System

Abstract

To provide a system.SOLUTION: A system for providing information on infertility treatment, includes: means for referring to a database including at least one of past treatment results, statistical information, and information disclosure by research institutions; means for providing information on infertility treatment based on information obtained from the database; means for acquiring information from the database in response to an inquiry from a user; means for sending a prompt sentence to a generative AI model based on the acquired information; and means for returning a response from the generative AI model to the user.SELECTED DRAWING: Figure 1

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In infertility treatment, there is a problem that sufficient information for each patient to select the most suitable treatment method for themselves cannot be obtained. Specifically, not only information provided by doctors, but also more extensive and detailed information such as past treatment records, statistical information, and information disclosure by research institutions is required.

Means for Solving the Problems

[0005] The present invention provides a system that refers to a database including past treatment records, statistical information, and information disclosures at research institutions, and provides information on infertility treatment based on this information. In addition, in response to inquiries from users, it responds based on the information obtained from the database. Furthermore, by providing information on specific infertility treatment methods and responding to inquiries from users in a chat format, it provides information for individual patients to select the optimal treatment method for themselves.

Brief Description of the Drawings

[0006]

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Embodiments for Carrying Out the Invention

[0007] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0009] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. As an example of an arithmetic unit, there are a CPU (Central Processing Unit),

[0010] GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (TENSOR PROCESSING UNIT (registered trademark)), etc.

[0011] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0012] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. As an example of a non-volatile storage device, there are flash memory (SSD (Solid State Drive)), magnetic disk (e.g.,

[0013] hard disk), or magnetic tape, etc.

[0014] In the following embodiments, the labeled communication I / F (Interface) is a communication processor and

[0015] It is an interface including an antenna and the like. The communication I / F controls communication between a plurality of 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), or Bluetooth (registered trademark).

[0016] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0017] [First Embodiment]

[0018] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0019] As shown in FIG. 1, the 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.

[0020] 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 the "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. Also, the database 24 and the communication I / F 26 are 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).

[0021] 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 5

[0022] 0 are connected to a bus 52. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0023] The reception device 38 includes a touch panel 38A, a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by contact of an indicator (e.g., a pen or a finger, etc.) by detecting the contact of the indicator. The microphone 38B receives user input by voice by detecting the voice of the user. 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 data indicating the user input.

[0024] The output device 40 includes a display 40A, a speaker 40B, etc., and presents data to the user 20 by outputting the data in a form (e.g., voice and / or text) perceptible by the user 20. The display 40A displays visible information such as text and images according to an instruction from the processor 46. The speaker 40B outputs voice according to an instruction from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, a diaphragm, and a shutter, and an imaging device such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CC

[0025] D (Charge Coupled Device) image sensor, etc.

[0026] camera.

[0027] The communication I / F 44 is connected to the 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.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in FIG. 2, in the data processing device 12, specific processing is performed by the processor 28. The specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of the "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 the specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The data generation model 58 and the emotion identification model 59 are stored in the storage 32. The data generation model 58 and the emotion identification model 59 are used by the specific processing unit 290.

[0031] In the smart device 14, input / output processing for reception is performed by the processor 46. The input / output program for reception 60 is stored in the storage 50. The input / output program for reception 60 is used in combination with the specific processing program 56 by the data processing system 10. The processor 46 reads the input / output program for reception 60 from the storage 50 and executes the read input / output program for reception 60 on the RAM 48. The input / output processing for reception is realized by the processor 46 operating as the control unit 46A according to the input / output program for reception 60 executed on the RAM 48.

[0032] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0033] "Form Example 1"

[0034] As an embodiment of the present invention, there is a system for providing infertility treatment information. This system

[0035] has means for referring to a database including past treatment records, statistical information, and information disclosures at research institutions. Specifically, the database collects and organizes information on various infertility treatment methods, information on the treatment results and treatment processes of patients to whom those treatment methods have been applied, research results on infertility treatment published at various research institutions, and the like.

[0036] "Form Example 2"

[0037] The above system has means for responding to inquiries from users based on information obtained from the database. Specifically, when a user inquires about a specific infertility treatment method, the system obtains information on the corresponding treatment method from the database and responds to the user based on that. For example, when a user inquires, "What is the success rate of PGT-A?", the system obtains information on the success rate of PGT-A from the database and provides it to the user.

