a means for selecting a proper medical institution based on the inquiry information, and for confirming medical examination possibility in cooperation with the medical institution, and a means for transmitting the information of the medical examination possible medical institution to the user terminal.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] For patients who suddenly become ill or injured at night or on holidays, in order to quickly visit an appropriate medical institution, they must call multiple medical institutions to confirm whether they are open, which often takes time. This can increase anxiety for patients and their families and delay appropriate treatment. In addition, the process of finding an acceptable medical institution requires hospitals to receive multiple inquiries, which increases their response time. To solve these problems, an effective and fast solution is needed. [Means for solving the problem]

[0005] The present invention provides a system that promptly guides patients to an appropriate medical institution in the event of an emergency such as sudden illness or injury at night or on a holiday. The present invention provides a system that includes a means for receiving symptom data transmitted from a user terminal, a means for analyzing the received data to generate medical interview information, a means for selecting an appropriate medical institution based on the medical interview information and confirming the availability of medical treatment in cooperation with that medical institution, and a means for transmitting information about available medical institutions to the user terminal. In addition, the system includes a means for determining the urgency of symptoms based on the received medical interview information and a means for analyzing the medical interview information as images, videos, and text, thereby enabling patients to receive treatment promptly at an appropriate medical institution. This reduces the burden on both patients and medical institutions and enables appropriate treatment to be provided promptly.

[0006] A "user terminal" is a communication device used by a user, and includes electronic devices such as smartphones, tablets, and personal computers.

[0007] "Symptom data" is information about a medical condition or injury entered by a patient, and may be in multiple formats, including text, audio, images, and video.

[0008] "Means for receiving" includes techniques and devices for obtaining data transmitted from a user terminal.

[0009] The "means for analyzing and generating interview information" includes techniques and devices for analyzing the received data and organizing it into information for diagnosing the patient's symptoms.

[0010] "Medical interview information" is medical information based on the analyzed symptoms of the user, and is provided as data necessary for diagnosis.

[0011] "Means for selecting a medical institution" includes methods and techniques for identifying an appropriate medical institution based on medical interview information.

[0012] "Means to confirm availability" includes techniques and methods for inquiring and confirming with selected medical institutions whether they can accept patients.

[0013] The "means for transmitting to the user terminal" includes techniques and devices for transmitting the generated guidance information to the user's device.

[0014] "Means for determining the degree of urgency" includes the use of methods and techniques for assessing the urgency of a patient's symptoms based on interview information.

[0015] "Means of analyzing images, videos, and text" includes techniques and methods for analyzing data in various formats and using it as medical interview information. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention is a system that promptly guides patients to appropriate medical institutions for sudden illness or injury at night or on holidays. The basic configuration of this system includes a user terminal, a server, a medical institution database, and a communication network.

[0038] The user terminal is a communication device such as a smartphone, tablet, or PC that the user uses to input symptom data. The symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[0039] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. The medical interview information includes details of symptoms and an assessment of the urgency of the condition.

[0040] The server also selects an appropriate medical institution based on the medical interview information. To do this, it references information from the medical institution database and takes into account information such as nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution to confirm whether the patient can be seen.

[0041] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[0042] This system allows users to receive emergency medical services without spending time and effort, and also allows medical institutions to efficiently accept patients who are available for treatment.

[0043] Specific examples

[0044] Example 1: When a child develops a high fever late at night

[0045] 1. User behavior

[0046] Users launch the app late at night, enter their child's symptoms (high fever, fatigue) in text, and take a photo of the rash and upload it to the app.

[0047] 2. Operation on the terminal side

[0048] The device collects this data and sends it to a server via the Internet.

[0049] 3. Server-side operation

[0050] The server analyzes the received data and uses an AI model to determine the urgency as "high." Because the condition involves a high fever, a detailed medical interview is generated and the user is advised on cooling methods as first aid.

[0051] 4. Selection of medical institution

[0052] The server searches the database for hospitals with pediatric departments that are open at night, sends the medical interview information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[0053] 5. Sending guidance information

[0054] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[0055] 6. Terminal operation

[0056] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[0057] Example 2: If you cut your hand on a holiday

[0058] 1. User behavior

[0059] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding, how much pain there is) in text.

[0060] 2. Operation on the terminal side

[0061] The device collects data and sends it to a server via the internet.

[0062] 3. Server-side operation

[0063] The server analyzes the image and text data, and uses an AI model to determine the urgency of the situation. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure.

[0064] 4. Selection of medical institution

[0065] The server searches for surgeries that are open even on holidays, sends medical interview information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[0066] 5. Sending guidance information

[0067] The server generates information about the selected hospital and sends it to the terminal.

[0068] 6. Terminal operation

[0069] The device displays the information, the user contacts the designated hospital, and the journey begins.

[0070] In this way, this system provides a prompt and appropriate response to sudden illness or injury at night or on holidays, significantly reducing the burden on patients and medical institutions.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The user launches the app.

[0074] Step 2:

[0075] The user enters symptoms by text or voice.

[0076] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[0077] Step 3:

[0078] The device collects this data and sends it to a server over the Internet.

[0079] Step 4:

[0080] The server receives text, audio, image, and video data sent from the user terminal.

[0081] Step 5:

[0082] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[0083] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[0084] Step 6:

[0085] The server uses a generative AI model to generate medical interview information from the extracted information.

[0086] The server assesses the urgency and generates the necessary emergency response information.

[0087] Step 7:

[0088] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and urgency information.

[0089] The server lists multiple candidate medical institutions.

[0090] Step 8:

[0091] The server transmits the medical interview information to each selected medical institution and confirms whether the patient can receive treatment.

[0092] Step 9:

[0093] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[0094] Step 10:

[0095] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[0096] Step 11:

[0097] The server transmits the generated guidance information to the user terminal.

[0098] Step 12:

[0099] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[0100] Step 13:

[0101] The user follows the displayed guidance information and heads to the designated medical institution.

[0102] If necessary, the user can contact the medical institution using the displayed contact information.

[0103] Example 1

[0104] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0105] In modern society, when people suddenly become ill or injured at night or on holidays, it can be difficult to quickly find an appropriate medical institution. Furthermore, there is a risk that a patient's condition may worsen if appropriate initial treatment is delayed for highly urgent symptoms. There is a need for a method to solve these problems and provide prompt and appropriate medical institution guidance.

[0106] 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.

[0107] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data to generate medical interview information, means for evaluating the urgency of the condition, means for selecting an appropriate medical facility from a medical facility database and confirming the availability of medical treatment in cooperation with the selected medical facility, means for transmitting information on available medical facilities to the user terminal, and means for analyzing the data using an AI model, natural language processing technology, and image recognition technology. This enables the user to be quickly directed to an appropriate medical institution even if they suddenly become ill or injured at night or on a holiday.

[0108] A "user terminal" is a communication device that allows a user to input and receive data related to symptoms, and includes smartphones, tablets, personal computers, etc.

[0109] "Means for receiving data" refers to a mechanism by which the server receives symptom-related data sent from the user terminal.

[0110] "Means for generating medical interview information" refers to a mechanism by which the server analyzes the data received and generates the necessary information based on the patient's symptoms.

[0111] "Means for assessing urgency" refers to a mechanism for determining the urgency of a patient's symptoms based on analyzed data.

[0112] The "medical facility database" is a database that contains information on the medical departments, bed availability, and the availability of specialists at various medical facilities.

[0113] "Means to confirm availability of medical treatment in cooperation with medical facilities" refers to a system for sending medical interview information to selected medical facilities to confirm availability of medical treatment.

[0114] "Means for transmitting information to a user terminal" refers to a mechanism for transmitting information about selected medical facilities from a server to a user terminal.

[0115] An "AI model" refers to a mathematical model that uses artificial intelligence technology to analyze data and generate appropriate information and judgments.

[0116] "Natural language processing technology" refers to technology that analyzes, understands, and generates natural human language.

[0117] "Image recognition technology" refers to the technology of analyzing image data and extracting useful information from it.

[0118] This invention is a system that promptly guides users who suddenly become ill or injured at night or on holidays to appropriate medical institutions. This system includes a user terminal, a server, a medical facility database, and a communication network.

[0119] First, a user enters symptom data into the application using a user device such as a smartphone, tablet, or PC. Symptom data can be provided in a variety of formats, including text input, voice input, images, and videos. For example, a user might enter text about their child's high fever and fatigue late at night and upload a photo of the rash. This data is then sent to a server via the Internet.

[0120] The server receives data sent from the user's device and analyzes the symptom data using an AI model, natural language processing technology, and image recognition technology. The AI ​​model is a mathematical model that analyzes data and generates medical interview information. The natural language processing technology is a technology for analyzing text data and understanding symptoms. The image recognition technology is a technology for analyzing image data and extracting useful information from it.

[0121] For example, if the server analyzes data on "high fever" and "rash" and determines that these are related symptoms, it will assess the urgency as "high." Based on the analyzed data, medical interview information is generated and the urgency is assessed. At the same time, the server generates first aid advice as needed. In the case of high fever and rash, advice on "cooling methods" and "hydration intake" is provided.

[0122] Next, the server references a medical facility database and selects the medical facility that best suits the user's symptoms. The medical facility database contains information such as medical specialty, available beds, and whether or not there are specialists. The server then sends the medical interview information to the selected medical facility to confirm whether or not the patient can be seen. For example, the server selects several hospitals with pediatric departments that are open at night, and sends the medical interview information to each to confirm whether or not the patient can be seen.

[0123] Once a medical facility where the patient can be seen is confirmed, the server sends that information to the user's terminal. The user terminal displays this information to the user. The guidance information includes the name, address, contact information, and arrival time of the medical facility. For example, the user terminal displays something like, "Please contact XX Hospital (address: XX town, XX chome). Arrival time is approximately 15 minutes."

[0124] Examples of concrete examples and prompts

[0125] Example: If your child develops a high fever in the middle of the night

[0126] 1. User behavior: The user launches the app late at night, enters their child's symptoms (high fever, fatigue) in text, takes a photo of the rash, and uploads it to the app.

[0127] 2. Operation on the device side: The device collects data and sends it to a server via the Internet.

[0128] 3. Server-side operation: The server analyzes the received data, determines the urgency as "high," generates a medical interview result, and advises emergency measures.

[0129] 4. Selection of medical institution: The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals.

[0130] 5. Sending guidance information: The server sends information about the selected hospital to the terminal.

[0131] 6. Operation on the terminal side: The terminal displays the information, the user contacts the hospital, and begins the journey.

[0132] Prompt Sentence Examples

[0133] "Late at night, the user enters a text message about their child's high fever and uploads a photo of the rash to the app. The device collects the data and sends it to a server via the internet. The server analyzes the data, determines the urgency as 'high,' generates a medical interview result, and advises first aid. The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals. The server then sends the information of the selected hospital to the device. The device displays the information, and the user contacts the hospital."

[0134] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[0135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0136] Step 1:

[0137] The user launches the system's application on a device such as a smartphone, tablet, or PC and enters detailed data about the symptoms.

[0138] Specific behavior:

[0139] The user enters text that they have a persistent high fever and feel very fatigued, takes a photo of the rash and uploads it to the app.

[0140] Input: Symptom data (text, images)

[0141] Output: Aggregated symptom data on the device

[0142] Step 2:

[0143] The user terminal transmits the input symptom data to a server via the Internet.

[0144] Specific behavior:

[0145] The smartphone collects text and image data and sends them to a server via a secure communication line.

[0146] Input: Symptom data collected on the device

[0147] Output: Symptom data sent to the server

[0148] Step 3:

[0149] The server receives the data sent from the user's device and analyzes it using AI models, natural language processing technology, and image recognition technology.

[0150] Specific behavior:

[0151] The server analyzes the data for "high fever" and "rash" and determines that these are related symptoms.

[0152] Input: Received symptom data

[0153] Output: Analyzed medical interview information (symptom classification, feature extraction)

[0154] Step 4:

[0155] The server generates medical interview information based on the analysis results and evaluates the urgency.

[0156] Specific behavior:

[0157] Based on cases of high fever and rash, advice is provided on "cooling methods" and "fluid intake."

[0158] Input: Parsed medical interview information

[0159] Output: Urgency assessment and advice

[0160] Step 5:

[0161] The server refers to a medical facility database and selects an appropriate medical facility.

[0162] Specific behavior:

[0163] The server selects multiple hospitals with pediatric departments that are open at night and transmits medical interview information to each hospital.

[0164] Input: Medical interview information, urgency assessment

[0165] Output: List of selected medical facilities

[0166] Step 6:

[0167] The server sends the medical interview information to the selected medical facility and checks whether the patient can be seen.

[0168] Specific behavior:

[0169] After receiving responses from each hospital, the most appropriate hospital will be selected.

[0170] Input: List of selected medical facilities, medical history information

[0171] Output: Check results for available medical facilities

[0172] Step 7:

[0173] Once the medical facility where the patient can be seen is confirmed, the server transmits the information to the user terminal.

[0174] Specific behavior:

[0175] The server generates a message saying, "Please contact XX Hospital (address: XX-cho XX-chome). Arrival time is approximately 15 minutes," and sends it to the user terminal.

[0176] Input: Confirmation result of available medical facilities

[0177] Output: Medical facility information sent to the user's device

[0178] Step 8:

[0179] The user terminal displays the received information about the medical facility to the user.

[0180] Specific behavior:

[0181] The smartphone displays detailed information about medical facilities on the screen, and the user follows the instructions to head to the hospital.

[0182] Input: Received medical facility information

[0183] Output: Medical facility information displayed on the screen

[0184] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[0185] (Application example 1)

[0186] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0187] While there are systems in place that can quickly guide patients to the appropriate medical institution in the event of sudden illness or injury at night or on holidays, there are no systems that take into account the patient's nutritional status or the provision of food for first aid. This can lead to patients being unable to select appropriate foods, resulting in insufficient nutrition. Medical institutions also have to work hard to provide food according to the patient's condition. Therefore, there is a need for a system that allows patients to quickly obtain information on both the appropriate medical institution and food, and to ensure appropriate nutritional management.

[0188] 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.

[0189] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data and generating medical interview information, means for selecting an appropriate medical institution affiliated organization based on the medical interview information and confirming the availability of medical treatment in cooperation with the medical institution affiliated organization, means for selecting optimal foods based on the availability of medical treatment by the medical institution affiliated organization, and means for transmitting information on available medical institution affiliated organizations and optimal food information to the user terminal, thereby enabling patients to quickly obtain information on both appropriate medical institutions and foods.

[0190] A "user terminal" is a communication device that allows a user to input data about symptoms and transmit the data to a server.

[0191] "Symptom Data" is information about a medical condition or injury a user is experiencing, provided in the form of text, images, video, or other information.

[0192] The "medical interview information" is information generated by the server by analyzing data on symptoms received from the user, and includes details of the symptoms and an assessment of the urgency of the symptoms.

[0193] The "medical institution affiliated organization" is a medical institution that the server selects based on the medical interview information and collaborates with to confirm the possibility of receiving medical treatment.

[0194] "Accessibility" is information indicating whether the selected medical institution affiliated organization can actually accept the patient.

[0195] "Optimal foods" are nutritionally balanced foods and drinks selected based on the user's symptoms.

[0196] "Appropriate food information" is detailed information about the most suitable food selected by the server and provided to the user.

[0197] This invention is a system that provides prompt and appropriate information on both medical institutions and food when a user suddenly becomes ill or injured at night or on a holiday. Specific methods for realizing this system are described below.

[0198] First, a user uses a user device such as a smartphone to input data about their symptoms. This data is provided in the form of text input, voice input, images, videos, etc. For example, if a user complains of a symptom of "high fever," they can input the symptoms in text and upload a photo of their face showing a high fever.

[0199] The user device then collects this data and sends it over the Internet to a server, which is built using the Flask framework and receives the data sent from the user device.

[0200] The server analyzes the received data and generates medical interview information. This analysis uses generative AI models, natural language processing technology, and image recognition technology. This allows the server to evaluate the details and urgency of symptoms and create specific medical interview information.

[0201] Next, the server selects an appropriate medical institution affiliated with the patient based on the generated medical interview information. It references information from the medical institution affiliated organization database and considers nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution affiliated with the patient to confirm whether the patient can be seen.

[0202] The server then selects the most appropriate food based on the patient's symptoms. This selection is done using a generative AI model based on the patient's symptoms. For example, if the patient has a high fever, appropriate foods such as porridge or soup will be selected.

[0203] Finally, the server sends information about affiliated medical institutions where patients can receive treatment, as well as information about the most suitable foods, to the user's device. Based on this information, the user's device guides the user on the most suitable course of action. Based on this guidance, the user can head to the appropriate medical institution and simultaneously order the appropriate foods.

[0204] (Example)

[0205] Example 1: When a user's child develops a high fever late at night

[0206] Users launch the app, type in the text "high fever," and then upload a photo of their face showing a high fever.

[0207] The server receives the data, analyzes it, and generates medical interview information. The urgency level is determined to be "high."

[0208] The server selects affiliated medical institutions with pediatric departments that are available for consultation and sends the information to the user's device. It also recommends "porridge" or "soup."

[0209] The user follows the guidance information and orders porridge for delivery on their way to the medical institution.

[0210] Example 2: If the user cuts their hand on a holiday

[0211] The user launches the app, takes a photo of the wound on their hand, and enters the bleeding status in text.

[0212] The server receives the data, analyzes it, and then generates medical interview information. As first aid, the doctor advises applying pressure to stop the bleeding.

[0213] The server selects a surgery that is open even on holidays and sends the information to the user's terminal. It also recommends appropriate foods for nutritional support.

[0214] The user follows the guidance information and orders the recommended food for delivery while heading to the medical institution.

[0215] (Example of a prompt)

[0216] "Please list foods that you recommend for high fever symptoms."

[0217] "Please tell me how to provide first aid for bleeding hands."

[0218] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0219] Step 1:

[0220] A user launches a smartphone app and inputs data about their symptoms. The input data includes textual symptom descriptions, voice input, images, and videos. For example, a user might input the symptom "high fever" in text and upload a photo of their face. In this case, the user's input becomes input data for the system.

[0221] Step 2:

[0222] The device collects data entered by the user and sends it to a server via the internet. The input data includes text, audio, images, and video detailing the symptoms. This is the data collection process on the device side. The output of the device is the data sent to the server.

[0223] Step 3:

[0224] The server receives the data sent from the device. It analyzes the received data and generates medical interview information using generative AI models, natural language processing (NLP), and image recognition technology. For example, the server analyzes the received image using image recognition technology, determines the details of a high fever, and evaluates the urgency as "high." The input is data from the device, and the output is the generated medical interview information.

[0225] Step 4:

[0226] The server selects an appropriate medical institution affiliated organization based on the medical interview information generated by the server. The server references a database of medical institution affiliated organizations and makes the selection taking into consideration information such as medical departments in the user's vicinity, available hospital beds, and the availability of specialists. For example, it selects a pediatric clinic that is open late at night. The input is the medical interview information, and the output is information on the selected medical institution affiliated organization.

[0227] Step 5:

[0228] The medical interview information is sent to the selected medical institution affiliated organizations to confirm the possibility of receiving medical treatment. Specifically, the server sends the medical interview information to each medical institution affiliated organization and waits for a response from each medical institution affiliated organization. The input is a list of medical institution affiliated organizations and the medical interview information, and the output is the confirmed possibility of receiving medical treatment information.

[0229] Step 6:

[0230] The server selects the most appropriate food based on the confirmed likelihood of medical treatment. In this process, the generative AI model recommends appropriate foods based on the symptoms. For example, in the case of a high fever, "porridge" or "soup" is recommended. The input is medical interview information about the symptoms, and the output is a list of appropriate foods.

[0231] Step 7:

[0232] Information on affiliated medical institutions where patients can be seen and information on optimal foods is sent to the user's terminal. The server sends all information together to the user's terminal, making it immediately available to the user. For example, in addition to the name, address, and contact information of the pediatric clinic the user should visit, "porridge" is displayed as a recommended food. The input is the confirmed information on availability of medical treatment and food information, and the output is guidance information sent to the user's terminal.