[0038] "Form Example 3"

[0039] Furthermore, the above system has means for responding to inquiries from users in a chat format. Specifically, when a user makes an inquiry in a chat format, the system returns a response to it in real time. This response is generated based on information obtained from the database. For example, when a user inquires, "What are the advantages and disadvantages of two-stage transplantation?", the system obtains information on the advantages and disadvantages of two-stage transplantation from the database and returns a response to the user based on that.

[0040] Below, the processing flow of each form example will be described.

[0041] "Form Example 1"

[0042] Step 1: The system refers to a database that includes past treatment records, statistical information, and information disclosures by research institutions.

[0043] Step 2: Based on the information obtained from the database, provide information regarding infertility treatment. "Form Example 2"

[0044] Step 1: Receive an inquiry from the user.

[0045] Step 2: Retrieve information corresponding to the inquiry from the database.

[0046] Step 3: Based on the retrieved information, return a response to the user.

[0047] "Form Example 3"

[0048] Step 1: Receive a chat-form inquiry from the user.

[0049] Step 2: Retrieve information corresponding to the inquiry from the database.

[0050] Step 3: Based on the retrieved information, return a real-time response to the user.

[0051] (Example 1)

[0052] Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0053] Information regarding infertility treatment is diverse, and it is difficult for patients and medical staff to obtain the necessary information quickly and accurately. In addition, there is a lack of a system for effectively utilizing past treatment records, statistical information, and information disclosures by research institutions. Furthermore, even when a user enters specific search conditions, the means for appropriately providing relevant information are limited. As a result, it has become difficult for users to make a decision for selecting the optimal treatment method.

[0054] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in the first embodiment is realized by the following means.

[0055] In the present invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, means for sorting the collected data by category and storing it in the database, means for analyzing the search conditions input by the user and sending a request to the server, and means for displaying the data returned from the server to the user. As a result, the user can quickly and accurately obtain the necessary infertility treatment information, and it becomes possible to make a decision to select the optimal treatment method.

[0056] The "database" is an aggregate of information that stores and can refer to information including past treatment results, statistical information, and information disclosure at research institutions.

[0057] The "referring means" is a method or technique for searching for information in the database and obtaining necessary data.

[0058] The "providing means" is a method or technique for displaying the obtained information to the user and providing it in a usable form.

[0059] The "responding means" is a method or technique for returning an answer based on the information obtained from the database in response to an inquiry from the user.

[0060] The "sorting means" is a method or technique for classifying the collected data by category and efficiently storing it in the database.

[0061] The "analyzing means" is a method or technique for understanding the search conditions input by the user and generating an appropriate request based on it.

[0062] The "means for transmitting" is a method or technology for transmitting the analyzed request to the server to obtain necessary information.

[0063] The "means for displaying" is a method or technology for displaying the data returned from the server in a user-friendly format.

[0064] This invention is a system for providing infertility treatment information, in which the server, the terminal, and the user operate in cooperation. The specific operations of each entity will be described below.

[0065] Operations of the server

[0066] The server plays a central role in collecting, organizing, and providing information related to infertility treatment. The server uses the following hardware and software.

[0067] Hardware: High-performance processor, sufficient memory, storage device

[0068] Software: Database management system (DBMS), API interface, data analysis tool

[0069] The server automatically collects information related to infertility treatment from the Internet or partnering research institutions. For example, it accesses the databases of research institutions through APIs and obtains data on "the success rate of treatment method A" and "the side effects of treatment method B". The collected data is organized by category and stored in the database. Duplicates and inconsistencies in the data are checked, and the data is cleansed if necessary.

[0070] In response to a request from the user, the server extracts appropriate information from the database and returns it to the terminal. The data is filtered based on the content of the request to provide the most relevant information to the user.

[0071] Operations of the terminal

[0072] The terminal provides an interface for the user to search for and view infertility treatment information. The terminal uses the following hardware and software.

[0073] Hardware: Personal computer, smartphone, tablet

[0074] Software: Web browser, mobile application

[0075] The terminal provides an interface that enables the user to easily search for information. For example, it displays web pages or applications with a search bar and filtering functions. When the user enters search criteria, the terminal sends that request to the server. When sending the request, the terminal converts the user's input into an appropriate format so that the server can understand it.

[0076] Upon receiving the data returned from the server, the terminal displays it to the user. The displayed information is provided in a visual format such as graphs or charts to enable the user to intuitively understand the information.

[0077] User operations

[0078] The user uses this system to obtain information regarding infertility treatment. The user operates the system according to the following procedure.

[0079] 1. Input of search criteria: The user enters search criteria through the interface of the terminal. For example, the user enters criteria such as "treatment methods suitable for women over 40 years old" or "side effects of treatment method D". Filtering options for setting search criteria in detail can also be used.

[0080] 2. Viewing of information: The user views the information provided by the server on the terminal. For example, when the user searches for "success rate of treatment method E", the user checks the result on the terminal. The user can scroll through the displayed information to check the details and can also use the function to save the information as needed.

[0081] 3. Decision-making Support: Based on the provided information, the user considers options for infertility treatment. For example, the user makes a decision such as "confirming that treatment method F has a high success rate and deciding to try that method." Tools can also be used to compare multiple treatment methods and find the optimal option.

[0082] Specific Examples and Prompt Sentences

[0083] For example, when the user searches for "infertility treatment methods suitable for women over 35 years old," the processing is carried out in the following steps.

[0084] 1. The user enters "infertility treatment methods suitable for women over 35 years old" in the search bar of the terminal.

[0085] 2. The terminal sends the request to the server.

[0086] 3. The server extracts the relevant information from the database and returns it to the terminal.

[0087] 4. The terminal displays the information to the user.

[0088] 5. The user considers appropriate treatment methods based on the displayed information.

[0089] By inputting the following prompt sentence into the generative AI model, specific infertility treatment information can be obtained.

[0090] "Please tell me about infertility treatment methods suitable for women over 35 years old. Provide detailed information based on past treatment records, statistical information, and information disclosures by research institutions."

[0091] By inputting this prompt sentence, the generative AI model provides the relevant information and supports the user's decision-making.

[0092] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0093] Step 1:

[0094] Data collection

[0095] The server automatically collects information on infertility treatment from the Internet or partner research institutions. As input, it accesses the databases of research institutions through APIs and obtains data on "success rate of treatment method A" and "side effects of treatment method B". As output, the collected data is stored in the server's temporary storage. As a specific operation, the server periodically sets a data collection schedule and updates the database whenever new information is published.

[0096] Step 2:

[0097] Data sorting

[0098] The server sorts the collected data by category and stores it in the database. As input, it receives the data stored in the temporary storage. As output, the sorted data is stored in the database. As a specific operation, the server checks for data duplication and inconsistencies and cleans the data as necessary. For example, if data for the same patient is collected multiple times, it is integrated into one.

[0099] Step 3:

[0100] Provision of user interface

[0101] The terminal provides an interface that allows users to easily search for information. As input, it receives the user's search criteria. As output, the search criteria are sent to the server. As a specific operation, the terminal displays a web page or application with a search bar and filtering function. It analyzes the search criteria entered by the user in real time and provides a suggestion function.

[0102] Step 4:

[0103] Sending a request

[0104] The terminal sends the search conditions entered by the user to the server. As input, it receives the user's search conditions. As output, a request converted into an appropriate format is sent to the server. As a specific operation, when sending the request, the terminal converts the input content of the user into an appropriate format so that the server can understand it.

[0105] Step 5:

[0106] Data provision

[0107] The server extracts appropriate information from the database according to the request from the user and returns it to the terminal. As input, it receives the request sent from the terminal. As output, the corresponding information is returned to the terminal. As a specific operation, the server filters the data based on the content of the request and provides the information most relevant to the user.

[0108] Step 6:

[0109] Display of results

[0110] The terminal displays the data returned from the server to the user. As input, it receives the data returned from the server. As output, the information is displayed in a user-friendly format. As a specific operation, the terminal provides the displayed information in a visual format such as graphs or charts so that the user can intuitively understand the information.