[0233] Step 8:

[0234] The user begins to act based on the information received. The user checks the guidance information and heads to the medical institution, while simultaneously ordering the recommended food from a delivery service. For example, the user can easily order "porridge" from the app and request delivery. The input is the guidance information sent to the user's device, and the output is the user's actions and food order.

[0235] 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.

[0236] This invention is a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it implements a means for providing the user with more appropriate support. The basic configuration of this system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network.

[0237] The user terminal is a communication device such as a smartphone, tablet, or PC, which the user uses to input symptom data. The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state. Symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[0238] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. Emotional information recognized by an emotion engine is also taken into account as part of the analysis. This allows the assessment of urgency and first aid advice to be adapted to the user's emotional state, providing more appropriate support.

[0239] The server then selects an appropriate medical institution based on the medical history information and emotion information. This selection refers to information in the medical institution database, taking into account nearby medical departments, available beds, the availability of specialists, and other information. The medical history information and emotion information are then sent to the selected medical institution to confirm whether the patient can be seen.

[0240] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[0241] This system allows users to receive emergency medical services without spending time and effort, and allows medical institutions to efficiently accept patients who can be seen. In addition, by responding to the user's emotions, it reduces the user's psychological burden and provides more appropriate medical services.

[0242] Specific examples

[0243] Example 1: When a child develops a high fever late at night

[0244] 1. User behavior

[0245] The user launches the app late at night and enters text about their child's symptoms (high fever, fatigue), then takes a photo of the rash and uploads it to the app. The app then uses its emotion engine to recognize the user's anxious expression and trembling voice.

[0246] 2. Operation on the terminal side

[0247] The device collects this data and sends it to a server via the Internet.

[0248] 3. Server-side operation

[0249] The server analyzes the received data and determines the urgency as "high" using an AI model. Since the situation involves a high fever, the emotion engine also incorporates information from the model to generate detailed interview results. Because the situation is urgent and highly anxious, the system immediately advises the user on how to cool down the situation.

[0250] 4. Selection of medical institution

[0251] The server searches the database for hospitals with pediatric departments that are open at night, sends the patient interview information and emotion information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[0252] 5. Sending guidance information

[0253] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[0254] 6. Terminal operation

[0255] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[0256] Example 2: If you cut your hand on a holiday

[0257] 1. User behavior

[0258] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding or not, the degree of pain) in text. The app uses its emotion engine to recognize the user's state of tension.

[0259] 2. Operation on the terminal side

[0260] The device collects data and sends it to a server via the internet.

[0261] 3. Server-side operation

[0262] The server analyzes the image and text data and uses an AI model to determine the level of urgency. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure. The system also takes into account information from the emotion engine, providing gentle, specific instructions.

[0263] 4. Selection of medical institution

[0264] The server searches for surgeries that are open even on holidays, sends medical interview information and emotion information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[0265] 5. Sending guidance information

[0266] The server generates information about the selected hospital and sends it to the terminal.

[0267] 6. Terminal operation

[0268] The device displays the information, the user contacts the designated hospital, and the journey begins.

[0269] In this way, by combining this system with an emotion engine, it is possible to reduce the psychological burden on users and enable more appropriate responses, thereby providing prompt and appropriate medical support while also reducing stress and anxiety for users.

[0270] The processing flow will be explained below.

[0271] Step 1:

[0272] The user launches the app.

[0273] Step 2:

[0274] The user enters symptoms by text or voice.

[0275] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[0276] Step 3:

[0277] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0278] For example, identifying emotions such as anxiety or tension.

[0279] Step 4:

[0280] The device collects symptom data (text, audio, images, video) and emotional information and sends it to a server via the Internet.

[0281] Step 5:

[0282] The server receives the data sent from the user terminal.

[0283] Step 6:

[0284] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[0285] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[0286] The server also analyzes the emotion information from the emotion engine.

[0287] Step 7:

[0288] The server uses a generative AI model to generate medical interview information from the extracted information (symptom data, emotion data).

[0289] The server evaluates the urgency and generates the necessary emergency measures, taking emotional information into consideration to provide appropriate advice.

[0290] Step 8:

[0291] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and emotion information.

[0292] The server lists multiple candidate medical institutions.

[0293] Step 9:

[0294] The server transmits the medical interview information and emotion information to each selected medical institution to confirm the possibility of receiving treatment.

[0295] Step 10:

[0296] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[0297] Step 11:

[0298] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[0299] Step 12:

[0300] The server transmits the generated guidance information to the user terminal.

[0301] Step 13:

[0302] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[0303] The device provides the user with information including additional first aid measures and precautions that take emotions into consideration.

[0304] Step 14:

[0305] The user follows the displayed guidance information and heads to the designated medical institution.

[0306] If necessary, the user can contact the medical institution using the displayed contact information.

[0307] Specific examples

[0308] Example 1: When a child develops a high fever late at night

[0309] 1. Step 1: A user launches the app late at night.

[0310] 2. Step 2: The user enters a text description of their child's symptoms (high fever, fatigue) and takes and uploads a photo of the rash.

[0311] 3. Step 3: The emotion engine recognizes the user's anxious facial expression and trembling voice.

[0312] 4. Step 4: The device sends this data (text, images, and emotional information) to the server.

[0313] 5. Step 5: The server receives the data.

[0314] 6. Step 6: The server analyzes the text data, inspects the images, and captures the user's emotional information.

[0315] 7. Step 7: The server determines the urgency to be "high" and the situation involves a high fever, so it generates detailed medical interview results and presents first aid measures (cooling methods).

[0316] 8. Step 8: The server searches the database for pediatricians who are available for overnight consultations and creates a list of candidates.

[0317] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[0318] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[0319] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[0320] 12. Step 12: The server sends the guidance information to the user terminal.

[0321] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[0322] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[0323] Example 2: If you cut your hand on a holiday

[0324] 1. Step 1: The user launches the app.

[0325] 2. Step 2: The user takes a photo of the wound on their hand and reports the extent of bleeding and pain in text.

[0326] 3. Step 3: The emotion engine recognizes the user's state of tension.

[0327] 4. Step 4: The device sends data (text, images, and emotional information) to the server.

[0328] 5. Step 5: The server receives the data.

[0329] 6. Step 6: The server analyzes the image and text data and captures emotional information.

[0330] 7. Step 7: The server determines the urgency to be "medium" and gently and specifically suggests first aid measures (pressure hemostasis).

[0331] 8. Step 8: The server searches for surgeries that are open on holidays and creates a candidate list.

[0332] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[0333] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[0334] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[0335] 12. Step 12: The server sends the guidance information to the user terminal.

[0336] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[0337] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[0338] Example 2

[0339] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0340] In modern society, there is a need for a system that enables users to seek medical attention quickly and appropriately when they suddenly become ill or injured at night or on holidays. However, it can be difficult for users, especially those who are emotionally upset, to find the most appropriate medical institution and complete the procedures for seeking medical attention. For this reason, a support system is needed that recognizes the user's emotional state and provides appropriate responses, allowing users to seek medical attention quickly and with peace of mind.

[0341] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving symptom-related data from a user terminal, means for analyzing the received data and generating medical interview information, and means for selecting an appropriate medical institution based on the medical interview information and emotional information using a generative AI model, and for confirming the possibility of receiving medical treatment in cooperation with the medical institution via a communication network. This allows the user to quickly find the most appropriate medical institution, and further allows the user to feel at ease when starting to seek medical treatment by receiving advice on first aid that takes emotional information into consideration.

[0342] A "user terminal" is an electronic device that allows a user to input data about symptoms and transmit the data to a server via a communication network.

[0343] "Symptom data" refers to information that indicates the state of illness or injury of the user or a third party, and may be in the form of text, images, video, audio, or the like.

[0344] The "receiving means" is a mechanism by which the server receives data transmitted from the user terminal via the communication network.

[0345] "Medical interview information" is information necessary for medical treatment obtained by analyzing received symptom data.

[0346] The "means for confirming availability for medical treatment" is a mechanism by which the server sends medical interview information to an appropriate medical institution and confirms whether or not the medical institution is available for medical treatment.

[0347] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to generate emotional information.

[0348] "Emotion information" is information obtained by analyzing the user's emotional state using an emotion engine.

[0349] The "means for selecting an appropriate medical institution" is a mechanism for identifying the most suitable medical institution for a user based on medical interview information and emotional information.

[0350] "Communications Network" means the Internet or other communications infrastructure used to transmit and receive data.

[0351] "First aid advice" is a temporary solution that the server provides to the user based on the analysis results and the urgency assessment.

[0352] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and generate emotional information.

[0353] The present invention provides a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately. This support system is particularly equipped with an emotion engine that recognizes the user's emotions, and is further equipped with a means for providing appropriate support to the user. The following describes in detail an embodiment of the present invention.

[0354] Basic configuration

[0355] The basic configuration of the system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network. User terminals can be communication devices such as smartphones, tablets, and PCs. The emotion engine is used to recognize the user's emotional state by analyzing their facial expressions and vocal tone. Data is sent and received via the Internet.

[0356] User terminal

[0357] Users use a smartphone, tablet, or PC with a dedicated application installed. The user device provides an interface for inputting symptom data. This data can include text input, voice input, images, and videos, allowing users to provide information in an appropriate format. The system also incorporates an emotion engine that generates emotional information by analyzing facial expressions and tone of voice when the user describes their symptoms.

[0358] server

[0359] The server uses high-performance hardware and analyzes data using AI models, natural language processing (NLP), and image recognition technology. When the server receives data sent from the user's device, it begins analysis and generates medical interview information and emotional information. This allows the server to assess the urgency of the symptoms and provide first aid advice if necessary.

[0360] Emotion Engine

[0361] The emotion engine is software that analyzes the user's facial expressions and tone of voice to generate emotional information, which determines whether the user is feeling anxious or nervous, and responds accordingly.

[0362] Selection of medical institutions

[0363] The server selects an appropriate medical institution based on the medical interview information and emotion information generated by the server. This selection refers to information in the medical institution database, taking into account information such as medical departments, available beds, and the availability of specialists. The server sends the medical interview information and emotion information to the medical institution and confirms the possibility of treatment.

[0364] Providing guidance information

[0365] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the most suitable medical institution to the user. Contact information is also provided so that the user can contact the medical institution directly.

[0366] Specific examples

[0367] Example 1: When a child develops a high fever late at night

[0368] 1. A user launches the app late at night and enters their child's symptoms (high fever, fatigue) in text. They also upload a photo of the rash to the app.

[0369] 2. The emotion engine recognizes the user's anxious facial expression and trembling voice.

[0370] 3. The server receives this data and determines the urgency as "high."

[0371] 4. The server searches for multiple hospitals with pediatric departments that are open at night and selects the most suitable hospital.

[0372] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[0373] Example 2: If you cut your hand on a holiday

[0374] 1. The user launches the app, takes a photo of the cut on their hand, and reports via text whether there is bleeding and the degree of pain.

[0375] 2. The emotion engine recognizes the user's state of tension.

[0376] 3. The server receives this data, analyzes it, and advises the patient to apply pressure to stop bleeding if there is bleeding.

[0377] 4. The server searches for surgeries that are open even on holidays and selects the most suitable hospital.

[0378] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[0379] In this way, by utilizing generative AI models and emotion engines, the system of the present invention can reduce the psychological burden on users and provide prompt and appropriate medical support.

[0380] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0381] Step 1:

[0382] Entering Symptom Information

[0383] User actions: The user launches the app on a device on which the dedicated application is installed and enters symptom data using the symptom input interface.

[0384] Input: Symptom text, audio, image, and video data.

[0385] Output: The input data is saved in the device.

[0386] What happens: A user types in "high fever" and takes and uploads a photo of a rash.

[0387] Step 2:

[0388] Emotional information generation

[0389] Device operation: The emotion engine analyzes the user's facial expressions and tone of voice to generate emotional information.

[0390] Input: User facial and voice data.

[0391] Output: Data indicating the user's emotional state.

[0392] Specific operation: The device takes a picture of the user's face with a camera, analyzes their emotional state (e.g., anxiety) from their facial expression, and saves it as data.

[0393] Step 3:

[0394] Sending data

[0395] Device operation: The device collects and analyzes symptom data and emotional information, which are then sent to a server via the Internet.

[0396] Input: Symptom data, emotion information.

[0397] Output: Data sent to server completed.

[0398] Specific operation: When the device presses the "send" button, data is sent to the server via the Internet.

[0399] Step 4:

[0400] Receiving data

[0401] Server operation: The server receives the data sent from the user terminal.

[0402] Input: Symptom data, emotion information.

[0403] Output: The received data is stored in the server.

[0404] Specific operation: The server periodically checks for data reception and saves any new data.

[0405] Step 5:

[0406] Data analysis

[0407] Server operation: The server analyzes the received symptom data and generates medical interview information. At the same time, it analyzes emotional information.

[0408] Input: Received symptom data, emotion information.

[0409] Output: Interview information, emotion evaluation results.

[0410] How it works: The AI ​​model analyzes text data using natural language processing technology to detect "high fever," and uses image recognition technology to identify "rash" and assess its urgency.

[0411] Step 6:

[0412] Urgency assessment and first aid advice

[0413] Server operation: Evaluate the urgency of the symptoms based on the analysis results and generate first aid advice.

[0414] Input: Interview information, emotion assessment results.

[0415] Output: Urgency assessment result, first aid advice.

[0416] Specific behavior: If the evaluation result is "Urgency: High," advice such as "Use a cooling towel" is generated.

[0417] Step 7:

[0418] Selection of medical institutions

[0419] Server operation: The server refers to the medical institution database and selects an appropriate medical institution based on the medical interview information and emotion information.

[0420] Input: Interview information, emotion assessment results.

[0421] Output: Information on selected medical institutions.

[0422] Specific operation: The server searches for pediatric hospitals that are open at night and obtains information on multiple medical institutions.

[0423] Step 8:

[0424] Checking availability for medical examination

[0425] Server operation: Sends medical interview information and emotion information to the selected medical institution to confirm the possibility of receiving treatment.

[0426] Input: Information on the selected medical institution, medical interview information, and emotion assessment results.

[0427] Output: A list of available medical facilities.

[0428] Specific operation: Check the response from each medical institution regarding the availability of treatment and determine the most suitable medical institution.

[0429] Step 9:

[0430] Generating guidance information

[0431] Server operation: Once available medical institutions are confirmed, guidance information is generated.

[0432] Input: Information about medical institutions where you can receive treatment.

[0433] Output: Guidance information.

[0434] Specific operation: The server generates a package containing the name, address, contact information, and arrival time of the medical institution.

[0435] Step 10:

[0436] Sending guidance information

[0437] Server operation: Sends guidance information to the user terminal.

[0438] Input: Guidance information.

[0439] Output: Data sent to user terminal.

[0440] Specific operation: The server sends guidance information to the user terminal via the Internet.

[0441] Step 11:

[0442] Displaying information and encouraging action

[0443] Terminal operation: The user terminal displays the guidance information received and prompts the user to take action.

[0444] Input: Received information.

[0445] Output: The clinic information displayed to the user.

[0446] What it does: The app displays, "The nearest pediatric clinic is XX Hospital. The address is XX and the reach time is approximately 15 minutes." and also makes the contact information clickable.

[0447] (Application example 2)

[0448] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0449] In order to enable users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, it is necessary to provide a system that can reduce the psychological burden on users and provide appropriate medicines and first aid advice.However, current medical support systems have the problem of being unable to provide appropriate responses that take into account the user's emotional state.

[0450] The identification process by the identification 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 means for receiving symptom-related data from a user terminal, means for analyzing the received data to generate medical interview information, means for analyzing the user's facial expression and tone of voice using an emotion engine to determine the level of urgency, means for selecting an appropriate medical institution based on the medical interview information and confirming the availability of medical treatment in cooperation with that medical institution, means for transmitting information about available medical institutions to the user terminal, means for providing the user with the inventory status of necessary medicines for the user's symptoms, and means for providing the user with first aid according to the level of urgency and advice to reduce psychological burden. This enables the user to receive prompt and appropriate medical services, and also realizes the appropriate provision of medicines and reduction of the user's psychological burden.

[0451] A "user terminal" is a communication device through which a user inputs symptom-related data and displays received information.

[0452] The "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state.

[0453] "Symptom data" is information that describes the user's symptoms, such as text, audio, images, and video.

[0454] "Medical interview information" is specific symptom information that is generated by analyzing received symptom-related data and is to be provided to a medical institution.

[0455] The "urgency" is an index for evaluating the seriousness of the user's symptoms, and is used to determine whether a prompt response is required.

[0456] "Medical institution" is a general term for medical facilities such as hospitals and clinics where users can receive medical treatment.

[0457] "Availability" is the process of checking whether the selected medical institution can accept the user for treatment.

[0458] "Pharmaceutical inventory status" refers to information about the quantity and types of pharmaceuticals held by pharmacies and drugstores.

[0459] "First aid" refers to emergency medical treatment that should be performed until the user arrives at a medical facility.

[0460] "Reducing psychological burden" means providing advice and support to ease the user's anxiety and tension.

[0461] This invention is a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, and in particular provides appropriate support to users by combining it with an emotion engine. This system is composed of a user terminal, a server, an emotion engine, a medical institution database, and a communication network.

[0462] The user terminal is a communication device such as a smartphone, tablet, or PC that the user uses to input symptom-related data. The symptom-related data can be provided in a variety of formats, including text input, voice input, images, and videos. The user terminal transmits the input data to a server via the Internet.

[0463] The server has a means for receiving data sent from the user terminal, analyzing it, and generating medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. Emotional information recognized by the emotion engine is also taken into account as part of the analysis, and the assessment of urgency and first aid advice are adapted to the user's emotional state, providing more appropriate support.

[0464] The server also has a means for selecting an appropriate medical institution based on the medical history information and emotion information. This selection refers to information in the medical institution database, taking into consideration information such as nearby medical departments, available beds, and the availability of specialists. The medical history information and emotion information are sent to the selected medical institution to confirm the possibility of treatment.

[0465] Once an available medical institution is identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, and arrival time of the medical institution that is most suitable for the user. It also provides the stock status of the necessary medicines to treat the user's symptoms. It also provides the user with first aid according to the level of urgency and advice to reduce psychological burden.

[0466] Specific examples

[0467] Example 1: When a child develops a high fever late at night

[0468] 1. User behavior

[0469] The user launches the app late at night and enters text about their child's symptoms (high fever, fatigue), then takes a photo of the rash and uploads it to the app. The app then uses its emotion engine to recognize the user's anxious facial expression and trembling voice.

[0470] 2. Operation on the terminal side

[0471] The device collects this data and sends it to a server over the Internet.

[0472] 3. Server-side operation

[0473] The server analyzes the received data and determines the urgency as "high" using an AI model. As the situation involves a high fever, it also incorporates information from the emotion engine to generate detailed interview results. As the situation is urgent and highly anxious, it immediately advises the user on how to cool down.

[0474] 4. Selection of medical institution

[0475] The server searches the database for hospitals with pediatric departments that are open at night, and sends the patient interview information and emotion information to multiple hospitals. After receiving responses from each hospital, the server selects the most appropriate hospital.

[0476] 5. Sending guidance information

[0477] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[0478] 6. Terminal operation

[0479] The terminal displays the information to the user, who then begins to take action towards the most suitable hospital.

[0480] Example 2: If you cut your hand on a holiday

[0481] 1. User behavior

[0482] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding or not, the degree of pain) in text. The app uses its emotion engine to recognize the user's state of tension.

[0483] 2. Operation on the terminal side

[0484] The device collects the data and sends it to a server over the internet.

[0485] 3. Server-side operation

[0486] The server analyzes the image and text data and uses an AI model to determine the level of urgency. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure. The system also takes into account information from the emotion engine, providing gentle, specific instructions.

[0487] 4. Selection of medical institution

[0488] The server searches for surgeries that are open even on holidays, and sends the patient's medical history and emotion information to multiple hospitals. After receiving responses from each hospital, the server selects the most suitable hospital.