[0111] Step 7:

[0112] Viewing information

[0113] The user browses the information displayed on the terminal. As input, the user receives the information displayed on the terminal. As output, the user checks the information and saves it if necessary. As a specific operation, the user scrolls the displayed information to check the details and uses the function to save the information if necessary.

[0114] Step 8:

[0115] Support for decision-making

[0116] Based on the information provided, the user considers the options for infertility treatment. As input, the user receives the information displayed on the terminal. As output, a decision is made for the user to select the optimal treatment method. As a specific operation, the user compares multiple treatment methods and uses tools to find the optimal option. For example, a comparison table for comparing the success rates and side effects of each treatment method is used.

[0117] (Application Example 1)

[0118] Next, Application Example 1 of the morphological example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0119] Couples or individuals considering infertility treatment need to collect and compare a lot of information in order to find the optimal treatment method and medical institution. However, this information is scattered and difficult to collect efficiently. In addition, it is difficult to obtain information based on the latest research results and treatment records, and there is a lack of judgment materials when selecting appropriate treatment methods and medical institutions. For this reason, there is a need for a system that can be easily accessed by users and provides reliable information.

[0120] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0121] In this invention, the server includes means for referring to a database containing past treatment records, statistical information, and information disclosures by research institutions; means for providing information on infertility treatment based on the information obtained from the database; means for responding to inquiries from users based on the information obtained from the database; means for proposing an optimal treatment method based on the symptoms input by the user and the treatment method desired by the user; and means for searching for an optimal medical institution based on the user's location information and the desired treatment method. As a result, users can efficiently obtain highly reliable infertility treatment information and select an optimal treatment method and medical institution.

[0122] "Past treatment records" refer to data regarding the results and processes of past infertility treatments.

[0123] "Statistical information" refers to information obtained by aggregating and analyzing numerical data regarding treatment results and treatment processes.

[0124] "Information disclosures by research institutions" refer to information such as research results and papers on infertility treatment publicly disclosed by research institutions.

[0125] "Database" refers to a system that organizes and stores information including past treatment records, statistical information, and information disclosures by research institutions.

[0126] "Information on infertility treatment" refers to information such as infertility treatment methods, treatment results, treatment processes, and the latest research results.

[0127] "Inquiries from users" refer to questions and requests for information made by users to the system.

[0128] "Symptoms" refer to physical and medical conditions related to infertility experienced by the user.

[0129] "Desired treatment method" refers to the method of infertility treatment that the user wishes to receive.

[0130] The "optimal treatment method" refers to the method of infertility treatment that best suits the user's symptoms and wishes.

[0131] The "location information" refers to the data regarding the place where the user is currently located.

[0132] The "medical institution" refers to facilities such as clinics and hospitals that provide infertility treatment.

[0133] The "chat format" refers to a format for real-time communication using text messages.

[0134] The system for implementing this invention includes a server, a user terminal, and a database. The server refers to a database including past treatment records, statistical information, and information disclosures by research institutions, and provides information regarding infertility treatment to the user. The user terminal is a device such as a smartphone or a tablet, and provides an interface for the user to access the system.

[0135] The server includes the following means:

[0136] 1. Database reference means: Refer to a database including past treatment records, statistical information, and information disclosures by research institutions.

[0137] 2. Information providing means: Provide information regarding infertility treatment based on the information obtained from the database.

[0138] 3. Inquiry response means: Respond to inquiries from the user based on the information obtained from the database.

[0139] 4. Treatment method proposal means: Propose the optimal treatment method based on the symptoms input by the user and the treatment method the user wishes for.

[0140] 5. Medical institution search means: Search for the optimal medical institution based on the user's location information and the treatment method the user wishes for.

[0141] Hardware and Software to be Used:

[0142] Hardware: Server, Smartphone, Tablet

[0143] Software: Flask (Python web framework), requests (Python library for sending HTTP requests)

[0144] Data Processing and Data Calculation:

[0145] The server receives input data (symptoms, desired treatment methods, location information) from users and searches for relevant information in the database. The search results are proposed as the optimal treatment methods and medical institutions for the users. Specifically, a web application is constructed using Flask, and the requests library is used to communicate with the database.

[0146] Specific Example:

[0147] When the user opens the "Infertility Treatment Navigator" app and enters their symptoms (e.g., polycystic ovary syndrome) and desired treatment method (e.g., in vitro fertilization), the server searches the database for the optimal treatment method and medical institution and proposes them to the user.

[0148] Example of Prompt Sentence:

[0149] The user has symptoms of polycystic ovary syndrome and desires in vitro fertilization. Please propose the optimal treatment method and medical institution.

[0150] In this way, users can efficiently obtain highly reliable infertility treatment information and select the optimal treatment methods and medical institutions.

[0151] The flow of specific processing in Application Example 1 will be described with reference to FIG. 12.

[0152] Step 1:

[0153] The user launches an application on a smartphone or tablet and enters symptoms, desired treatment methods, and location information.

[0154] Input: Symptoms, desired treatment methods, location information

[0155] Output: User input data

[0156] Specific operation: The user enters symptoms (e.g., polycystic ovary syndrome), desired treatment methods (e.g., in vitro fertilization), and location information into the input form of the application and presses the send button.

[0157] Step 2:

[0158] The user terminal sends the input data to the server.

[0159] Input: User input data

[0160] Output: Request to the server

[0161] Specific operation: The user terminal sends the input data to the server as an HTTP request.

[0162] Step 3:

[0163] The server analyzes the received user input data and searches for relevant treatment information in the database.

[0164] Input: User input data

[0165] Output: Treatment information

[0166] Specific operation: The server uses Flask to analyze the received data, sends a query to the database using the requests library, and obtains relevant treatment information.

[0167] Step 4:

[0168] Based on the treatment method information obtained by the server, propose the most suitable treatment method for the user's symptoms and desired treatment method.

[0169] Input: Treatment method information, user input data

[0170] Output: Proposal for the most suitable treatment method

[0171] Specific operation: Analyze the treatment method information obtained by the server, select and propose the treatment method that best suits the user's symptoms and wishes.

[0172] Step 5:

[0173] The server searches for the most suitable medical institution based on the user's location information and desired treatment method.

[0174] Input: Location information, desired treatment method

[0175] Output: Medical institution information

[0176] Specific operation: The server searches the database based on the location information and desired treatment method, and obtains the information of the most suitable medical institution.

[0177] Step 6:

[0178] The server sends the proposal for the most suitable treatment method and medical institution information to the user terminal.

[0179] Input: Proposal for the most suitable treatment method, medical institution information

[0180] Output: Response to the user terminal

[0181] Specific operation: The server sends the proposal for the most suitable treatment method and medical institution information to the user terminal as an HTTP response.

[0182] Step 7:

[0183] The user terminal receives the response from the server and displays it to the user.

[0184] Input: Response from the server

[0185] Output: Display information to the user

[0186] Specific operation: The user terminal receives the response from the server and displays the optimal treatment proposal and medical institution information on the interface of the application.

[0187] In this way, the user can efficiently obtain highly reliable infertility treatment information and select the optimal treatment method and medical institution.

[0188] (Example 2)

[0189] Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0190] In the conventional infertility treatment information providing system, it was difficult for users to quickly and accurately obtain the information they needed. In addition, there was a lack of means to provide detailed information on specific infertility treatment methods, and it was impossible to appropriately respond to user inquiries. Furthermore, the user interface was insufficient, and the environment in which users could easily obtain information was not well-established.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0192] In this invention, the server includes means for a user to input an inquiry from a terminal, means for the terminal to send the inquiry to the server, means for the server to analyze the inquiry, means for the server to access a database to obtain information, means for the server to send the obtained information to the terminal, and means for the terminal to display the information to the user. As a result, the user can obtain the necessary infertility treatment information quickly and accurately.

[0193] A "user" is an individual or group that attempts to obtain information using the system.

[0194] A "terminal" is an electronic device used by a user to input an inquiry and receive information.

[0195] A "server" is a computer system that has the role of receiving an inquiry from a user, analyzing it, accessing a database to obtain information, and sending it to the terminal.