[0489] 5. Sending guidance information

[0490] The server generates information about the selected hospital and sends it to the terminal.

[0491] 6. Terminal operation

[0492] The terminal displays the information, the user contacts the designated hospital, and the journey begins.

[0493] Prompt Sentence Examples

[0494] The user enters the following information into the app:

[0495] Symptoms: High fever and fatigue

[0496] Audio: Audio recording

[0497] Image:Facial image

[0498] System Response:

[0499] Urgency: High

[0500] First aid advice: Cooling recommended

[0501] Nearby pharmacy information: ____ pharmacy, ____ address

[0502] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0503] Step 1:

[0504] The user launches the smartphone application and inputs data about their symptoms. Specifically, they describe their symptoms using text, audio, images, or video, and if necessary, record their voice and take a photo of their face. This becomes the input data.

[0505] Step 2:

[0506] The device collects the data entered by the user and transmits it to a server over the Internet, including text data, audio files, and image files.

[0507] Step 3:

[0508] The server analyzes the received data. First, it analyzes the text data about symptoms using natural language processing (NLP) technology to generate medical interview information. This process uses a pre-trained AI model. This is part of the data processing. The output is the medical interview information.

[0509] Step 4:

[0510] Next, the server uses an emotion engine to analyze the user's facial expression data and voice data. OpenCV is used to analyze the facial expression data, extracting facial feature points and recognizing facial expressions. Librosa is used to analyze the voice data, extracting voice features and inputting them into an emotion recognition model. This allows the user's emotional state to be understood. The output is emotional information.

[0511] Step 5:

[0512] The server evaluates the urgency of the symptoms based on the medical interview information and emotional information. A pre-trained AI model is used to evaluate the urgency and determine the optimal response for the user's situation. This urgency information is generated.

[0513] Step 6:

[0514] The server selects an appropriate medical institution from a database of medical institutions based on the user's symptoms. It evaluates multiple hospitals, taking into account the user's location, medical specialty, available beds, and whether or not they have specialists. It creates a list of appropriate medical institutions and sends the medical interview information and emotion information to the selected medical institution. The output is a list of selected medical institutions.

[0515] Step 7:

[0516] The server collects information from medical institutions to confirm whether the patient can receive treatment, and then selects the most appropriate medical institution. This information includes the available dates and times for treatment and the hospital's availability. The output is the consultation confirmation information.

[0517] Step 8:

[0518] Once an available medical institution is identified, the server sends that information to the user's terminal. The user's terminal displays the name, address, contact information, and arrival time of the selected medical institution. It also displays stock information of medicines according to the user's symptoms. The output is the display information.

[0519] Step 9:

[0520] The server generates first aid advice according to the user's level of urgency and sends it to the user's device. For example, in the case of a high fever, it provides advice on cooling methods, and in the case of bleeding, it advises on pressure hemostasis. This allows the user to take immediate action. The output is first aid advice.

[0521] 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.

[0522] 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> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0523] 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.

[0524] [Second embodiment]

[0525] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0526] 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.

[0527] 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).

[0528] 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.

[0529] 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.

[0530] 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).

[0531] 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. 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.

[0532] 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.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0537] The present invention is a system that promptly guides patients to appropriate medical institutions for sudden illness or injury at night or on holidays. The basic configuration of this system includes a user terminal, a server, a medical institution database, and a communication network.

[0538] The user terminal is a communication device such as a smartphone, tablet, or PC that the user uses to input symptom data. The symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[0539] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. The medical interview information includes details of symptoms and an assessment of the urgency of the condition.

[0540] The server also selects an appropriate medical institution based on the medical interview information. To do this, it references information from the medical institution database and takes into account information such as nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution to confirm whether the patient can be seen.

[0541] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[0542] This system allows users to receive emergency medical services without spending time and effort, and also allows medical institutions to efficiently accept patients who are available for treatment.

[0543] Specific examples

[0544] Example 1: When a child develops a high fever late at night

[0545] 1. User behavior

[0546] Users launch the app late at night, enter their child's symptoms (high fever, fatigue) in text, and take a photo of the rash and upload it to the app.

[0547] 2. Operation on the terminal side

[0548] The device collects this data and sends it to a server via the Internet.

[0549] 3. Server-side operation

[0550] The server analyzes the received data and uses an AI model to determine the urgency as "high." Because the condition involves a high fever, a detailed medical interview is generated and the user is advised on cooling methods as first aid.

[0551] 4. Selection of medical institution

[0552] The server searches the database for hospitals with pediatric departments that are open at night, sends the medical interview information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[0553] 5. Sending guidance information

[0554] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[0555] 6. Terminal operation

[0556] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[0557] Example 2: If you cut your hand on a holiday

[0558] 1. User behavior

[0559] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding, how much pain there is) in text.

[0560] 2. Operation on the terminal side

[0561] The device collects data and sends it to a server via the internet.

[0562] 3. Server-side operation

[0563] The server analyzes the image and text data, and uses an AI model to determine the urgency of the situation. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure.

[0564] 4. Selection of medical institution

[0565] The server searches for surgeries that are open even on holidays, sends medical interview information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[0566] 5. Sending guidance information

[0567] The server generates information about the selected hospital and sends it to the terminal.

[0568] 6. Terminal operation

[0569] The device displays the information, the user contacts the designated hospital, and the journey begins.

[0570] In this way, this system provides a prompt and appropriate response to sudden illness or injury at night or on holidays, significantly reducing the burden on patients and medical institutions.

[0571] The processing flow will be explained below.

[0572] Step 1:

[0573] The user launches the app.

[0574] Step 2:

[0575] The user enters symptoms by text or voice.

[0576] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[0577] Step 3:

[0578] The device collects this data and sends it to a server over the Internet.

[0579] Step 4:

[0580] The server receives text, audio, image, and video data sent from the user terminal.

[0581] Step 5:

[0582] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[0583] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[0584] Step 6:

[0585] The server uses a generative AI model to generate medical interview information from the extracted information.

[0586] The server assesses the urgency and generates the necessary emergency response information.

[0587] Step 7:

[0588] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and urgency information.

[0589] The server lists multiple candidate medical institutions.

[0590] Step 8:

[0591] The server transmits the medical interview information to each selected medical institution and confirms whether the patient can receive treatment.

[0592] Step 9:

[0593] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[0594] Step 10:

[0595] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[0596] Step 11:

[0597] The server transmits the generated guidance information to the user terminal.

[0598] Step 12:

[0599] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[0600] Step 13:

[0601] The user follows the displayed guidance information and heads to the designated medical institution.

[0602] If necessary, the user can contact the medical institution using the displayed contact information.

[0603] Example 1

[0604] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0605] In modern society, when people suddenly become ill or injured at night or on holidays, it can be difficult to quickly find an appropriate medical institution. Furthermore, there is a risk that a patient's condition may worsen if appropriate initial treatment is delayed for highly urgent symptoms. There is a need for a method to solve these problems and provide prompt and appropriate medical institution guidance.

[0606] 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.

[0607] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data to generate medical interview information, means for evaluating the urgency of the condition, means for selecting an appropriate medical facility from a medical facility database and confirming the availability of medical treatment in cooperation with the selected medical facility, means for transmitting information on available medical facilities to the user terminal, and means for analyzing the data using an AI model, natural language processing technology, and image recognition technology. This enables the user to be quickly directed to an appropriate medical institution even if they suddenly become ill or injured at night or on a holiday.

[0608] A "user terminal" is a communication device that allows a user to input and receive data related to symptoms, and includes smartphones, tablets, personal computers, etc.

[0609] "Means for receiving data" refers to a mechanism by which the server receives symptom-related data sent from the user terminal.

[0610] "Means for generating medical interview information" refers to a mechanism by which the server analyzes the data received and generates the necessary information based on the patient's symptoms.

[0611] "Means for assessing urgency" refers to a mechanism for determining the urgency of a patient's symptoms based on analyzed data.

[0612] The "medical facility database" is a database that contains information on the medical departments, bed availability, and the availability of specialists at various medical facilities.

[0613] "Means to confirm availability of medical treatment in cooperation with medical facilities" refers to a system for sending medical interview information to selected medical facilities to confirm availability of medical treatment.

[0614] "Means for transmitting information to a user terminal" refers to a mechanism for transmitting information about selected medical facilities from a server to a user terminal.

[0615] An "AI model" refers to a mathematical model that uses artificial intelligence technology to analyze data and generate appropriate information and judgments.

[0616] "Natural language processing technology" refers to technology that analyzes, understands, and generates natural human language.

[0617] "Image recognition technology" refers to the technology of analyzing image data and extracting useful information from it.

[0618] This invention is a system that promptly guides users who suddenly become ill or injured at night or on holidays to appropriate medical institutions. This system includes a user terminal, a server, a medical facility database, and a communication network.

[0619] First, a user enters symptom data into the application using a user device such as a smartphone, tablet, or PC. Symptom data can be provided in a variety of formats, including text input, voice input, images, and videos. For example, a user might enter text about their child's high fever and fatigue late at night and upload a photo of the rash. This data is then sent to a server via the Internet.

[0620] The server receives data sent from the user's device and analyzes the symptom data using an AI model, natural language processing technology, and image recognition technology. The AI ​​model is a mathematical model that analyzes data and generates medical interview information. The natural language processing technology is a technology for analyzing text data and understanding symptoms. The image recognition technology is a technology for analyzing image data and extracting useful information from it.

[0621] For example, if the server analyzes data on "high fever" and "rash" and determines that these are related symptoms, it will assess the urgency as "high." Based on the analyzed data, medical interview information is generated and the urgency is assessed. At the same time, the server generates first aid advice as needed. In the case of high fever and rash, advice on "cooling methods" and "hydration intake" is provided.

[0622] Next, the server references a medical facility database and selects the medical facility that best suits the user's symptoms. The medical facility database contains information such as medical specialty, available beds, and whether or not there are specialists. The server then sends the medical interview information to the selected medical facility to confirm whether or not the patient can be seen. For example, the server selects several hospitals with pediatric departments that are open at night, and sends the medical interview information to each to confirm whether or not the patient can be seen.

[0623] Once a medical facility where the patient can be seen is confirmed, the server sends that information to the user's terminal. The user terminal displays this information to the user. The guidance information includes the name, address, contact information, and arrival time of the medical facility. For example, the user terminal displays something like, "Please contact XX Hospital (address: XX town, XX chome). Arrival time is approximately 15 minutes."

[0624] Examples of concrete examples and prompts

[0625] Example: If your child develops a high fever in the middle of the night

[0626] 1. User behavior: The user launches the app late at night, enters their child's symptoms (high fever, fatigue) in text, takes a photo of the rash, and uploads it to the app.

[0627] 2. Operation on the device side: The device collects data and sends it to a server via the Internet.

[0628] 3. Server-side operation: The server analyzes the received data, determines the urgency as "high," generates a medical interview result, and advises emergency measures.

[0629] 4. Selection of medical institution: The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals.

[0630] 5. Sending guidance information: The server sends information about the selected hospital to the terminal.

[0631] 6. Operation on the terminal side: The terminal displays the information, the user contacts the hospital, and begins the journey.

[0632] Prompt Sentence Examples

[0633] "Late at night, the user enters a text message about their child's high fever and uploads a photo of the rash to the app. The device collects the data and sends it to a server via the internet. The server analyzes the data, determines the urgency as 'high,' generates a medical interview result, and advises first aid. The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals. The server then sends the information of the selected hospital to the device. The device displays the information, and the user contacts the hospital."

[0634] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[0635] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0636] Step 1:

[0637] The user launches the system's application on a device such as a smartphone, tablet, or PC and enters detailed data about the symptoms.

[0638] Specific behavior:

[0639] The user enters text that they have a persistent high fever and feel very fatigued, takes a photo of the rash and uploads it to the app.

[0640] Input: Symptom data (text, images)

[0641] Output: Aggregated symptom data on the device

[0642] Step 2:

[0643] The user terminal transmits the input symptom data to a server via the Internet.

[0644] Specific behavior:

[0645] The smartphone collects text and image data and sends them to a server via a secure communication line.

[0646] Input: Symptom data collected on the device

[0647] Output: Symptom data sent to the server

[0648] Step 3:

[0649] The server receives the data sent from the user's device and analyzes it using AI models, natural language processing technology, and image recognition technology.

[0650] Specific behavior:

[0651] The server analyzes the data for "high fever" and "rash" and determines that these are related symptoms.

[0652] Input: Received symptom data

[0653] Output: Analyzed medical interview information (symptom classification, feature extraction)

[0654] Step 4:

[0655] The server generates medical interview information based on the analysis results and evaluates the urgency.

[0656] Specific behavior:

[0657] Based on cases of high fever and rash, advice is provided on "cooling methods" and "fluid intake."

[0658] Input: Parsed medical interview information

[0659] Output: Urgency assessment and advice

[0660] Step 5:

[0661] The server refers to a medical facility database and selects an appropriate medical facility.

[0662] Specific behavior:

[0663] The server selects multiple hospitals with pediatric departments that are open at night and transmits medical interview information to each hospital.

[0664] Input: Medical interview information, urgency assessment

[0665] Output: List of selected medical facilities

[0666] Step 6:

[0667] The server sends the medical interview information to the selected medical facility and checks whether the patient can be seen.

[0668] Specific behavior:

[0669] After receiving responses from each hospital, the most appropriate hospital will be selected.

[0670] Input: List of selected medical facilities, medical history information

[0671] Output: Check results for available medical facilities

[0672] Step 7:

[0673] Once the medical facility where the patient can be seen is confirmed, the server transmits the information to the user terminal.

[0674] Specific behavior:

[0675] The server generates a message saying, "Please contact XX Hospital (address: XX-cho XX-chome). Arrival time is approximately 15 minutes," and sends it to the user terminal.

[0676] Input: Confirmation result of available medical facilities

[0677] Output: Medical facility information sent to the user's device

[0678] Step 8:

[0679] The user terminal displays the received information about the medical facility to the user.

[0680] Specific behavior:

[0681] The smartphone displays detailed information about medical facilities on the screen, and the user follows the instructions to head to the hospital.

[0682] Input: Received medical facility information

[0683] Output: Medical facility information displayed on the screen

[0684] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[0685] (Application example 1)

[0686] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0687] While there are systems in place that can quickly guide patients to the appropriate medical institution in the event of sudden illness or injury at night or on holidays, there are no systems that take into account the patient's nutritional status or the provision of food for first aid. This can lead to patients being unable to select appropriate foods, resulting in insufficient nutrition. Medical institutions also have to work hard to provide food according to the patient's condition. Therefore, there is a need for a system that allows patients to quickly obtain information on both the appropriate medical institution and food, and to ensure appropriate nutritional management.

[0688] 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.

[0689] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data and generating medical interview information, means for selecting an appropriate medical institution affiliated organization based on the medical interview information and confirming the availability of medical treatment in cooperation with the medical institution affiliated organization, means for selecting optimal foods based on the availability of medical treatment by the medical institution affiliated organization, and means for transmitting information on available medical institution affiliated organizations and optimal food information to the user terminal, thereby enabling patients to quickly obtain information on both appropriate medical institutions and foods.

[0690] A "user terminal" is a communication device that allows a user to input data about symptoms and transmit the data to a server.

[0691] "Symptom Data" is information about a medical condition or injury a user is experiencing, provided in the form of text, images, video, or other information.

[0692] The "medical interview information" is information generated by the server by analyzing data on symptoms received from the user, and includes details of the symptoms and an assessment of the urgency of the symptoms.

[0693] The "medical institution affiliated organization" is a medical institution that the server selects based on the medical interview information and collaborates with to confirm the possibility of receiving medical treatment.

[0694] "Accessibility" is information indicating whether the selected medical institution affiliated organization can actually accept the patient.

[0695] "Optimal foods" are nutritionally balanced foods and drinks selected based on the user's symptoms.

[0696] "Appropriate food information" is detailed information about the most suitable food selected by the server and provided to the user.

[0697] This invention is a system that provides prompt and appropriate information on both medical institutions and food when a user suddenly becomes ill or injured at night or on a holiday. Specific methods for realizing this system are described below.

[0698] First, a user uses a user device such as a smartphone to input data about their symptoms. This data is provided in the form of text input, voice input, images, videos, etc. For example, if a user complains of a symptom of "high fever," they can input the symptoms in text and upload a photo of their face showing a high fever.

[0699] The user device then collects this data and sends it over the Internet to a server, which is built using the Flask framework and receives the data sent from the user device.

[0700] The server analyzes the received data and generates medical interview information. This analysis uses generative AI models, natural language processing technology, and image recognition technology. This allows the server to evaluate the details and urgency of symptoms and create specific medical interview information.

[0701] Next, the server selects an appropriate medical institution affiliated with the patient based on the generated medical interview information. It references information from the medical institution affiliated organization database and considers nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution affiliated with the patient to confirm whether the patient can be seen.

[0702] The server then selects the most appropriate food based on the patient's symptoms. This selection is done using a generative AI model based on the patient's symptoms. For example, if the patient has a high fever, appropriate foods such as porridge or soup will be selected.

[0703] Finally, the server sends information about affiliated medical institutions where patients can receive treatment, as well as information about the most suitable foods, to the user's device. Based on this information, the user's device guides the user on the most suitable course of action. Based on this guidance, the user can head to the appropriate medical institution and simultaneously order the appropriate foods.

[0704] (Example)

[0705] Example 1: When a user's child develops a high fever late at night

[0706] Users launch the app, type in the text "high fever," and then upload a photo of their face showing a high fever.

[0707] The server receives the data, analyzes it, and generates medical interview information. The urgency level is determined to be "high."

[0708] The server selects affiliated medical institutions with pediatric departments that are available for consultation and sends the information to the user's device. It also recommends "porridge" or "soup."

[0709] The user follows the guidance information and orders porridge for delivery on their way to the medical institution.

[0710] Example 2: If the user cuts their hand on a holiday

[0711] The user launches the app, takes a photo of the wound on their hand, and enters the bleeding status in text.

[0712] The server receives the data, analyzes it, and then generates medical interview information. As first aid, the doctor advises applying pressure to stop the bleeding.

[0713] The server selects a surgery that is open even on holidays and sends the information to the user's terminal. It also recommends appropriate foods for nutritional support.

[0714] The user follows the guidance information and orders the recommended food for delivery while heading to the medical institution.

[0715] (Example of a prompt)

[0716] "Please list foods that you recommend for high fever symptoms."

[0717] "Please tell me how to provide first aid for bleeding hands."

[0718] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0719] Step 1:

[0720] A user launches a smartphone app and inputs data about their symptoms. The input data includes textual symptom descriptions, voice input, images, and videos. For example, a user might input the symptom "high fever" in text and upload a photo of their face. In this case, the user's input becomes input data for the system.

[0721] Step 2:

[0722] The device collects data entered by the user and sends it to a server via the internet. The input data includes text, audio, images, and video detailing the symptoms. This is the data collection process on the device side. The output of the device is the data sent to the server.

[0723] Step 3:

[0724] The server receives the data sent from the device. It analyzes the received data and generates medical interview information using generative AI models, natural language processing (NLP), and image recognition technology. For example, the server analyzes the received image using image recognition technology, determines the details of a high fever, and evaluates the urgency as "high." The input is data from the device, and the output is the generated medical interview information.

[0725] Step 4:

[0726] The server selects an appropriate medical institution affiliated organization based on the medical interview information generated by the server. The server references a database of medical institution affiliated organizations and makes the selection taking into consideration information such as medical departments in the user's vicinity, available hospital beds, and the availability of specialists. For example, it selects a pediatric clinic that is open late at night. The input is the medical interview information, and the output is information on the selected medical institution affiliated organization.

[0727] Step 5:

[0728] The medical interview information is sent to the selected medical institution affiliated organizations to confirm the possibility of receiving medical treatment. Specifically, the server sends the medical interview information to each medical institution affiliated organization and waits for a response from each medical institution affiliated organization. The input is a list of medical institution affiliated organizations and the medical interview information, and the output is the confirmed possibility of receiving medical treatment information.

[0729] Step 6:

[0730] The server selects the most appropriate food based on the confirmed likelihood of medical treatment. In this process, the generative AI model recommends appropriate foods based on the symptoms. For example, in the case of a high fever, "porridge" or "soup" is recommended. The input is medical interview information about the symptoms, and the output is a list of appropriate foods.

[0731] Step 7:

[0732] Information on affiliated medical institutions where patients can be seen and information on optimal foods is sent to the user's terminal. The server sends all information together to the user's terminal, making it immediately available to the user. For example, in addition to the name, address, and contact information of the pediatric clinic the user should visit, "porridge" is displayed as a recommended food. The input is the confirmed information on availability of medical treatment and food information, and the output is guidance information sent to the user's terminal.

[0733] Step 8:

[0734] The user begins to act based on the information received. The user checks the guidance information and heads to the medical institution, while simultaneously ordering the recommended food from a delivery service. For example, the user can easily order "porridge" from the app and request delivery. The input is the guidance information sent to the user's device, and the output is the user's actions and food order.

[0735] 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.

[0736] This invention is a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it implements a means for providing the user with more appropriate support. The basic configuration of this system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network.

[0737] The user terminal is a communication device such as a smartphone, tablet, or PC, which the user uses to input symptom data. The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state. Symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[0738] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. Emotional information recognized by an emotion engine is also taken into account as part of the analysis. This allows the assessment of urgency and first aid advice to be adapted to the user's emotional state, providing more appropriate support.

[0739] The server then selects an appropriate medical institution based on the medical history information and emotion information. This selection refers to information in the medical institution database, taking into account nearby medical departments, available beds, the availability of specialists, and other information. The medical history information and emotion information are then sent to the selected medical institution to confirm whether the patient can be seen.

[0740] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[0741] This system allows users to receive emergency medical services without spending time and effort, and allows medical institutions to efficiently accept patients who can be seen. In addition, by responding to the user's emotions, it reduces the user's psychological burden and provides more appropriate medical services.

[0742] Specific examples

[0743] Example 1: When a child develops a high fever late at night

[0744] 1. User behavior

[0745] The user launches the app late at night and enters text about their child's symptoms (high fever, fatigue), then takes a photo of the rash and uploads it to the app. The app then uses its emotion engine to recognize the user's anxious expression and trembling voice.

[0746] 2. Operation on the terminal side

[0747] The device collects this data and sends it to a server via the Internet.

[0748] 3. Server-side operation

[0749] The server analyzes the received data and determines the urgency as "high" using an AI model. Since the situation involves a high fever, the emotion engine also incorporates information from the model to generate detailed interview results. Because the situation is urgent and highly anxious, the system immediately advises the user on how to cool down the situation.

[0750] 4. Selection of medical institution

[0751] The server searches the database for hospitals with pediatric departments that are open at night, sends the patient interview information and emotion information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[0752] 5. Sending guidance information

[0753] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[0754] 6. Terminal operation

[0755] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[0756] Example 2: If you cut your hand on a holiday

[0757] 1. User behavior

[0758] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding or not, the degree of pain) in text. The app uses its emotion engine to recognize the user's state of tension.

[0759] 2. Operation on the terminal side

[0760] The device collects data and sends it to a server via the internet.

[0761] 3. Server-side operation

[0762] The server analyzes the image and text data and uses an AI model to determine the level of urgency. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure. The system also takes into account information from the emotion engine, providing gentle, specific instructions.

[0763] 4. Selection of medical institution

[0764] The server searches for surgeries that are open even on holidays, sends medical interview information and emotion information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[0765] 5. Sending guidance information

[0766] The server generates information about the selected hospital and sends it to the terminal.

[0767] 6. Terminal operation

[0768] The device displays the information, the user contacts the designated hospital, and the journey begins.

[0769] In this way, by combining this system with an emotion engine, it is possible to reduce the psychological burden on users and enable more appropriate responses, thereby providing prompt and appropriate medical support while also reducing stress and anxiety for users.

[0770] The processing flow will be explained below.

[0771] Step 1:

[0772] The user launches the app.

[0773] Step 2:

[0774] The user enters symptoms by text or voice.

[0775] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[0776] Step 3:

[0777] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0778] For example, identifying emotions such as anxiety or tension.

[0779] Step 4:

[0780] The device collects symptom data (text, audio, images, video) and emotional information and sends it to a server via the Internet.

[0781] Step 5:

[0782] The server receives the data sent from the user terminal.

[0783] Step 6:

[0784] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[0785] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[0786] The server also analyzes the emotion information from the emotion engine.

[0787] Step 7:

[0788] The server uses a generative AI model to generate medical interview information from the extracted information (symptom data, emotion data).

[0789] The server evaluates the urgency and generates the necessary emergency measures, taking emotional information into consideration to provide appropriate advice.

[0790] Step 8:

[0791] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and emotion information.

[0792] The server lists multiple candidate medical institutions.

[0793] Step 9:

[0794] The server transmits the medical interview information and emotion information to each selected medical institution to confirm the possibility of receiving treatment.

[0795] Step 10:

[0796] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[0797] Step 11:

[0798] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[0799] Step 12:

[0800] The server transmits the generated guidance information to the user terminal.

[0801] Step 13:

[0802] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[0803] The device provides the user with information including additional first aid measures and precautions that take emotions into consideration.

[0804] Step 14:

[0805] The user follows the displayed guidance information and heads to the designated medical institution.

[0806] If necessary, the user can contact the medical institution using the displayed contact information.

[0807] Specific examples

[0808] Example 1: When a child develops a high fever late at night

[0809] 1. Step 1: A user launches the app late at night.

[0810] 2. Step 2: The user enters a text description of their child's symptoms (high fever, fatigue) and takes and uploads a photo of the rash.

[0811] 3. Step 3: The emotion engine recognizes the user's anxious facial expression and trembling voice.

[0812] 4. Step 4: The device sends this data (text, images, and emotional information) to the server.

[0813] 5. Step 5: The server receives the data.

[0814] 6. Step 6: The server analyzes the text data, inspects the images, and captures the user's emotional information.

[0815] 7. Step 7: The server determines the urgency to be "high" and the situation involves a high fever, so it generates detailed medical interview results and presents first aid measures (cooling methods).

[0816] 8. Step 8: The server searches the database for pediatricians who are available for overnight consultations and creates a list of candidates.

[0817] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[0818] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[0819] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[0820] 12. Step 12: The server sends the guidance information to the user terminal.

[0821] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[0822] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[0823] Example 2: If you cut your hand on a holiday

[0824] 1. Step 1: The user launches the app.

[0825] 2. Step 2: The user takes a photo of the wound on their hand and reports the extent of bleeding and pain in text.

[0826] 3. Step 3: The emotion engine recognizes the user's state of tension.

[0827] 4. Step 4: The device sends data (text, images, and emotional information) to the server.

[0828] 5. Step 5: The server receives the data.

[0829] 6. Step 6: The server analyzes the image and text data and captures emotional information.

[0830] 7. Step 7: The server determines the urgency to be "medium" and gently and specifically suggests first aid measures (pressure hemostasis).

[0831] 8. Step 8: The server searches for surgeries that are open on holidays and creates a candidate list.

[0832] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[0833] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[0834] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[0835] 12. Step 12: The server sends the guidance information to the user terminal.

[0836] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[0837] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[0838] Example 2

[0839] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0840] In modern society, there is a need for a system that enables users to seek medical attention quickly and appropriately when they suddenly become ill or injured at night or on holidays. However, it can be difficult for users, especially those who are emotionally upset, to find the most appropriate medical institution and complete the procedures for seeking medical attention. For this reason, a support system is needed that recognizes the user's emotional state and provides appropriate responses, allowing users to seek medical attention quickly and with peace of mind.

[0841] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving symptom-related data from a user terminal, means for analyzing the received data and generating medical interview information, and means for selecting an appropriate medical institution based on the medical interview information and emotional information using a generative AI model, and for confirming the possibility of receiving medical treatment in cooperation with the medical institution via a communication network. This allows the user to quickly find the most appropriate medical institution, and further allows the user to feel at ease when starting to seek medical treatment by receiving advice on first aid that takes emotional information into consideration.

[0842] A "user terminal" is an electronic device that allows a user to input data about symptoms and transmit the data to a server via a communication network.

[0843] "Symptom data" refers to information that indicates the state of illness or injury of the user or a third party, and may be in the form of text, images, video, audio, or the like.

[0844] The "receiving means" is a mechanism by which the server receives data transmitted from the user terminal via the communication network.

[0845] "Medical interview information" is information necessary for medical treatment obtained by analyzing received symptom data.

[0846] The "means for confirming availability for medical treatment" is a mechanism by which the server sends medical interview information to an appropriate medical institution and confirms whether or not the medical institution is available for medical treatment.

[0847] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to generate emotional information.

[0848] "Emotion information" is information obtained by analyzing the user's emotional state using an emotion engine.

[0849] The "means for selecting an appropriate medical institution" is a mechanism for identifying the most suitable medical institution for a user based on medical interview information and emotional information.

[0850] "Communications Network" means the Internet or other communications infrastructure used to transmit and receive data.

[0851] "First aid advice" is a temporary solution that the server provides to the user based on the analysis results and the urgency assessment.

[0852] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and generate emotional information.

[0853] The present invention provides a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately. This support system is particularly equipped with an emotion engine that recognizes the user's emotions, and is further equipped with a means for providing appropriate support to the user. The following describes in detail an embodiment of the present invention.

[0854] Basic configuration

[0855] The basic configuration of the system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network. User terminals can be communication devices such as smartphones, tablets, and PCs. The emotion engine is used to recognize the user's emotional state by analyzing their facial expressions and vocal tone. Data is sent and received via the Internet.

[0856] User terminal

[0857] Users use a smartphone, tablet, or PC with a dedicated application installed. The user device provides an interface for inputting symptom data. This data can include text input, voice input, images, and videos, allowing users to provide information in an appropriate format. The system also incorporates an emotion engine that generates emotional information by analyzing facial expressions and tone of voice when the user describes their symptoms.

[0858] server

[0859] The server uses high-performance hardware and analyzes data using AI models, natural language processing (NLP), and image recognition technology. When the server receives data sent from the user's device, it begins analysis and generates medical interview information and emotional information. This allows the server to assess the urgency of the symptoms and provide first aid advice if necessary.

[0860] Emotion Engine

[0861] The emotion engine is software that analyzes the user's facial expressions and tone of voice to generate emotional information, which determines whether the user is feeling anxious or nervous, and responds accordingly.

[0862] Selection of medical institutions

[0863] The server selects an appropriate medical institution based on the medical interview information and emotion information generated by the server. This selection refers to information in the medical institution database, taking into account information such as medical departments, available beds, and the availability of specialists. The server sends the medical interview information and emotion information to the medical institution and confirms the possibility of treatment.

[0864] Providing guidance information

[0865] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the most suitable medical institution to the user. Contact information is also provided so that the user can contact the medical institution directly.

[0866] Specific examples

[0867] Example 1: When a child develops a high fever late at night

[0868] 1. A user launches the app late at night and enters their child's symptoms (high fever, fatigue) in text. They also upload a photo of the rash to the app.

[0869] 2. The emotion engine recognizes the user's anxious facial expression and trembling voice.

[0870] 3. The server receives this data and determines the urgency as "high."

[0871] 4. The server searches for multiple hospitals with pediatric departments that are open at night and selects the most suitable hospital.

[0872] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[0873] Example 2: If you cut your hand on a holiday

[0874] 1. The user launches the app, takes a photo of the cut on their hand, and reports via text whether there is bleeding and the degree of pain.

[0875] 2. The emotion engine recognizes the user's state of tension.

[0876] 3. The server receives this data, analyzes it, and advises the patient to apply pressure to stop bleeding if there is bleeding.

[0877] 4. The server searches for surgeries that are open even on holidays and selects the most suitable hospital.

[0878] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[0879] In this way, by utilizing generative AI models and emotion engines, the system of the present invention can reduce the psychological burden on users and provide prompt and appropriate medical support.

[0880] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0881] Step 1:

[0882] Entering Symptom Information

[0883] User actions: The user launches the app on a device on which the dedicated application is installed and enters symptom data using the symptom input interface.

[0884] Input: Symptom text, audio, image, and video data.

[0885] Output: The input data is saved in the device.

[0886] What happens: A user types in "high fever" and takes and uploads a photo of a rash.

[0887] Step 2:

[0888] Emotional information generation

[0889] Device operation: The emotion engine analyzes the user's facial expressions and tone of voice to generate emotional information.

[0890] Input: User facial and voice data.

[0891] Output: Data indicating the user's emotional state.

[0892] Specific operation: The device takes a picture of the user's face with a camera, analyzes their emotional state (e.g., anxiety) from their facial expression, and saves it as data.

[0893] Step 3:

[0894] Sending data

[0895] Device operation: The device collects and analyzes symptom data and emotional information, which are then sent to a server via the Internet.

[0896] Input: Symptom data, emotion information.

[0897] Output: Data sent to server completed.

[0898] Specific operation: When the device presses the "send" button, data is sent to the server via the Internet.

[0899] Step 4:

[0900] Receiving data

[0901] Server operation: The server receives the data sent from the user terminal.

[0902] Input: Symptom data, emotion information.

[0903] Output: The received data is stored in the server.

[0904] Specific operation: The server periodically checks for data reception and saves any new data.

[0905] Step 5:

[0906] Data analysis

[0907] Server operation: The server analyzes the received symptom data and generates medical interview information. At the same time, it analyzes emotional information.

[0908] Input: Received symptom data, emotion information.

[0909] Output: Interview information, emotion evaluation results.

[0910] How it works: The AI ​​model analyzes text data using natural language processing technology to detect "high fever," and uses image recognition technology to identify "rash" and assess its urgency.

[0911] Step 6:

[0912] Urgency assessment and first aid advice

[0913] Server operation: Evaluate the urgency of the symptoms based on the analysis results and generate first aid advice.

[0914] Input: Interview information, emotion assessment results.

[0915] Output: Urgency assessment result, first aid advice.

[0916] Specific behavior: If the evaluation result is "Urgency: High," advice such as "Use a cooling towel" is generated.

[0917] Step 7:

[0918] Selection of medical institutions

[0919] Server operation: The server refers to the medical institution database and selects an appropriate medical institution based on the medical interview information and emotion information.

[0920] Input: Interview information, emotion assessment results.

[0921] Output: Information on selected medical institutions.

[0922] Specific operation: The server searches for pediatric hospitals that are open at night and obtains information on multiple medical institutions.

[0923] Step 8:

[0924] Checking availability for medical examination

[0925] Server operation: Sends medical interview information and emotion information to the selected medical institution to confirm the possibility of receiving treatment.

[0926] Input: Information on the selected medical institution, medical interview information, and emotion assessment results.

[0927] Output: A list of available medical facilities.

[0928] Specific operation: Check the response from each medical institution regarding the availability of treatment and determine the most suitable medical institution.

[0929] Step 9:

[0930] Generating guidance information

[0931] Server operation: Once available medical institutions are confirmed, guidance information is generated.

[0932] Input: Information about medical institutions where you can receive treatment.

[0933] Output: Guidance information.

[0934] Specific operation: The server generates a package containing the name, address, contact information, and arrival time of the medical institution.

[0935] Step 10:

[0936] Sending guidance information

[0937] Server operation: Sends guidance information to the user terminal.

[0938] Input: Guidance information.

[0939] Output: Data sent to user terminal.

[0940] Specific operation: The server sends guidance information to the user terminal via the Internet.

[0941] Step 11:

[0942] Displaying information and encouraging action

[0943] Terminal operation: The user terminal displays the guidance information received and prompts the user to take action.

[0944] Input: Received information.

[0945] Output: The clinic information displayed to the user.

[0946] What it does: The app displays, "The nearest pediatric clinic is XX Hospital. The address is XX and the reach time is approximately 15 minutes." and also makes the contact information clickable.

[0947] (Application example 2)

[0948] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0949] In order to enable users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, it is necessary to provide a system that can reduce the psychological burden on users and provide appropriate medicines and first aid advice.However, current medical support systems have the problem of being unable to provide appropriate responses that take into account the user's emotional state.

[0950] The identification process by the identification 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 means for receiving symptom-related data from a user terminal, means for analyzing the received data to generate medical interview information, means for analyzing the user's facial expression and tone of voice using an emotion engine to determine the level of urgency, means for selecting an appropriate medical institution based on the medical interview information and confirming the availability of medical treatment in cooperation with that medical institution, means for transmitting information about available medical institutions to the user terminal, means for providing the user with the inventory status of necessary medicines for the user's symptoms, and means for providing the user with first aid according to the level of urgency and advice to reduce psychological burden. This enables the user to receive prompt and appropriate medical services, and also realizes the appropriate provision of medicines and reduction of the user's psychological burden.

[0951] A "user terminal" is a communication device through which a user inputs symptom-related data and displays received information.

[0952] The "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state.

[0953] "Symptom data" is information that describes the user's symptoms, such as text, audio, images, and video.

[0954] "Medical interview information" is specific symptom information that is generated by analyzing received symptom-related data and is to be provided to a medical institution.

[0955] The "urgency" is an index for evaluating the seriousness of the user's symptoms, and is used to determine whether a prompt response is required.

[0956] "Medical institution" is a general term for medical facilities such as hospitals and clinics where users can receive medical treatment.

[0957] "Availability" is the process of checking whether the selected medical institution can accept the user for treatment.

[0958] "Pharmaceutical inventory status" refers to information about the quantity and types of pharmaceuticals held by pharmacies and drugstores.

[0959] "First aid" refers to emergency medical treatment that should be performed until the user arrives at a medical facility.

[0960] "Reducing psychological burden" means providing advice and support to ease the user's anxiety and tension.

[0961] This invention is a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, and in particular provides appropriate support to users by combining it with an emotion engine. This system is composed of a user terminal, a server, an emotion engine, a medical institution database, and a communication network.

[0962] The user terminal is a communication device such as a smartphone, tablet, or PC that the user uses to input symptom-related data. The symptom-related data can be provided in a variety of formats, including text input, voice input, images, and videos. The user terminal transmits the input data to a server via the Internet.

[0963] The server has a means for receiving data sent from the user terminal, analyzing it, and generating medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. Emotional information recognized by the emotion engine is also taken into account as part of the analysis, and the assessment of urgency and first aid advice are adapted to the user's emotional state, providing more appropriate support.

[0964] The server also has a means for selecting an appropriate medical institution based on the medical history information and emotion information. This selection refers to information in the medical institution database, taking into consideration information such as nearby medical departments, available beds, and the availability of specialists. The medical history information and emotion information are sent to the selected medical institution to confirm the possibility of treatment.

[0965] Once an available medical institution is identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, and arrival time of the medical institution that is most suitable for the user. It also provides the stock status of the necessary medicines to treat the user's symptoms. It also provides the user with first aid according to the level of urgency and advice to reduce psychological burden.

[0966] Specific examples

[0967] Example 1: When a child develops a high fever late at night

[0968] 1. User behavior

[0969] The user launches the app late at night and enters text about their child's symptoms (high fever, fatigue), then takes a photo of the rash and uploads it to the app. The app then uses its emotion engine to recognize the user's anxious facial expression and trembling voice.

[0970] 2. Operation on the terminal side

[0971] The device collects this data and sends it to a server over the Internet.

[0972] 3. Server-side operation

[0973] The server analyzes the received data and determines the urgency as "high" using an AI model. As the situation involves a high fever, it also incorporates information from the emotion engine to generate detailed interview results. As the situation is urgent and highly anxious, it immediately advises the user on how to cool down.

[0974] 4. Selection of medical institution

[0975] The server searches the database for hospitals with pediatric departments that are open at night, and sends the patient interview information and emotion information to multiple hospitals. After receiving responses from each hospital, the server selects the most appropriate hospital.

[0976] 5. Sending guidance information

[0977] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[0978] 6. Terminal operation

[0979] The terminal displays the information to the user, who then begins to take action towards the most suitable hospital.

[0980] Example 2: If you cut your hand on a holiday

[0981] 1. User behavior

[0982] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding or not, the degree of pain) in text. The app uses its emotion engine to recognize the user's state of tension.