[0196] An "inquiry" is a question or request input by a user to the system through the terminal.

[0197] A "database" is a data storage system for storing information including past treatment records, statistical information, and information disclosures at research institutions.

[0198] "Means for obtaining information" is a process for the server to access the database, search for, and obtain the necessary information.

[0199] "Means for displaying information" is a function for the terminal to display the information received from the server to the user in an easy-to-view format.

[0200] "Specific infertility treatment methods" refer to specific infertility treatment methods such as PGTA and two-stage transplantation.

[0201] The "chat format" is an interface format for users to make inquiries in an interactive manner with the system and receive responses.

[0202] This invention is a system that enables users to quickly and accurately obtain information related to infertility treatment using a terminal. The system operates by the user inputting an inquiry from the terminal and sending the inquiry to the server. The server analyzes the inquiry, accesses the database to obtain the necessary information, and sends the obtained information to the terminal. The terminal displays the received information to the user.

[0203] This system uses the following hardware and software:

[0204] Terminal: Electronic devices such as smartphones, tablets, and personal computers

[0205] Server: High-performance computer system

[0206] Database Management System (DBMS): MySQL (registered trademark)

[0207] Server software: Apache (registered trademark)

[0208] Programming language: Python

[0209] As a specific example of the operation, a user inputs "What is the success rate of PGTA?" into the input field of the terminal. This inquiry is sent from the terminal to the server, and the server accesses the MySQL database to obtain information regarding the success rate of PGTA. Subsequently, the obtained information is sent to the terminal, and the terminal displays to the user "The success rate of PGTA is 60%."

[0210] Examples of prompt sentences:

[0211] User: What is the success rate of PGTA?

[0212] Server: Retrieving information from the database...

[0213] Server: The success rate of PGTA is approximately 60%.

[0214] With this system, users can quickly and accurately obtain detailed information on specific infertility treatment methods. In addition, since it has a function of answering inquiries in a chat format, users can obtain information in an interactive manner. This greatly improves the convenience for users.

[0215] The flow of the specific process in Example 2 will be described with reference to FIG. 13.

[0216] Step 1:

[0217] The user inputs an inquiry from the terminal.

[0218] As a specific operation, the user opens a browser on a smartphone or a personal computer and enters "What is the success rate of PGTA?" in the search bar. The input inquiry is displayed in the input field of the terminal.

[0219] Input: Inquiry input by the user (e.g., "What is the success rate of PGTA?")

[0220] Output: Inquiry displayed in the input field of the terminal

[0221] Step 2:

[0222] The terminal sends the inquiry to the server.

[0223] The terminal sends the inquiry input by the user to the server as an HTTP request. At this time, the terminal sends the inquiry content to the server in JSON format.

[0224] Input: Inquiry input by the user (e.g., "What is the success rate of PGTA?")

[0225] Output: HTTP request sent to the server (example: {"query": "What is the success rate of PGTA?"})

[0226] Step 3:

[0227] The server analyzes the query.

[0228] The server analyzes the received HTTP request and extracts the query content. For example, it recognizes that the query is "What is the success rate of PGTA?".

[0229] Input: HTTP request sent from the terminal (example: {"query": "What is the success rate of PGTA?"})

[0230] Output: Analyzed query content (example: "What is the success rate of PGTA?")

[0231] Step 4:

[0232] The server accesses the database to obtain information.

[0233] The server sends a query to the database based on the query content. For example, it executes a query like "SELECT success_rate FROM treatments WHERE name='PGTA'". The database returns a success rate of "60%".

[0234] Input: Analyzed query content (example: "What is the success rate of PGTA?")

[0235] Output: Information obtained from the database (example: "60%")

[0236] Step 5:

[0237] The server sends the obtained information to the terminal.

[0238] The server converts the information obtained from the database into JSON format and sends it to the terminal as an HTTP response. For example, it sends information such as "The success rate of PGTA is 60%".

[0239] Input: Information obtained from the database (example: "60%")

[0240] Output: HTTP response sent to the terminal (example: {"response": "The success rate of PGTA is 60%"})

[0241] Step 6:

[0242] The terminal displays the information to the user.