[0983] 2. Operation on the terminal side

[0984] The device collects the data and sends it to a server over the internet.

[0985] 3. Server-side operation

[0986] The server analyzes the image and text data and uses an AI model to determine the level of urgency. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure. The system also takes into account information from the emotion engine, providing gentle, specific instructions.

[0987] 4. Selection of medical institution

[0988] The server searches for surgeries that are open even on holidays, and sends the patient's medical history and emotion information to multiple hospitals. After receiving responses from each hospital, the server selects the most suitable hospital.

[0989] 5. Sending guidance information

[0990] The server generates information about the selected hospital and sends it to the terminal.

[0991] 6. Terminal operation

[0992] The terminal displays the information, the user contacts the designated hospital, and the journey begins.

[0993] Prompt Sentence Examples

[0994] The user enters the following information into the app:

[0995] Symptoms: High fever and fatigue

[0996] Audio: Audio recording

[0997] Image:Facial image

[0998] System Response:

[0999] Urgency: High

[1000] First aid advice: Cooling recommended

[1001] Nearby pharmacy information: ____ pharmacy, ____ address

[1002] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1003] Step 1:

[1004] The user launches the smartphone application and inputs data about their symptoms. Specifically, they describe their symptoms using text, audio, images, or video, and if necessary, record their voice and take a photo of their face. This becomes the input data.

[1005] Step 2:

[1006] The device collects the data entered by the user and transmits it to a server over the Internet, including text data, audio files, and image files.

[1007] Step 3:

[1008] The server analyzes the received data. First, it analyzes the text data about symptoms using natural language processing (NLP) technology to generate medical interview information. This process uses a pre-trained AI model. This is part of the data processing. The output is the medical interview information.

[1009] Step 4:

[1010] Next, the server uses an emotion engine to analyze the user's facial expression data and voice data. OpenCV is used to analyze the facial expression data, extracting facial feature points and recognizing facial expressions. Librosa is used to analyze the voice data, extracting voice features and inputting them into an emotion recognition model. This allows the user's emotional state to be understood. The output is emotional information.

[1011] Step 5:

[1012] The server evaluates the urgency of the symptoms based on the medical interview information and emotional information. A pre-trained AI model is used to evaluate the urgency and determine the optimal response for the user's situation. This urgency information is generated.

[1013] Step 6:

[1014] The server selects an appropriate medical institution from a database of medical institutions based on the user's symptoms. It evaluates multiple hospitals, taking into account the user's location, medical specialty, available beds, and whether or not they have specialists. It creates a list of appropriate medical institutions and sends the medical interview information and emotion information to the selected medical institution. The output is a list of selected medical institutions.

[1015] Step 7:

[1016] The server collects information from medical institutions to confirm whether the patient can receive treatment, and then selects the most appropriate medical institution. This information includes the available dates and times for treatment and the hospital's availability. The output is the consultation confirmation information.

[1017] Step 8:

[1018] Once an available medical institution is identified, the server sends that information to the user's terminal. The user's terminal displays the name, address, contact information, and arrival time of the selected medical institution. It also displays stock information of medicines according to the user's symptoms. The output is the display information.

[1019] Step 9:

[1020] The server generates first aid advice according to the user's level of urgency and sends it to the user's device. For example, in the case of a high fever, it provides advice on cooling methods, and in the case of bleeding, it advises on pressure hemostasis. This allows the user to take immediate action. The output is first aid advice.

[1021] 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.

[1022] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1023] 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.

[1024] [Third embodiment]

[1025] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1026] 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.

[1027] 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).

[1028] 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.

[1029] 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.

[1030] 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).

[1031] 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. 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.

[1032] 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.

[1033] 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.

[1034] 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.

[1035] 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.

[1036] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1037] The present invention is a system that promptly guides patients to appropriate medical institutions for sudden illness or injury at night or on holidays. The basic configuration of this system includes a user terminal, a server, a medical institution database, and a communication network.

[1038] The user terminal is a communication device such as a smartphone, tablet, or PC that the user uses to input symptom data. The symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[1039] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. The medical interview information includes details of symptoms and an assessment of the urgency of the condition.

[1040] The server also selects an appropriate medical institution based on the medical interview information. To do this, it references information from the medical institution database and takes into account information such as nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution to confirm whether the patient can be seen.

[1041] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[1042] This system allows users to receive emergency medical services without spending time and effort, and also allows medical institutions to efficiently accept patients who are available for treatment.

[1043] Specific examples

[1044] Example 1: When a child develops a high fever late at night

[1045] 1. User behavior

[1046] Users launch the app late at night, enter their child's symptoms (high fever, fatigue) in text, and take a photo of the rash and upload it to the app.

[1047] 2. Operation on the terminal side

[1048] The device collects this data and sends it to a server via the Internet.

[1049] 3. Server-side operation

[1050] The server analyzes the received data and uses an AI model to determine the urgency as "high." Because the condition involves a high fever, a detailed medical interview is generated and the user is advised on cooling methods as first aid.

[1051] 4. Selection of medical institution

[1052] The server searches the database for hospitals with pediatric departments that are open at night, sends the medical interview information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[1053] 5. Sending guidance information

[1054] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[1055] 6. Terminal operation

[1056] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[1057] Example 2: If you cut your hand on a holiday

[1058] 1. User behavior

[1059] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding, how much pain there is) in text.

[1060] 2. Operation on the terminal side

[1061] The device collects data and sends it to a server via the internet.

[1062] 3. Server-side operation

[1063] The server analyzes the image and text data, and uses an AI model to determine the urgency of the situation. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure.

[1064] 4. Selection of medical institution

[1065] The server searches for surgeries that are open even on holidays, sends medical interview information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[1066] 5. Sending guidance information

[1067] The server generates information about the selected hospital and sends it to the terminal.

[1068] 6. Terminal operation

[1069] The device displays the information, the user contacts the designated hospital, and the journey begins.

[1070] In this way, this system provides a prompt and appropriate response to sudden illness or injury at night or on holidays, significantly reducing the burden on patients and medical institutions.

[1071] The processing flow will be explained below.

[1072] Step 1:

[1073] The user launches the app.

[1074] Step 2:

[1075] The user enters symptoms by text or voice.

[1076] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[1077] Step 3:

[1078] The device collects this data and sends it to a server over the Internet.

[1079] Step 4:

[1080] The server receives text, audio, image, and video data sent from the user terminal.

[1081] Step 5:

[1082] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[1083] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[1084] Step 6:

[1085] The server uses a generative AI model to generate medical interview information from the extracted information.

[1086] The server assesses the urgency and generates the necessary emergency response information.

[1087] Step 7:

[1088] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and urgency information.

[1089] The server lists multiple candidate medical institutions.

[1090] Step 8:

[1091] The server transmits the medical interview information to each selected medical institution and confirms whether the patient can receive treatment.

[1092] Step 9:

[1093] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[1094] Step 10:

[1095] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[1096] Step 11:

[1097] The server transmits the generated guidance information to the user terminal.

[1098] Step 12:

[1099] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[1100] Step 13:

[1101] The user follows the displayed guidance information and heads to the designated medical institution.

[1102] If necessary, the user can contact the medical institution using the displayed contact information.

[1103] Example 1

[1104] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1105] In modern society, when people suddenly become ill or injured at night or on holidays, it can be difficult to quickly find an appropriate medical institution. Furthermore, there is a risk that a patient's condition may worsen if appropriate initial treatment is delayed for highly urgent symptoms. There is a need for a method to solve these problems and provide prompt and appropriate medical institution guidance.

[1106] 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.

[1107] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data to generate medical interview information, means for evaluating the urgency of the condition, means for selecting an appropriate medical facility from a medical facility database and confirming the availability of medical treatment in cooperation with the selected medical facility, means for transmitting information on available medical facilities to the user terminal, and means for analyzing the data using an AI model, natural language processing technology, and image recognition technology. This enables the user to be quickly directed to an appropriate medical institution even if they suddenly become ill or injured at night or on a holiday.

[1108] A "user terminal" is a communication device that allows a user to input and receive data related to symptoms, and includes smartphones, tablets, personal computers, etc.

[1109] "Means for receiving data" refers to a mechanism by which the server receives symptom-related data sent from the user terminal.

[1110] "Means for generating medical interview information" refers to a mechanism by which the server analyzes the data received and generates the necessary information based on the patient's symptoms.

[1111] "Means for assessing urgency" refers to a mechanism for determining the urgency of a patient's symptoms based on analyzed data.

[1112] The "medical facility database" is a database that contains information on the medical departments, bed availability, and the availability of specialists at various medical facilities.

[1113] "Means to confirm availability of medical treatment in cooperation with medical facilities" refers to a system for sending medical interview information to selected medical facilities to confirm availability of medical treatment.

[1114] "Means for transmitting information to a user terminal" refers to a mechanism for transmitting information about selected medical facilities from a server to a user terminal.

[1115] An "AI model" refers to a mathematical model that uses artificial intelligence technology to analyze data and generate appropriate information and judgments.

[1116] "Natural language processing technology" refers to technology that analyzes, understands, and generates natural human language.

[1117] "Image recognition technology" refers to the technology of analyzing image data and extracting useful information from it.

[1118] This invention is a system that promptly guides users who suddenly become ill or injured at night or on holidays to appropriate medical institutions. This system includes a user terminal, a server, a medical facility database, and a communication network.

[1119] First, a user enters symptom data into the application using a user device such as a smartphone, tablet, or PC. Symptom data can be provided in a variety of formats, including text input, voice input, images, and videos. For example, a user might enter text about their child's high fever and fatigue late at night and upload a photo of the rash. This data is then sent to a server via the Internet.

[1120] The server receives data sent from the user's device and analyzes the symptom data using an AI model, natural language processing technology, and image recognition technology. The AI ​​model is a mathematical model that analyzes data and generates medical interview information. The natural language processing technology is a technology for analyzing text data and understanding symptoms. The image recognition technology is a technology for analyzing image data and extracting useful information from it.

[1121] For example, if the server analyzes data on "high fever" and "rash" and determines that these are related symptoms, it will assess the urgency as "high." Based on the analyzed data, medical interview information is generated and the urgency is assessed. At the same time, the server generates first aid advice as needed. In the case of high fever and rash, advice on "cooling methods" and "hydration intake" is provided.

[1122] Next, the server references a medical facility database and selects the medical facility that best suits the user's symptoms. The medical facility database contains information such as medical specialty, available beds, and whether or not there are specialists. The server then sends the medical interview information to the selected medical facility to confirm whether or not the patient can be seen. For example, the server selects several hospitals with pediatric departments that are open at night, and sends the medical interview information to each to confirm whether or not the patient can be seen.

[1123] Once a medical facility where the patient can be seen is confirmed, the server sends that information to the user's terminal. The user terminal displays this information to the user. The guidance information includes the name, address, contact information, and arrival time of the medical facility. For example, the user terminal displays something like, "Please contact XX Hospital (address: XX town, XX chome). Arrival time is approximately 15 minutes."

[1124] Examples of concrete examples and prompts

[1125] Example: If your child develops a high fever in the middle of the night

[1126] 1. User behavior: The user launches the app late at night, enters their child's symptoms (high fever, fatigue) in text, takes a photo of the rash, and uploads it to the app.

[1127] 2. Operation on the device side: The device collects data and sends it to a server via the Internet.

[1128] 3. Server-side operation: The server analyzes the received data, determines the urgency as "high," generates a medical interview result, and advises emergency measures.

[1129] 4. Selection of medical institution: The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals.

[1130] 5. Sending guidance information: The server sends information about the selected hospital to the terminal.

[1131] 6. Operation on the terminal side: The terminal displays the information, the user contacts the hospital, and begins the journey.

[1132] Prompt Sentence Examples

[1133] "Late at night, the user enters a text message about their child's high fever and uploads a photo of the rash to the app. The device collects the data and sends it to a server via the internet. The server analyzes the data, determines the urgency as 'high,' generates a medical interview result, and advises first aid. The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals. The server then sends the information of the selected hospital to the device. The device displays the information, and the user contacts the hospital."

[1134] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[1135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1136] Step 1:

[1137] The user launches the system's application on a device such as a smartphone, tablet, or PC and enters detailed data about the symptoms.

[1138] Specific behavior:

[1139] The user enters text that they have a persistent high fever and feel very fatigued, takes a photo of the rash and uploads it to the app.

[1140] Input: Symptom data (text, images)

[1141] Output: Aggregated symptom data on the device

[1142] Step 2:

[1143] The user terminal transmits the input symptom data to a server via the Internet.

[1144] Specific behavior:

[1145] The smartphone collects text and image data and sends them to a server via a secure communication line.

[1146] Input: Symptom data collected on the device

[1147] Output: Symptom data sent to the server

[1148] Step 3:

[1149] The server receives the data sent from the user's device and analyzes it using AI models, natural language processing technology, and image recognition technology.

[1150] Specific behavior:

[1151] The server analyzes the data for "high fever" and "rash" and determines that these are related symptoms.

[1152] Input: Received symptom data

[1153] Output: Analyzed medical interview information (symptom classification, feature extraction)

[1154] Step 4:

[1155] The server generates medical interview information based on the analysis results and evaluates the urgency.

[1156] Specific behavior:

[1157] Based on cases of high fever and rash, advice is provided on "cooling methods" and "fluid intake."

[1158] Input: Parsed medical interview information

[1159] Output: Urgency assessment and advice

[1160] Step 5:

[1161] The server refers to a medical facility database and selects an appropriate medical facility.

[1162] Specific behavior:

[1163] The server selects multiple hospitals with pediatric departments that are open at night and transmits medical interview information to each hospital.

[1164] Input: Medical interview information, urgency assessment

[1165] Output: List of selected medical facilities

[1166] Step 6:

[1167] The server sends the medical interview information to the selected medical facility and checks whether the patient can be seen.

[1168] Specific behavior:

[1169] After receiving responses from each hospital, the most appropriate hospital will be selected.

[1170] Input: List of selected medical facilities, medical history information

[1171] Output: Check results for available medical facilities

[1172] Step 7:

[1173] Once the medical facility where the patient can be seen is confirmed, the server transmits the information to the user terminal.

[1174] Specific behavior:

[1175] The server generates a message saying, "Please contact XX Hospital (address: XX-cho XX-chome). Arrival time is approximately 15 minutes," and sends it to the user terminal.

[1176] Input: Confirmation result of available medical facilities

[1177] Output: Medical facility information sent to the user's device

[1178] Step 8:

[1179] The user terminal displays the received information about the medical facility to the user.

[1180] Specific behavior:

[1181] The smartphone displays detailed information about medical facilities on the screen, and the user follows the instructions to head to the hospital.

[1182] Input: Received medical facility information

[1183] Output: Medical facility information displayed on the screen

[1184] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[1185] (Application example 1)

[1186] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1187] While there are systems in place that can quickly guide patients to the appropriate medical institution in the event of sudden illness or injury at night or on holidays, there are no systems that take into account the patient's nutritional status or the provision of food for first aid. This can lead to patients being unable to select appropriate foods, resulting in insufficient nutrition. Medical institutions also have to work hard to provide food according to the patient's condition. Therefore, there is a need for a system that allows patients to quickly obtain information on both the appropriate medical institution and food, and to ensure appropriate nutritional management.

[1188] 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.

[1189] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data and generating medical interview information, means for selecting an appropriate medical institution affiliated organization based on the medical interview information and confirming the availability of medical treatment in cooperation with the medical institution affiliated organization, means for selecting optimal foods based on the availability of medical treatment by the medical institution affiliated organization, and means for transmitting information on available medical institution affiliated organizations and optimal food information to the user terminal, thereby enabling patients to quickly obtain information on both appropriate medical institutions and foods.

[1190] A "user terminal" is a communication device that allows a user to input data about symptoms and transmit the data to a server.

[1191] "Symptom Data" is information about a medical condition or injury a user is experiencing, provided in the form of text, images, video, or other information.

[1192] The "medical interview information" is information generated by the server by analyzing data on symptoms received from the user, and includes details of the symptoms and an assessment of the urgency of the symptoms.

[1193] The "medical institution affiliated organization" is a medical institution that the server selects based on the medical interview information and collaborates with to confirm the possibility of receiving medical treatment.

[1194] "Accessibility" is information indicating whether the selected medical institution affiliated organization can actually accept the patient.

[1195] "Optimal foods" are nutritionally balanced foods and drinks selected based on the user's symptoms.

[1196] "Appropriate food information" is detailed information about the most suitable food selected by the server and provided to the user.

[1197] This invention is a system that provides prompt and appropriate information on both medical institutions and food when a user suddenly becomes ill or injured at night or on a holiday. Specific methods for realizing this system are described below.

[1198] First, a user uses a user device such as a smartphone to input data about their symptoms. This data is provided in the form of text input, voice input, images, videos, etc. For example, if a user complains of a symptom of "high fever," they can input the symptoms in text and upload a photo of their face showing a high fever.

[1199] The user device then collects this data and sends it over the Internet to a server, which is built using the Flask framework and receives the data sent from the user device.

[1200] The server analyzes the received data and generates medical interview information. This analysis uses generative AI models, natural language processing technology, and image recognition technology. This allows the server to evaluate the details and urgency of symptoms and create specific medical interview information.

[1201] Next, the server selects an appropriate medical institution affiliated with the patient based on the generated medical interview information. It references information from the medical institution affiliated organization database and considers nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution affiliated with the patient to confirm whether the patient can be seen.

[1202] The server then selects the most appropriate food based on the patient's symptoms. This selection is done using a generative AI model based on the patient's symptoms. For example, if the patient has a high fever, appropriate foods such as porridge or soup will be selected.

[1203] Finally, the server sends information about affiliated medical institutions where patients can receive treatment, as well as information about the most suitable foods, to the user's device. Based on this information, the user's device guides the user on the most suitable course of action. Based on this guidance, the user can head to the appropriate medical institution and simultaneously order the appropriate foods.

[1204] (Example)

[1205] Example 1: When a user's child develops a high fever late at night

[1206] Users launch the app, type in the text "high fever," and then upload a photo of their face showing a high fever.

[1207] The server receives the data, analyzes it, and generates medical interview information. The urgency level is determined to be "high."

[1208] The server selects affiliated medical institutions with pediatric departments that are available for consultation and sends the information to the user's device. It also recommends "porridge" or "soup."

[1209] The user follows the guidance information and orders porridge for delivery on their way to the medical institution.

[1210] Example 2: If the user cuts their hand on a holiday

[1211] The user launches the app, takes a photo of the wound on their hand, and enters the bleeding status in text.

[1212] The server receives the data, analyzes it, and then generates medical interview information. As first aid, the doctor advises applying pressure to stop the bleeding.

[1213] The server selects a surgery that is open even on holidays and sends the information to the user's terminal. It also recommends appropriate foods for nutritional support.

[1214] The user follows the guidance information and orders the recommended food for delivery while heading to the medical institution.

[1215] (Example of a prompt)

[1216] "Please list foods that you recommend for high fever symptoms."

[1217] "Please tell me how to provide first aid for bleeding hands."

[1218] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1219] Step 1:

[1220] A user launches a smartphone app and inputs data about their symptoms. The input data includes textual symptom descriptions, voice input, images, and videos. For example, a user might input the symptom "high fever" in text and upload a photo of their face. In this case, the user's input becomes input data for the system.

[1221] Step 2:

[1222] The device collects data entered by the user and sends it to a server via the internet. The input data includes text, audio, images, and video detailing the symptoms. This is the data collection process on the device side. The output of the device is the data sent to the server.

[1223] Step 3:

[1224] The server receives the data sent from the device. It analyzes the received data and generates medical interview information using generative AI models, natural language processing (NLP), and image recognition technology. For example, the server analyzes the received image using image recognition technology, determines the details of a high fever, and evaluates the urgency as "high." The input is data from the device, and the output is the generated medical interview information.

[1225] Step 4:

[1226] The server selects an appropriate medical institution affiliated organization based on the medical interview information generated by the server. The server references a database of medical institution affiliated organizations and makes the selection taking into consideration information such as medical departments in the user's vicinity, available hospital beds, and the availability of specialists. For example, it selects a pediatric clinic that is open late at night. The input is the medical interview information, and the output is information on the selected medical institution affiliated organization.

[1227] Step 5:

[1228] The medical interview information is sent to the selected medical institution affiliated organizations to confirm the possibility of receiving medical treatment. Specifically, the server sends the medical interview information to each medical institution affiliated organization and waits for a response from each medical institution affiliated organization. The input is a list of medical institution affiliated organizations and the medical interview information, and the output is the confirmed possibility of receiving medical treatment information.

[1229] Step 6:

[1230] The server selects the most appropriate food based on the confirmed likelihood of medical treatment. In this process, the generative AI model recommends appropriate foods based on the symptoms. For example, in the case of a high fever, "porridge" or "soup" is recommended. The input is medical interview information about the symptoms, and the output is a list of appropriate foods.

[1231] Step 7:

[1232] Information on affiliated medical institutions where patients can be seen and information on optimal foods is sent to the user's terminal. The server sends all information together to the user's terminal, making it immediately available to the user. For example, in addition to the name, address, and contact information of the pediatric clinic the user should visit, "porridge" is displayed as a recommended food. The input is the confirmed information on availability of medical treatment and food information, and the output is guidance information sent to the user's terminal.

[1233] Step 8:

[1234] The user begins to act based on the information received. The user checks the guidance information and heads to the medical institution, while simultaneously ordering the recommended food from a delivery service. For example, the user can easily order "porridge" from the app and request delivery. The input is the guidance information sent to the user's device, and the output is the user's actions and food order.

[1235] 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.

[1236] This invention is a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it implements a means for providing the user with more appropriate support. The basic configuration of this system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network.

[1237] The user terminal is a communication device such as a smartphone, tablet, or PC, which the user uses to input symptom data. The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state. Symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[1238] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. Emotional information recognized by an emotion engine is also taken into account as part of the analysis. This allows the assessment of urgency and first aid advice to be adapted to the user's emotional state, providing more appropriate support.

[1239] The server then selects an appropriate medical institution based on the medical history information and emotion information. This selection refers to information in the medical institution database, taking into account nearby medical departments, available beds, the availability of specialists, and other information. The medical history information and emotion information are then sent to the selected medical institution to confirm whether the patient can be seen.

[1240] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[1241] This system allows users to receive emergency medical services without spending time and effort, and allows medical institutions to efficiently accept patients who can be seen. In addition, by responding to the user's emotions, it reduces the user's psychological burden and provides more appropriate medical services.

[1242] Specific examples

[1243] Example 1: When a child develops a high fever late at night

[1244] 1. User behavior

[1245] The user launches the app late at night and enters text about their child's symptoms (high fever, fatigue), then takes a photo of the rash and uploads it to the app. The app then uses its emotion engine to recognize the user's anxious expression and trembling voice.

[1246] 2. Operation on the terminal side

[1247] The device collects this data and sends it to a server via the Internet.

[1248] 3. Server-side operation

[1249] The server analyzes the received data and determines the urgency as "high" using an AI model. Since the situation involves a high fever, the emotion engine also incorporates information from the model to generate detailed interview results. Because the situation is urgent and highly anxious, the system immediately advises the user on how to cool down the situation.

[1250] 4. Selection of medical institution

[1251] The server searches the database for hospitals with pediatric departments that are open at night, sends the patient interview information and emotion information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[1252] 5. Sending guidance information

[1253] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[1254] 6. Terminal operation

[1255] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[1256] Example 2: If you cut your hand on a holiday

[1257] 1. User behavior

[1258] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding or not, the degree of pain) in text. The app uses its emotion engine to recognize the user's state of tension.

[1259] 2. Operation on the terminal side

[1260] The device collects data and sends it to a server via the internet.

[1261] 3. Server-side operation

[1262] The server analyzes the image and text data and uses an AI model to determine the level of urgency. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure. The system also takes into account information from the emotion engine, providing gentle, specific instructions.

[1263] 4. Selection of medical institution

[1264] The server searches for surgeries that are open even on holidays, sends medical interview information and emotion information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[1265] 5. Sending guidance information

[1266] The server generates information about the selected hospital and sends it to the terminal.

[1267] 6. Terminal operation

[1268] The device displays the information, the user contacts the designated hospital, and the journey begins.

[1269] In this way, by combining this system with an emotion engine, it is possible to reduce the psychological burden on users and enable more appropriate responses, thereby providing prompt and appropriate medical support while also reducing stress and anxiety for users.

[1270] The processing flow will be explained below.

[1271] Step 1:

[1272] The user launches the app.

[1273] Step 2:

[1274] The user enters symptoms by text or voice.

[1275] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[1276] Step 3:

[1277] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[1278] For example, identifying emotions such as anxiety or tension.

[1279] Step 4:

[1280] The device collects symptom data (text, audio, images, video) and emotional information and sends it to a server via the Internet.

[1281] Step 5:

[1282] The server receives the data sent from the user terminal.

[1283] Step 6:

[1284] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[1285] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[1286] The server also analyzes the emotion information from the emotion engine.

[1287] Step 7:

[1288] The server uses a generative AI model to generate medical interview information from the extracted information (symptom data, emotion data).

[1289] The server evaluates the urgency and generates the necessary emergency measures, taking emotional information into consideration to provide appropriate advice.

[1290] Step 8:

[1291] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and emotion information.

[1292] The server lists multiple candidate medical institutions.

[1293] Step 9:

[1294] The server transmits the medical interview information and emotion information to each selected medical institution to confirm the possibility of receiving treatment.

[1295] Step 10:

[1296] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[1297] Step 11:

[1298] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[1299] Step 12:

[1300] The server transmits the generated guidance information to the user terminal.

[1301] Step 13:

[1302] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[1303] The device provides the user with information including additional first aid measures and precautions that take emotions into consideration.

[1304] Step 14:

[1305] The user follows the displayed guidance information and heads to the designated medical institution.

[1306] If necessary, the user can contact the medical institution using the displayed contact information.

[1307] Specific examples

[1308] Example 1: When a child develops a high fever late at night

[1309] 1. Step 1: A user launches the app late at night.

[1310] 2. Step 2: The user enters a text description of their child's symptoms (high fever, fatigue) and takes and uploads a photo of the rash.

[1311] 3. Step 3: The emotion engine recognizes the user's anxious facial expression and trembling voice.

[1312] 4. Step 4: The device sends this data (text, images, and emotional information) to the server.

[1313] 5. Step 5: The server receives the data.

[1314] 6. Step 6: The server analyzes the text data, inspects the images, and captures the user's emotional information.

[1315] 7. Step 7: The server determines the urgency to be "high" and the situation involves a high fever, so it generates detailed medical interview results and presents first aid measures (cooling methods).

[1316] 8. Step 8: The server searches the database for pediatricians who are available for overnight consultations and creates a list of candidates.

[1317] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[1318] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[1319] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[1320] 12. Step 12: The server sends the guidance information to the user terminal.

[1321] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[1322] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[1323] Example 2: If you cut your hand on a holiday

[1324] 1. Step 1: The user launches the app.

[1325] 2. Step 2: The user takes a photo of the wound on their hand and reports the extent of bleeding and pain in text.

[1326] 3. Step 3: The emotion engine recognizes the user's state of tension.

[1327] 4. Step 4: The device sends data (text, images, and emotional information) to the server.

[1328] 5. Step 5: The server receives the data.

[1329] 6. Step 6: The server analyzes the image and text data and captures emotional information.

[1330] 7. Step 7: The server determines the urgency to be "medium" and gently and specifically suggests first aid measures (pressure hemostasis).

[1331] 8. Step 8: The server searches for surgeries that are open on holidays and creates a candidate list.

[1332] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[1333] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[1334] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[1335] 12. Step 12: The server sends the guidance information to the user terminal.

[1336] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[1337] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[1338] Example 2

[1339] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1340] In modern society, there is a need for a system that enables users to seek medical attention quickly and appropriately when they suddenly become ill or injured at night or on holidays. However, it can be difficult for users, especially those who are emotionally upset, to find the most appropriate medical institution and complete the procedures for seeking medical attention. For this reason, a support system is needed that recognizes the user's emotional state and provides appropriate responses, allowing users to seek medical attention quickly and with peace of mind.

[1341] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving symptom-related data from a user terminal, means for analyzing the received data and generating medical interview information, and means for selecting an appropriate medical institution based on the medical interview information and emotional information using a generative AI model, and for confirming the possibility of receiving medical treatment in cooperation with the medical institution via a communication network. This allows the user to quickly find the most appropriate medical institution, and further allows the user to feel at ease when starting to seek medical treatment by receiving advice on first aid that takes emotional information into consideration.

[1342] A "user terminal" is an electronic device that allows a user to input data about symptoms and transmit the data to a server via a communication network.

[1343] "Symptom data" refers to information that indicates the state of illness or injury of the user or a third party, and may be in the form of text, images, video, audio, or the like.

[1344] The "receiving means" is a mechanism by which the server receives data transmitted from the user terminal via the communication network.

[1345] "Medical interview information" is information necessary for medical treatment obtained by analyzing received symptom data.

[1346] The "means for confirming availability for medical treatment" is a mechanism by which the server sends medical interview information to an appropriate medical institution and confirms whether or not the medical institution is available for medical treatment.

[1347] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to generate emotional information.

[1348] "Emotion information" is information obtained by analyzing the user's emotional state using an emotion engine.

[1349] The "means for selecting an appropriate medical institution" is a mechanism for identifying the most suitable medical institution for a user based on medical interview information and emotional information.

[1350] "Communications Network" means the Internet or other communications infrastructure used to transmit and receive data.

[1351] "First aid advice" is a temporary solution that the server provides to the user based on the analysis results and the urgency assessment.

[1352] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and generate emotional information.

[1353] The present invention provides a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately. This support system is particularly equipped with an emotion engine that recognizes the user's emotions, and is further equipped with a means for providing appropriate support to the user. The following describes in detail an embodiment of the present invention.

[1354] Basic configuration

[1355] The basic configuration of the system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network. User terminals can be communication devices such as smartphones, tablets, and PCs. The emotion engine is used to recognize the user's emotional state by analyzing their facial expressions and vocal tone. Data is sent and received via the Internet.

[1356] User terminal

[1357] Users use a smartphone, tablet, or PC with a dedicated application installed. The user device provides an interface for inputting symptom data. This data can include text input, voice input, images, and videos, allowing users to provide information in an appropriate format. The system also incorporates an emotion engine that generates emotional information by analyzing facial expressions and tone of voice when the user describes their symptoms.

[1358] server

[1359] The server uses high-performance hardware and analyzes data using AI models, natural language processing (NLP), and image recognition technology. When the server receives data sent from the user's device, it begins analysis and generates medical interview information and emotional information. This allows the server to assess the urgency of the symptoms and provide first aid advice if necessary.

[1360] Emotion Engine

[1361] The emotion engine is software that analyzes the user's facial expressions and tone of voice to generate emotional information, which determines whether the user is feeling anxious or nervous, and responds accordingly.

[1362] Selection of medical institutions

[1363] The server selects an appropriate medical institution based on the medical interview information and emotion information generated by the server. This selection refers to information in the medical institution database, taking into account information such as medical departments, available beds, and the availability of specialists. The server sends the medical interview information and emotion information to the medical institution and confirms the possibility of treatment.

[1364] Providing guidance information

[1365] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the most suitable medical institution to the user. Contact information is also provided so that the user can contact the medical institution directly.

[1366] Specific examples

[1367] Example 1: When a child develops a high fever late at night

[1368] 1. A user launches the app late at night and enters their child's symptoms (high fever, fatigue) in text. They also upload a photo of the rash to the app.

[1369] 2. The emotion engine recognizes the user's anxious facial expression and trembling voice.

[1370] 3. The server receives this data and determines the urgency as "high."

[1371] 4. The server searches for multiple hospitals with pediatric departments that are open at night and selects the most suitable hospital.

[1372] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[1373] Example 2: If you cut your hand on a holiday

[1374] 1. The user launches the app, takes a photo of the cut on their hand, and reports via text whether there is bleeding and the degree of pain.

[1375] 2. The emotion engine recognizes the user's state of tension.

[1376] 3. The server receives this data, analyzes it, and advises the patient to apply pressure to stop bleeding if there is bleeding.

[1377] 4. The server searches for surgeries that are open even on holidays and selects the most suitable hospital.

[1378] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[1379] In this way, by utilizing generative AI models and emotion engines, the system of the present invention can reduce the psychological burden on users and provide prompt and appropriate medical support.

[1380] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1381] Step 1:

[1382] Entering Symptom Information

[1383] User actions: The user launches the app on a device on which the dedicated application is installed and enters symptom data using the symptom input interface.

[1384] Input: Symptom text, audio, image, and video data.

[1385] Output: The input data is saved in the device.

[1386] What happens: A user types in "high fever" and takes and uploads a photo of a rash.

[1387] Step 2:

[1388] Emotional information generation

[1389] Device operation: The emotion engine analyzes the user's facial expressions and tone of voice to generate emotional information.

[1390] Input: User facial and voice data.

[1391] Output: Data indicating the user's emotional state.

[1392] Specific operation: The device takes a picture of the user's face with a camera, analyzes their emotional state (e.g., anxiety) from their facial expression, and saves it as data.

[1393] Step 3:

[1394] Sending data

[1395] Device operation: The device collects and analyzes symptom data and emotional information, which are then sent to a server via the Internet.

[1396] Input: Symptom data, emotion information.

[1397] Output: Data sent to server completed.

[1398] Specific operation: When the device presses the "send" button, data is sent to the server via the Internet.

[1399] Step 4:

[1400] Receiving data

[1401] Server operation: The server receives the data sent from the user terminal.

[1402] Input: Symptom data, emotion information.

[1403] Output: The received data is stored in the server.

[1404] Specific operation: The server periodically checks for data reception and saves any new data.

[1405] Step 5:

[1406] Data analysis

[1407] Server operation: The server analyzes the received symptom data and generates medical interview information. At the same time, it analyzes emotional information.

[1408] Input: Received symptom data, emotion information.

[1409] Output: Interview information, emotion evaluation results.

[1410] How it works: The AI ​​model analyzes text data using natural language processing technology to detect "high fever," and uses image recognition technology to identify "rash" and assess its urgency.

[1411] Step 6:

[1412] Urgency assessment and first aid advice

[1413] Server operation: Evaluate the urgency of the symptoms based on the analysis results and generate first aid advice.

[1414] Input: Interview information, emotion assessment results.

[1415] Output: Urgency assessment result, first aid advice.

[1416] Specific behavior: If the evaluation result is "Urgency: High," advice such as "Use a cooling towel" is generated.

[1417] Step 7:

[1418] Selection of medical institutions

[1419] Server operation: The server refers to the medical institution database and selects an appropriate medical institution based on the medical interview information and emotion information.

[1420] Input: Interview information, emotion assessment results.

[1421] Output: Information on selected medical institutions.

[1422] Specific operation: The server searches for pediatric hospitals that are open at night and obtains information on multiple medical institutions.

[1423] Step 8:

[1424] Checking availability for medical examination

[1425] Server operation: Sends medical interview information and emotion information to the selected medical institution to confirm the possibility of receiving treatment.

[1426] Input: Information on the selected medical institution, medical interview information, and emotion assessment results.

[1427] Output: A list of available medical facilities.

[1428] Specific operation: Check the response from each medical institution regarding the availability of treatment and determine the most suitable medical institution.

[1429] Step 9:

[1430] Generating guidance information

[1431] Server operation: Once available medical institutions are confirmed, guidance information is generated.

[1432] Input: Information about medical institutions where you can receive treatment.

[1433] Output: Guidance information.

[1434] Specific operation: The server generates a package containing the name, address, contact information, and arrival time of the medical institution.

[1435] Step 10:

[1436] Sending guidance information

[1437] Server operation: Sends guidance information to the user terminal.

[1438] Input: Guidance information.

[1439] Output: Data sent to user terminal.

[1440] Specific operation: The server sends guidance information to the user terminal via the Internet.

[1441] Step 11:

[1442] Displaying information and encouraging action

[1443] Terminal operation: The user terminal displays the guidance information received and prompts the user to take action.

[1444] Input: Received information.

[1445] Output: The clinic information displayed to the user.

[1446] What it does: The app displays, "The nearest pediatric clinic is XX Hospital. The address is XX and the reach time is approximately 15 minutes." and also makes the contact information clickable.

[1447] (Application example 2)

[1448] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1449] In order to enable users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, it is necessary to provide a system that can reduce the psychological burden on users and provide appropriate medicines and first aid advice.However, current medical support systems have the problem of being unable to provide appropriate responses that take into account the user's emotional state.

[1450] The identification process by the identification 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 means for receiving symptom-related data from a user terminal, means for analyzing the received data to generate medical interview information, means for analyzing the user's facial expression and tone of voice using an emotion engine to determine the level of urgency, means for selecting an appropriate medical institution based on the medical interview information and confirming the availability of medical treatment in cooperation with that medical institution, means for transmitting information about available medical institutions to the user terminal, means for providing the user with the inventory status of necessary medicines for the user's symptoms, and means for providing the user with first aid according to the level of urgency and advice to reduce psychological burden. This enables the user to receive prompt and appropriate medical services, and also realizes the appropriate provision of medicines and reduction of the user's psychological burden.

[1451] A "user terminal" is a communication device through which a user inputs symptom-related data and displays received information.

[1452] The "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state.

[1453] "Symptom data" is information that describes the user's symptoms, such as text, audio, images, and video.

[1454] "Medical interview information" is specific symptom information that is generated by analyzing received symptom-related data and is to be provided to a medical institution.

[1455] The "urgency" is an index for evaluating the seriousness of the user's symptoms, and is used to determine whether a prompt response is required.

[1456] "Medical institution" is a general term for medical facilities such as hospitals and clinics where users can receive medical treatment.

[1457] "Availability" is the process of checking whether the selected medical institution can accept the user for treatment.

[1458] "Pharmaceutical inventory status" refers to information about the quantity and types of pharmaceuticals held by pharmacies and drugstores.

[1459] "First aid" refers to emergency medical treatment that should be performed until the user arrives at a medical facility.

[1460] "Reducing psychological burden" means providing advice and support to ease the user's anxiety and tension.

[1461] This invention is a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, and in particular provides appropriate support to users by combining it with an emotion engine. This system is composed of a user terminal, a server, an emotion engine, a medical institution database, and a communication network.

[1462] The user terminal is a communication device such as a smartphone, tablet, or PC that the user uses to input symptom-related data. The symptom-related data can be provided in a variety of formats, including text input, voice input, images, and videos. The user terminal transmits the input data to a server via the Internet.

[1463] The server has a means for receiving data sent from the user terminal, analyzing it, and generating medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. Emotional information recognized by the emotion engine is also taken into account as part of the analysis, and the assessment of urgency and first aid advice are adapted to the user's emotional state, providing more appropriate support.

[1464] The server also has a means for selecting an appropriate medical institution based on the medical history information and emotion information. This selection refers to information in the medical institution database, taking into consideration information such as nearby medical departments, available beds, and the availability of specialists. The medical history information and emotion information are sent to the selected medical institution to confirm the possibility of treatment.

[1465] Once an available medical institution is identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, and arrival time of the medical institution that is most suitable for the user. It also provides the stock status of the necessary medicines to treat the user's symptoms. It also provides the user with first aid according to the level of urgency and advice to reduce psychological burden.

[1466] Specific examples

[1467] Example 1: When a child develops a high fever late at night

[1468] 1. User behavior

[1469] The user launches the app late at night and enters text about their child's symptoms (high fever, fatigue), then takes a photo of the rash and uploads it to the app. The app then uses its emotion engine to recognize the user's anxious facial expression and trembling voice.

[1470] 2. Operation on the terminal side

[1471] The device collects this data and sends it to a server over the Internet.

[1472] 3. Server-side operation

[1473] The server analyzes the received data and determines the urgency as "high" using an AI model. As the situation involves a high fever, it also incorporates information from the emotion engine to generate detailed interview results. As the situation is urgent and highly anxious, it immediately advises the user on how to cool down.

[1474] 4. Selection of medical institution

[1475] The server searches the database for hospitals with pediatric departments that are open at night, and sends the patient interview information and emotion information to multiple hospitals. After receiving responses from each hospital, the server selects the most appropriate hospital.

[1476] 5. Sending guidance information

[1477] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[1478] 6. Terminal operation

[1479] The terminal displays the information to the user, who then begins to take action towards the most suitable hospital.

[1480] Example 2: If you cut your hand on a holiday

[1481] 1. User behavior

[1482] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding or not, the degree of pain) in text. The app uses its emotion engine to recognize the user's state of tension.

[1483] 2. Operation on the terminal side

[1484] The device collects the data and sends it to a server over the internet.

[1485] 3. Server-side operation

[1486] The server analyzes the image and text data and uses an AI model to determine the level of urgency. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure. The system also takes into account information from the emotion engine, providing gentle, specific instructions.

[1487] 4. Selection of medical institution

[1488] The server searches for surgeries that are open even on holidays, and sends the patient's medical history and emotion information to multiple hospitals. After receiving responses from each hospital, the server selects the most suitable hospital.

[1489] 5. Sending guidance information

[1490] The server generates information about the selected hospital and sends it to the terminal.

[1491] 6. Terminal operation

[1492] The terminal displays the information, the user contacts the designated hospital, and the journey begins.

[1493] Prompt Sentence Examples

[1494] The user enters the following information into the app:

[1495] Symptoms: High fever and fatigue

[1496] Audio: Audio recording

[1497] Image:Facial image

[1498] System Response:

[1499] Urgency: High

[1500] First aid advice: Cooling recommended

[1501] Nearby pharmacy information: ____ pharmacy, ____ address

[1502] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1503] Step 1:

[1504] The user launches the smartphone application and inputs data about their symptoms. Specifically, they describe their symptoms using text, audio, images, or video, and if necessary, record their voice and take a photo of their face. This becomes the input data.

[1505] Step 2:

[1506] The device collects the data entered by the user and transmits it to a server over the Internet, including text data, audio files, and image files.

[1507] Step 3:

[1508] The server analyzes the received data. First, it analyzes the text data about symptoms using natural language processing (NLP) technology to generate medical interview information. This process uses a pre-trained AI model. This is part of the data processing. The output is the medical interview information.

[1509] Step 4:

[1510] Next, the server uses an emotion engine to analyze the user's facial expression data and voice data. OpenCV is used to analyze the facial expression data, extracting facial feature points and recognizing facial expressions. Librosa is used to analyze the voice data, extracting voice features and inputting them into an emotion recognition model. This allows the user's emotional state to be understood. The output is emotional information.

[1511] Step 5:

[1512] The server evaluates the urgency of the symptoms based on the medical interview information and emotional information. A pre-trained AI model is used to evaluate the urgency and determine the optimal response for the user's situation. This urgency information is generated.

[1513] Step 6:

[1514] The server selects an appropriate medical institution from a database of medical institutions based on the user's symptoms. It evaluates multiple hospitals, taking into account the user's location, medical specialty, available beds, and whether or not they have specialists. It creates a list of appropriate medical institutions and sends the medical interview information and emotion information to the selected medical institution. The output is a list of selected medical institutions.

[1515] Step 7:

[1516] The server collects information from medical institutions to confirm whether the patient can receive treatment, and then selects the most appropriate medical institution. This information includes the available dates and times for treatment and the hospital's availability. The output is the consultation confirmation information.

[1517] Step 8:

[1518] Once an available medical institution is identified, the server sends that information to the user's terminal. The user's terminal displays the name, address, contact information, and arrival time of the selected medical institution. It also displays stock information of medicines according to the user's symptoms. The output is the display information.

[1519] Step 9:

[1520] The server generates first aid advice according to the user's level of urgency and sends it to the user's device. For example, in the case of a high fever, it provides advice on cooling methods, and in the case of bleeding, it advises on pressure hemostasis. This allows the user to take immediate action. The output is first aid advice.

[1521] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1522] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1523] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1524] [Fourth embodiment]

[1525] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1526] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1527] 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).

[1528] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1529] 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.

[1530] 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).

[1531] 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. 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.

[1532] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1533] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1534] 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.

[1535] 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.

[1536] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1537] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1538] The present invention is a system that promptly guides patients to appropriate medical institutions for sudden illness or injury at night or on holidays. The basic configuration of this system includes a user terminal, a server, a medical institution database, and a communication network.

[1539] The user terminal is a communication device such as a smartphone, tablet, or PC that the user uses to input symptom data. The symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[1540] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. The medical interview information includes details of symptoms and an assessment of the urgency of the condition.

[1541] The server also selects an appropriate medical institution based on the medical interview information. To do this, it references information from the medical institution database and takes into account information such as nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution to confirm whether the patient can be seen.

[1542] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[1543] This system allows users to receive emergency medical services without spending time and effort, and also allows medical institutions to efficiently accept patients who are available for treatment.

[1544] Specific examples

[1545] Example 1: When a child develops a high fever late at night

[1546] 1. User behavior

[1547] Users launch the app late at night, enter their child's symptoms (high fever, fatigue) in text, and take a photo of the rash and upload it to the app.

[1548] 2. Operation on the terminal side

[1549] The device collects this data and sends it to a server via the Internet.

[1550] 3. Server-side operation

[1551] The server analyzes the received data and uses an AI model to determine the urgency as "high." Because the condition involves a high fever, a detailed medical interview is generated and the user is advised on cooling methods as first aid.

[1552] 4. Selection of medical institution

[1553] The server searches the database for hospitals with pediatric departments that are open at night, sends the medical interview information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[1554] 5. Sending guidance information

[1555] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[1556] 6. Terminal operation

[1557] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[1558] Example 2: If you cut your hand on a holiday

[1559] 1. User behavior

[1560] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding, how much pain there is) in text.

[1561] 2. Operation on the terminal side

[1562] The device collects data and sends it to a server via the internet.

[1563] 3. Server-side operation

[1564] The server analyzes the image and text data, and uses an AI model to determine the urgency of the situation. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure.

[1565] 4. Selection of medical institution

[1566] The server searches for surgeries that are open even on holidays, sends medical interview information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[1567] 5. Sending guidance information

[1568] The server generates information about the selected hospital and sends it to the terminal.

[1569] 6. Terminal operation

[1570] The device displays the information, the user contacts the designated hospital, and the journey begins.

[1571] In this way, this system provides a prompt and appropriate response to sudden illness or injury at night or on holidays, significantly reducing the burden on patients and medical institutions.

[1572] The processing flow will be explained below.

[1573] Step 1:

[1574] The user launches the app.

[1575] Step 2:

[1576] The user enters symptoms by text or voice.

[1577] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[1578] Step 3:

[1579] The device collects this data and sends it to a server over the Internet.

[1580] Step 4:

[1581] The server receives text, audio, image, and video data sent from the user terminal.

[1582] Step 5:

[1583] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[1584] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[1585] Step 6:

[1586] The server uses a generative AI model to generate medical interview information from the extracted information.

[1587] The server assesses the urgency and generates the necessary emergency response information.

[1588] Step 7:

[1589] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and urgency information.

[1590] The server lists multiple candidate medical institutions.

[1591] Step 8:

[1592] The server transmits the medical interview information to each selected medical institution and confirms whether the patient can receive treatment.

[1593] Step 9:

[1594] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[1595] Step 10:

[1596] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[1597] Step 11:

[1598] The server transmits the generated guidance information to the user terminal.

[1599] Step 12:

[1600] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[1601] Step 13:

[1602] The user follows the displayed guidance information and heads to the designated medical institution.

[1603] If necessary, the user can contact the medical institution using the displayed contact information.

[1604] Example 1

[1605] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1606] In modern society, when people suddenly become ill or injured at night or on holidays, it can be difficult to quickly find an appropriate medical institution. Furthermore, there is a risk that a patient's condition may worsen if appropriate initial treatment is delayed for highly urgent symptoms. There is a need for a method to solve these problems and provide prompt and appropriate medical institution guidance.

[1607] 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.

[1608] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data to generate medical interview information, means for evaluating the urgency of the condition, means for selecting an appropriate medical facility from a medical facility database and confirming the availability of medical treatment in cooperation with the selected medical facility, means for transmitting information on available medical facilities to the user terminal, and means for analyzing the data using an AI model, natural language processing technology, and image recognition technology. This enables the user to be quickly directed to an appropriate medical institution even if they suddenly become ill or injured at night or on a holiday.

[1609] A "user terminal" is a communication device that allows a user to input and receive data related to symptoms, and includes smartphones, tablets, personal computers, etc.

[1610] "Means for receiving data" refers to a mechanism by which the server receives symptom-related data sent from the user terminal.

[1611] "Means for generating medical interview information" refers to a mechanism by which the server analyzes the data received and generates the necessary information based on the patient's symptoms.

[1612] "Means for assessing urgency" refers to a mechanism for determining the urgency of a patient's symptoms based on analyzed data.

[1613] The "medical facility database" is a database that contains information on the medical departments, bed availability, and the availability of specialists at various medical facilities.

[1614] "Means to confirm availability of medical treatment in cooperation with medical facilities" refers to a system for sending medical interview information to selected medical facilities to confirm availability of medical treatment.

[1615] "Means for transmitting information to a user terminal" refers to a mechanism for transmitting information about selected medical facilities from a server to a user terminal.

[1616] An "AI model" refers to a mathematical model that uses artificial intelligence technology to analyze data and generate appropriate information and judgments.

[1617] "Natural language processing technology" refers to technology that analyzes, understands, and generates natural human language.

[1618] "Image recognition technology" refers to the technology of analyzing image data and extracting useful information from it.

[1619] This invention is a system that promptly guides users who suddenly become ill or injured at night or on holidays to appropriate medical institutions. This system includes a user terminal, a server, a medical facility database, and a communication network.

[1620] First, a user enters symptom data into the application using a user device such as a smartphone, tablet, or PC. Symptom data can be provided in a variety of formats, including text input, voice input, images, and videos. For example, a user might enter text about their child's high fever and fatigue late at night and upload a photo of the rash. This data is then sent to a server via the Internet.

[1621] The server receives data sent from the user's device and analyzes the symptom data using an AI model, natural language processing technology, and image recognition technology. The AI ​​model is a mathematical model that analyzes data and generates medical interview information. The natural language processing technology is a technology for analyzing text data and understanding symptoms. The image recognition technology is a technology for analyzing image data and extracting useful information from it.

[1622] For example, if the server analyzes data on "high fever" and "rash" and determines that these are related symptoms, it will assess the urgency as "high." Based on the analyzed data, medical interview information is generated and the urgency is assessed. At the same time, the server generates first aid advice as needed. In the case of high fever and rash, advice on "cooling methods" and "hydration intake" is provided.

[1623] Next, the server references a medical facility database and selects the medical facility that best suits the user's symptoms. The medical facility database contains information such as medical specialty, available beds, and whether or not there are specialists. The server then sends the medical interview information to the selected medical facility to confirm whether or not the patient can be seen. For example, the server selects several hospitals with pediatric departments that are open at night, and sends the medical interview information to each to confirm whether or not the patient can be seen.

[1624] Once a medical facility where the patient can be seen is confirmed, the server sends that information to the user's terminal. The user terminal displays this information to the user. The guidance information includes the name, address, contact information, and arrival time of the medical facility. For example, the user terminal displays something like, "Please contact XX Hospital (address: XX town, XX chome). Arrival time is approximately 15 minutes."

[1625] Examples of concrete examples and prompts

[1626] Example: If your child develops a high fever in the middle of the night

[1627] 1. User behavior: The user launches the app late at night, enters their child's symptoms (high fever, fatigue) in text, takes a photo of the rash, and uploads it to the app.

[1628] 2. Operation on the device side: The device collects data and sends it to a server via the Internet.

[1629] 3. Server-side operation: The server analyzes the received data, determines the urgency as "high," generates a medical interview result, and advises emergency measures.

[1630] 4. Selection of medical institution: The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals.

[1631] 5. Sending guidance information: The server sends information about the selected hospital to the terminal.

[1632] 6. Operation on the terminal side: The terminal displays the information, the user contacts the hospital, and begins the journey.

[1633] Prompt Sentence Examples

[1634] "Late at night, the user enters a text message about their child's high fever and uploads a photo of the rash to the app. The device collects the data and sends it to a server via the internet. The server analyzes the data, determines the urgency as 'high,' generates a medical interview result, and advises first aid. The server searches for hospitals that are open overnight and sends the medical interview information to multiple hospitals. The server then sends the information of the selected hospital to the device. The device displays the information, and the user contacts the hospital."

[1635] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[1636] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1637] Step 1:

[1638] The user launches the system's application on a device such as a smartphone, tablet, or PC and enters detailed data about the symptoms.

[1639] Specific behavior:

[1640] The user enters text that they have a persistent high fever and feel very fatigued, takes a photo of the rash and uploads it to the app.

[1641] Input: Symptom data (text, images)

[1642] Output: Aggregated symptom data on the device

[1643] Step 2:

[1644] The user terminal transmits the input symptom data to a server via the Internet.

[1645] Specific behavior:

[1646] The smartphone collects text and image data and sends them to a server via a secure communication line.

[1647] Input: Symptom data collected on the device

[1648] Output: Symptom data sent to the server

[1649] Step 3:

[1650] The server receives the data sent from the user's device and analyzes it using AI models, natural language processing technology, and image recognition technology.

[1651] Specific behavior:

[1652] The server analyzes the data for "high fever" and "rash" and determines that these are related symptoms.

[1653] Input: Received symptom data

[1654] Output: Analyzed medical interview information (symptom classification, feature extraction)

[1655] Step 4:

[1656] The server generates medical interview information based on the analysis results and evaluates the urgency.

[1657] Specific behavior:

[1658] Based on cases of high fever and rash, advice is provided on "cooling methods" and "fluid intake."

[1659] Input: Parsed medical interview information

[1660] Output: Urgency assessment and advice

[1661] Step 5:

[1662] The server refers to a medical facility database and selects an appropriate medical facility.

[1663] Specific behavior:

[1664] The server selects multiple hospitals with pediatric departments that are open at night and transmits medical interview information to each hospital.

[1665] Input: Medical interview information, urgency assessment

[1666] Output: List of selected medical facilities

[1667] Step 6:

[1668] The server sends the medical interview information to the selected medical facility and checks whether the patient can be seen.

[1669] Specific behavior:

[1670] After receiving responses from each hospital, the most appropriate hospital will be selected.

[1671] Input: List of selected medical facilities, medical history information

[1672] Output: Check results for available medical facilities

[1673] Step 7:

[1674] Once the medical facility where the patient can be seen is confirmed, the server transmits the information to the user terminal.

[1675] Specific behavior:

[1676] The server generates a message saying, "Please contact XX Hospital (address: XX-cho XX-chome). Arrival time is approximately 15 minutes," and sends it to the user terminal.

[1677] Input: Confirmation result of available medical facilities

[1678] Output: Medical facility information sent to the user's device

[1679] Step 8:

[1680] The user terminal displays the received information about the medical facility to the user.

[1681] Specific behavior:

[1682] The smartphone displays detailed information about medical facilities on the screen, and the user follows the instructions to head to the hospital.

[1683] Input: Received medical facility information

[1684] Output: Medical facility information displayed on the screen

[1685] This system allows users to receive emergency medical services without wasting time or effort, and also allows medical facilities to efficiently accept patients who are available for treatment.

[1686] (Application example 1)

[1687] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1688] While there are systems in place that can quickly guide patients to the appropriate medical institution in the event of sudden illness or injury at night or on holidays, there are no systems that take into account the patient's nutritional status or the provision of food for first aid. This can lead to patients being unable to select appropriate foods, resulting in insufficient nutrition. Medical institutions also have to work hard to provide food according to the patient's condition. Therefore, there is a need for a system that allows patients to quickly obtain information on both the appropriate medical institution and food, and to ensure appropriate nutritional management.

[1689] 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.

[1690] In this invention, the server includes means for receiving symptom data from a user terminal, means for analyzing the received data and generating medical interview information, means for selecting an appropriate medical institution affiliated organization based on the medical interview information and confirming the availability of medical treatment in cooperation with the medical institution affiliated organization, means for selecting optimal foods based on the availability of medical treatment by the medical institution affiliated organization, and means for transmitting information on available medical institution affiliated organizations and optimal food information to the user terminal, thereby enabling patients to quickly obtain information on both appropriate medical institutions and foods.

[1691] A "user terminal" is a communication device that allows a user to input data about symptoms and transmit the data to a server.

[1692] "Symptom Data" is information about a medical condition or injury a user is experiencing, provided in the form of text, images, video, or other information.

[1693] The "medical interview information" is information generated by the server by analyzing data on symptoms received from the user, and includes details of the symptoms and an assessment of the urgency of the symptoms.

[1694] The "medical institution affiliated organization" is a medical institution that the server selects based on the medical interview information and collaborates with to confirm the possibility of receiving medical treatment.

[1695] "Accessibility" is information indicating whether the selected medical institution affiliated organization can actually accept the patient.

[1696] "Optimal foods" are nutritionally balanced foods and drinks selected based on the user's symptoms.

[1697] "Appropriate food information" is detailed information about the most suitable food selected by the server and provided to the user.

[1698] This invention is a system that provides prompt and appropriate information on both medical institutions and food when a user suddenly becomes ill or injured at night or on a holiday. Specific methods for realizing this system are described below.

[1699] First, a user uses a user device such as a smartphone to input data about their symptoms. This data is provided in the form of text input, voice input, images, videos, etc. For example, if a user complains of a symptom of "high fever," they can input the symptoms in text and upload a photo of their face showing a high fever.

[1700] The user device then collects this data and sends it over the Internet to a server, which is built using the Flask framework and receives the data sent from the user device.

[1701] The server analyzes the received data and generates medical interview information. This analysis uses generative AI models, natural language processing technology, and image recognition technology. This allows the server to evaluate the details and urgency of symptoms and create specific medical interview information.

[1702] Next, the server selects an appropriate medical institution affiliated with the patient based on the generated medical interview information. It references information from the medical institution affiliated organization database and considers nearby medical departments, available beds, and the availability of specialists. It then sends the medical interview information to the selected medical institution affiliated with the patient to confirm whether the patient can be seen.

[1703] The server then selects the most appropriate food based on the patient's symptoms. This selection is done using a generative AI model based on the patient's symptoms. For example, if the patient has a high fever, appropriate foods such as porridge or soup will be selected.

[1704] Finally, the server sends information about affiliated medical institutions where patients can receive treatment, as well as information about the most suitable foods, to the user's device. Based on this information, the user's device guides the user on the most suitable course of action. Based on this guidance, the user can head to the appropriate medical institution and simultaneously order the appropriate foods.

[1705] (Example)

[1706] Example 1: When a user's child develops a high fever late at night

[1707] Users launch the app, type in the text "high fever," and then upload a photo of their face showing a high fever.

[1708] The server receives the data, analyzes it, and generates medical interview information. The urgency level is determined to be "high."

[1709] The server selects affiliated medical institutions with pediatric departments that are available for consultation and sends the information to the user's device. It also recommends "porridge" or "soup."

[1710] The user follows the guidance information and orders porridge for delivery on their way to the medical institution.

[1711] Example 2: If the user cuts their hand on a holiday

[1712] The user launches the app, takes a photo of the wound on their hand, and enters the bleeding status in text.

[1713] The server receives the data, analyzes it, and then generates medical interview information. As first aid, the doctor advises applying pressure to stop the bleeding.

[1714] The server selects a surgery that is open even on holidays and sends the information to the user's terminal. It also recommends appropriate foods for nutritional support.

[1715] The user follows the guidance information and orders the recommended food for delivery while heading to the medical institution.

[1716] (Example of a prompt)

[1717] "Please list foods that you recommend for high fever symptoms."

[1718] "Please tell me how to provide first aid for bleeding hands."

[1719] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1720] Step 1:

[1721] A user launches a smartphone app and inputs data about their symptoms. The input data includes textual symptom descriptions, voice input, images, and videos. For example, a user might input the symptom "high fever" in text and upload a photo of their face. In this case, the user's input becomes input data for the system.

[1722] Step 2:

[1723] The device collects data entered by the user and sends it to a server via the internet. The input data includes text, audio, images, and video detailing the symptoms. This is the data collection process on the device side. The output of the device is the data sent to the server.

[1724] Step 3:

[1725] The server receives the data sent from the device. It analyzes the received data and generates medical interview information using generative AI models, natural language processing (NLP), and image recognition technology. For example, the server analyzes the received image using image recognition technology, determines the details of a high fever, and evaluates the urgency as "high." The input is data from the device, and the output is the generated medical interview information.

[1726] Step 4:

[1727] The server selects an appropriate medical institution affiliated organization based on the medical interview information generated by the server. The server references a database of medical institution affiliated organizations and makes the selection taking into consideration information such as medical departments in the user's vicinity, available hospital beds, and the availability of specialists. For example, it selects a pediatric clinic that is open late at night. The input is the medical interview information, and the output is information on the selected medical institution affiliated organization.

[1728] Step 5:

[1729] The medical interview information is sent to the selected medical institution affiliated organizations to confirm the possibility of receiving medical treatment. Specifically, the server sends the medical interview information to each medical institution affiliated organization and waits for a response from each medical institution affiliated organization. The input is a list of medical institution affiliated organizations and the medical interview information, and the output is the confirmed possibility of receiving medical treatment information.

[1730] Step 6:

[1731] The server selects the most appropriate food based on the confirmed likelihood of medical treatment. In this process, the generative AI model recommends appropriate foods based on the symptoms. For example, in the case of a high fever, "porridge" or "soup" is recommended. The input is medical interview information about the symptoms, and the output is a list of appropriate foods.

[1732] Step 7:

[1733] Information on affiliated medical institutions where patients can be seen and information on optimal foods is sent to the user's terminal. The server sends all information together to the user's terminal, making it immediately available to the user. For example, in addition to the name, address, and contact information of the pediatric clinic the user should visit, "porridge" is displayed as a recommended food. The input is the confirmed information on availability of medical treatment and food information, and the output is guidance information sent to the user's terminal.

[1734] Step 8:

[1735] The user begins to act based on the information received. The user checks the guidance information and heads to the medical institution, while simultaneously ordering the recommended food from a delivery service. For example, the user can easily order "porridge" from the app and request delivery. The input is the guidance information sent to the user's device, and the output is the user's actions and food order.

[1736] 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.

[1737] This invention is a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it implements a means for providing the user with more appropriate support. The basic configuration of this system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network.

[1738] The user terminal is a communication device such as a smartphone, tablet, or PC, which the user uses to input symptom data. The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state. Symptom data is provided in a variety of formats, including text input, voice input, images, and videos. This data is sent to a server via the Internet.

[1739] The server receives the data sent from the user's device, analyzes it, and generates medical interview information. AI models, natural language processing technology, and image recognition technology are used to generate the medical interview information. Emotional information recognized by an emotion engine is also taken into account as part of the analysis. This allows the assessment of urgency and first aid advice to be adapted to the user's emotional state, providing more appropriate support.

[1740] The server then selects an appropriate medical institution based on the medical history information and emotion information. This selection refers to information in the medical institution database, taking into account nearby medical departments, available beds, the availability of specialists, and other information. The medical history information and emotion information are then sent to the selected medical institution to confirm whether the patient can be seen.

[1741] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the medical institution that is most suitable for the user. Contact information is also provided so that the user can contact the medical institution directly.

[1742] This system allows users to receive emergency medical services without spending time and effort, and allows medical institutions to efficiently accept patients who can be seen. In addition, by responding to the user's emotions, it reduces the user's psychological burden and provides more appropriate medical services.

[1743] Specific examples

[1744] Example 1: When a child develops a high fever late at night

[1745] 1. User behavior

[1746] The user launches the app late at night and enters text about their child's symptoms (high fever, fatigue), then takes a photo of the rash and uploads it to the app. The app then uses its emotion engine to recognize the user's anxious expression and trembling voice.

[1747] 2. Operation on the terminal side

[1748] The device collects this data and sends it to a server via the Internet.

[1749] 3. Server-side operation

[1750] The server analyzes the received data and determines the urgency as "high" using an AI model. Since the situation involves a high fever, the emotion engine also incorporates information from the model to generate detailed interview results. Because the situation is urgent and highly anxious, the system immediately advises the user on how to cool down the situation.

[1751] 4. Selection of medical institution

[1752] The server searches the database for hospitals with pediatric departments that are open at night, sends the patient interview information and emotion information to multiple hospitals, and then selects the most appropriate hospital based on the responses from each hospital.

[1753] 5. Sending guidance information

[1754] The server generates information about the selected hospital (name, address, contact information, arrival time) and sends it to the terminal.

[1755] 6. Terminal operation

[1756] The device displays information to the user, who then begins taking action to find the most suitable hospital.

[1757] Example 2: If you cut your hand on a holiday

[1758] 1. User behavior

[1759] The user launches the app, takes a photo of the cut on their hand, and reports the situation (whether there is bleeding or not, the degree of pain) in text. The app uses its emotion engine to recognize the user's state of tension.

[1760] 2. Operation on the terminal side

[1761] The device collects data and sends it to a server via the internet.

[1762] 3. Server-side operation

[1763] The server analyzes the image and text data and uses an AI model to determine the level of urgency. Since there is bleeding, the system advises applying pressure to stop the bleeding as a first aid measure. The system also takes into account information from the emotion engine, providing gentle, specific instructions.

[1764] 4. Selection of medical institution

[1765] The server searches for surgeries that are open even on holidays, sends medical interview information and emotion information to multiple hospitals, and selects the most suitable hospital based on responses from each hospital.

[1766] 5. Sending guidance information

[1767] The server generates information about the selected hospital and sends it to the terminal.

[1768] 6. Terminal operation

[1769] The device displays the information, the user contacts the designated hospital, and the journey begins.

[1770] In this way, by combining this system with an emotion engine, it is possible to reduce the psychological burden on users and enable more appropriate responses, thereby providing prompt and appropriate medical support while also reducing stress and anxiety for users.

[1771] The processing flow will be explained below.

[1772] Step 1:

[1773] The user launches the app.

[1774] Step 2:

[1775] The user enters symptoms by text or voice.

[1776] Users use their smartphone camera to take pictures or videos of their symptoms and upload them to the app.

[1777] Step 3:

[1778] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[1779] For example, identifying emotions such as anxiety or tension.

[1780] Step 4:

[1781] The device collects symptom data (text, audio, images, video) and emotional information and sends it to a server via the Internet.

[1782] Step 5:

[1783] The server receives the data sent from the user terminal.

[1784] Step 6:

[1785] The text data received by the server is analyzed using natural language processing technology to identify symptoms and their severity.

[1786] The images and videos received by the server are analyzed using image recognition technology to identify abnormalities and symptoms.

[1787] The server also analyzes the emotion information from the emotion engine.

[1788] Step 7:

[1789] The server uses a generative AI model to generate medical interview information from the extracted information (symptom data, emotion data).

[1790] The server evaluates the urgency and generates the necessary emergency measures, taking emotional information into consideration to provide appropriate advice.

[1791] Step 8:

[1792] The server searches for an appropriate medical institution from a medical institution database based on the medical interview information and emotion information.

[1793] The server lists multiple candidate medical institutions.

[1794] Step 9:

[1795] The server transmits the medical interview information and emotion information to each selected medical institution to confirm the possibility of receiving treatment.

[1796] Step 10:

[1797] The server analyzes the received replies from each medical institution and checks which medical institutions are able to accept the patient.

[1798] Step 11:

[1799] The server identifies medical institutions that can accept patients and generates detailed guidance information (such as name, address, contact information, and arrival time).

[1800] Step 12:

[1801] The server transmits the generated guidance information to the user terminal.

[1802] Step 13:

[1803] The terminal receives the guidance information transmitted from the server and displays it in a format that is easy for the user to understand.

[1804] The device provides the user with information including additional first aid measures and precautions that take emotions into consideration.

[1805] Step 14:

[1806] The user follows the displayed guidance information and heads to the designated medical institution.

[1807] If necessary, the user can contact the medical institution using the displayed contact information.

[1808] Specific examples

[1809] Example 1: When a child develops a high fever late at night

[1810] 1. Step 1: A user launches the app late at night.

[1811] 2. Step 2: The user enters a text description of their child's symptoms (high fever, fatigue) and takes and uploads a photo of the rash.

[1812] 3. Step 3: The emotion engine recognizes the user's anxious facial expression and trembling voice.

[1813] 4. Step 4: The device sends this data (text, images, and emotional information) to the server.

[1814] 5. Step 5: The server receives the data.

[1815] 6. Step 6: The server analyzes the text data, inspects the images, and captures the user's emotional information.

[1816] 7. Step 7: The server determines the urgency to be "high" and the situation involves a high fever, so it generates detailed medical interview results and presents first aid measures (cooling methods).

[1817] 8. Step 8: The server searches the database for pediatricians who are available for overnight consultations and creates a list of candidates.

[1818] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[1819] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[1820] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[1821] 12. Step 12: The server sends the guidance information to the user terminal.

[1822] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[1823] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[1824] Example 2: If you cut your hand on a holiday

[1825] 1. Step 1: The user launches the app.

[1826] 2. Step 2: The user takes a photo of the wound on their hand and reports the extent of bleeding and pain in text.

[1827] 3. Step 3: The emotion engine recognizes the user's state of tension.

[1828] 4. Step 4: The device sends data (text, images, and emotional information) to the server.

[1829] 5. Step 5: The server receives the data.

[1830] 6. Step 6: The server analyzes the image and text data and captures emotional information.

[1831] 7. Step 7: The server determines the urgency to be "medium" and gently and specifically suggests first aid measures (pressure hemostasis).

[1832] 8. Step 8: The server searches for surgeries that are open on holidays and creates a candidate list.

[1833] 9. Step 9: The server sends the medical interview information and emotion information to each medical institution and inquires about the possibility of treatment.

[1834] 10. Step 10: The server analyzes the response indicating that the patient is available for treatment and determines the most appropriate medical institution.

[1835] 11. Step 11: The server generates detailed information on medical institutions that can accept the patient.

[1836] 12. Step 12: The server sends the guidance information to the user terminal.

[1837] 13. Step 13: The device displays guidance information and suggests additional first aid measures and precautions that take emotions into account.

[1838] 14. Step 14: The user contacts the designated medical facility, starts traveling according to the directions, and arrives at the medical facility.

[1839] Example 2

[1840] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1841] In modern society, there is a need for a system that enables users to seek medical attention quickly and appropriately when they suddenly become ill or injured at night or on holidays. However, it can be difficult for users, especially those who are emotionally upset, to find the most appropriate medical institution and complete the procedures for seeking medical attention. For this reason, a support system is needed that recognizes the user's emotional state and provides appropriate responses, allowing users to seek medical attention quickly and with peace of mind.

[1842] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving symptom-related data from a user terminal, means for analyzing the received data and generating medical interview information, and means for selecting an appropriate medical institution based on the medical interview information and emotional information using a generative AI model, and for confirming the possibility of receiving medical treatment in cooperation with the medical institution via a communication network. This allows the user to quickly find the most appropriate medical institution, and further allows the user to feel at ease when starting to seek medical treatment by receiving advice on first aid that takes emotional information into consideration.

[1843] A "user terminal" is an electronic device that allows a user to input data about symptoms and transmit the data to a server via a communication network.

[1844] "Symptom data" refers to information that indicates the state of illness or injury of the user or a third party, and may be in the form of text, images, video, audio, or the like.

[1845] The "receiving means" is a mechanism by which the server receives data transmitted from the user terminal via the communication network.

[1846] "Medical interview information" is information necessary for medical treatment obtained by analyzing received symptom data.

[1847] The "means for confirming availability for medical treatment" is a mechanism by which the server sends medical interview information to an appropriate medical institution and confirms whether or not the medical institution is available for medical treatment.

[1848] An "emotion engine" is software or a system that analyzes a user's facial expressions and tone of voice to generate emotional information.

[1849] "Emotion information" is information obtained by analyzing the user's emotional state using an emotion engine.

[1850] The "means for selecting an appropriate medical institution" is a mechanism for identifying the most suitable medical institution for a user based on medical interview information and emotional information.

[1851] "Communications Network" means the Internet or other communications infrastructure used to transmit and receive data.

[1852] "First aid advice" is a temporary solution that the server provides to the user based on the analysis results and the urgency assessment.

[1853] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and generate emotional information.

[1854] The present invention provides a support system that enables users who suddenly become ill or injured at night or on holidays to seek medical attention promptly and appropriately. This support system is particularly equipped with an emotion engine that recognizes the user's emotions, and is further equipped with a means for providing appropriate support to the user. The following describes in detail an embodiment of the present invention.

[1855] Basic configuration

[1856] The basic configuration of the system includes a user terminal, a server, an emotion engine, a medical institution database, and a communication network. User terminals can be communication devices such as smartphones, tablets, and PCs. The emotion engine is used to recognize the user's emotional state by analyzing their facial expressions and vocal tone. Data is sent and received via the Internet.

[1857] User terminal

[1858] Users use a smartphone, tablet, or PC with a dedicated application installed. The user device provides an interface for inputting symptom data. This data can include text input, voice input, images, and videos, allowing users to provide information in an appropriate format. The system also incorporates an emotion engine that generates emotional information by analyzing facial expressions and tone of voice when the user describes their symptoms.

[1859] server

[1860] The server uses high-performance hardware and analyzes data using AI models, natural language processing (NLP), and image recognition technology. When the server receives data sent from the user's device, it begins analysis and generates medical interview information and emotional information. This allows the server to assess the urgency of the symptoms and provide first aid advice if necessary.

[1861] Emotion Engine

[1862] The emotion engine is software that analyzes the user's facial expressions and tone of voice to generate emotional information, which determines whether the user is feeling anxious or nervous, and responds accordingly.

[1863] Selection of medical institutions

[1864] The server selects an appropriate medical institution based on the medical interview information and emotion information generated by the server. This selection refers to information in the medical institution database, taking into account information such as medical departments, available beds, and the availability of specialists. The server sends the medical interview information and emotion information to the medical institution and confirms the possibility of treatment.

[1865] Providing guidance information

[1866] Once available medical institutions are identified, the server sends that information to the user's terminal. Based on the received information, the user's terminal displays the name, address, contact information, arrival time, etc. of the most suitable medical institution to the user. Contact information is also provided so that the user can contact the medical institution directly.

[1867] Specific examples

[1868] Example 1: When a child develops a high fever late at night

[1869] 1. A user launches the app late at night and enters their child's symptoms (high fever, fatigue) in text. They also upload a photo of the rash to the app.

[1870] 2. The emotion engine recognizes the user's anxious facial expression and trembling voice.

[1871] 3. The server receives this data and determines the urgency as "high."

[1872] 4. The server searches for multiple hospitals with pediatric departments that are open at night and selects the most suitable hospital.

[1873] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[1874] Example 2: If you cut your hand on a holiday

[1875] 1. The user launches the app, takes a photo of the cut on their hand, and reports via text whether there is bleeding and the degree of pain.

[1876] 2. The emotion engine recognizes the user's state of tension.

[1877] 3. The server receives this data, analyzes it, and advises the patient to apply pressure to stop bleeding if there is bleeding.

[1878] 4. The server searches for surgeries that are open even on holidays and selects the most suitable hospital.

[1879] 5. The server sends information about the selected hospital to the user's terminal, and the terminal displays the information to the user.

[1880] In this way, by utilizing generative AI models and emotion engines, the system of the present invention can reduce the psychological burden on users and provide prompt and appropriate medical support.

[1881] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1882] Step 1:

[1883] Entering Symptom Information

[1884] User actions: The user launches the app on a device on which the dedicated application is installed and enters symptom data using the symptom input interface.

[1885] Input: Symptom text, audio, image, and video data.

[1886] Output: The input data is saved in the device.

[1887] What happens: A user types in "high fever" and takes and uploads a photo of a rash.

[1888] Step 2:

[1889] Emotional information generation

[1890] Device operation: The emotion engine analyzes the user's facial expressions and tone of voice to generate emotional information.

[1891] Input: User facial and voice data.

[1892] Output: Data indicating the user's emotional state.

[1893] Specific operation: The device takes a picture of the user's face with a camera, analyzes their emotional state (e.g., anxiety) from their facial expression, and saves it as data.

[1894] Step 3:

[1895] Sending data

[1896] Device operation: The device collects and analyzes symptom data and emotional information, which are then sent to a server via the Internet.

[1897] Input: Symptom data, emotion information.

[1898] Output: Data sent to server completed.

[1899] Specific operation: When the device presses the "send" button, data is sent to the server via the Internet.

[1900] Step 4:

[1901] Receiving data

[1902] Server operation: The server receives the data sent from the user terminal.

[1903] Input: Symptom data, emotion information.

[1904] Output: The received data is stored in the server.

[1905] Specific operation: The server periodically checks for data reception and saves any new data.

[1906] Step 5:

[1907] Data analysis

[1908] Server operation: The server analyzes the received symptom data and generates medical interview information. At the same time, it analyzes emotional information.

[1909] Input: Received symptom data, emotion information.

[1910] Output: Interview information, emotion evaluation results.

[1911] How it works: The AI ​​model analyzes text data using natural language processing technology to detect "high fever," and uses image recognition technology to identify "rash" and assess its urgency.

[1912] Step 6:

[1913] Urgency assessment and first aid advice

[1914] Server operation: Evaluate the urgency of the symptoms based on the analysis results and generate first aid advice.

[1915] Input: Interview information, emotion assessment results.

[1916] Output: Urgency assessment result, first aid advice.

[1917] Specific behavior: If the evaluation result is "Urgency: High," advice such as "Use a cooling towel" is generated.

[1918] Step 7:

[1919] Selection of medical institutions

[1920] Server operation: The server refers to the medical institution database and selects an appropriate medical institution based on the medical interview information and emotion information.

[1921] Input: Interview information, emotion assessment results.

[1922] Output: Information on selected medical institutions.

[1923] Specific operation: The server searches for pediatric hospitals that are open at night and obtains information on multiple medical institutions.

[1924] Step 8:

[1925] Checking availability for medical examination

[1926] Server operation: Sends medical interview information and emotion information to the selected medical institution to confirm the possibility of receiving treatment.

[1927] Input: Information on the selected medical institution, medical interview information, and emotion assessment results.

[1928] Output: A list of available medical facilities.

[1929] Specific operation: Check the response from each medical institution regarding the availability of treatment and determine the most suitable medical institution.

[1930] Step 9:

[1931] Generating guidance information

[1932] Server operation: Once available medical institutions are confirmed, guidance information is generated.

[1933] Input: Information about medical institutions where you can receive treatment.

[1934] Output: Guidance information.

[1935] Specific operation: The server generates a package containing the name, address, contact information, and arrival time of the medical institution.

[1936] Step 10:

[1937] Sending guidance information

[1938] Server operation: Sends guidance information to the user terminal.

[1939] Input: Guidance information.

[1940] Output: Data sent to user terminal.

[1941] Specific operation: The server sends guidance information to the user terminal via the Internet.

[1942] Step 11:

[1943] Displaying information and encouraging action

[1944] Terminal operation: The user terminal displays the guidance information received and prompts the user to take action.

[1945] Input: Received information.

[1946] Output: The clinic information displayed to the ...

Claims

1. means for receiving symptom-related data from a user terminal; A means for analyzing the received data and generating medical interview information; A method for selecting an appropriate medical institution based on the medical interview information and working with that medical institution to confirm whether the patient can receive treatment; A system including a means for transmitting information on medical institutions where treatment is available to a user terminal.

2. The system according to claim 1 , further comprising means for determining the urgency of the symptoms based on the received medical interview information.

3. The system of claim 1 , further comprising means for analyzing the medical interview information as an image, video, or text.

Images