[0243] The terminal analyzes the information received from the server and displays it in a user-friendly format. For example, it displays "The success rate of PGTA is 60%" on the screen.

[0244] Input: HTTP response sent from the server (example: {"response": "The success rate of PGTA is 60%"})

[0245] Output: Information displayed to the user (example: "The success rate of PGTA is 60%")

[0246] (Application Example 2)

[0247] Next, Application Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0248] The conventional infertility treatment information providing system is specialized in providing information related to infertility treatment, so there is a problem that users cannot obtain information related to security. In addition, a separate system for providing security information is required, which also causes a problem of reduced convenience for users.

[0249] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosures at research institutions; means for providing information regarding infertility treatment based on the information obtained from the database; means for responding to an inquiry from a user based on the information obtained from the database; means for referring to a database for providing security information; and means for responding to the user based on the security information obtained from the database. Thereby, it becomes possible to provide both infertility treatment information and security information in one system.

[0250] "Infertility treatment information" refers to all information related to infertility treatment, including past treatment results, statistical information, and information disclosures at research institutions.

[0251] "Database" refers to an aggregate of information that systematically organizes and stores specific information so that it can be searched and acquired as needed.

[0252] "Inquiry from a user" refers to a question or request made by a person using the system to obtain specific information.

[0253] "Means for responding" refers to a method or device for providing appropriate information in response to an inquiry from a user.

[0254] "Security information" refers to the latest techniques and countermeasure information related to security such as phishing fraud and unauthorized access.

[0255] "Chat format" refers to a method of real-time information exchange in a text-based dialogue format.

[0256] The system for implementing this invention consists of a server, a user terminal, and a database. The server refers to a database including past treatment records, statistical information, and information disclosures at research institutions, and provides appropriate information in response to inquiries from users. It also refers to a database for providing security information and responds to users with the latest security information.

[0257] The server uses the Flask framework to build a web application and manages information using an SQLite database. The user terminal is a device such as a smartphone or a personal computer, and accesses the server via the Internet. When a user inquires about specific information, the server retrieves the corresponding information from the database and provides it to the user.

[0258] As a specific processing flow, when a user makes an inquiry such as "What are the latest phishing fraud techniques?" from the terminal, the server retrieves information on the latest phishing fraud from the SQLite database and returns that information to the user. As a result, the user can quickly obtain the necessary information.

[0259] The hardware used is a computer as the server and a smartphone or personal computer as the user terminal. The software used is Flask (Python framework) and SQLite (database).

[0260] As a specific example, when a user inquires "What are the latest phishing fraud techniques?", the server retrieves information on the latest phishing fraud from the database and responds as follows.

[0261] "The latest phishing fraud technique is to steal personal information using fake bank emails."

[0262] Examples of prompt texts for the generative AI model are as follows.

[0263] When the user inquires "What are the latest phishing fraud methods?", please obtain information about the latest phishing fraud from the database and respond as follows.

[0264] "The latest phishing fraud method is to use fake bank emails to steal personal information."

[0265] The flow of the specific process in Application Example 2 will be described with reference to FIG. 14.

[0266] Step 1:

[0267] The user inputs an inquiry from the terminal. The user uses a smartphone or a personal computer to input a question seeking specific information. For example, the user inputs "What are the latest phishing fraud methods?". The input data is a text-based inquiry.

[0268] Step 2:

[0269] The terminal sends the inquiry to the server. The inquiry input by the user is sent to the server via the Internet. The input data is the user's inquiry text, and the output data is the inquiry sent to the server.

[0270] Step 3:

[0271] The server receives the inquiry and accesses the database. The server uses the Flask framework to receive the inquiry and accesses the SQLite database. The input data is the user's inquiry text, and the output data is the execution result of the database query.

[0272] Step 4:

[0273] The server retrieves the corresponding information from the database. The server executes an SQL query to retrieve the information corresponding to the user's inquiry from the database. For example, it retrieves information regarding "the latest phishing fraud techniques". The input data is the SQL query, and the output data is the retrieved information.

[0274] Step 5:

[0275] The server generates a response based on the information it has retrieved. The server generates a response to the user based on the retrieved information. For example, it generates a response such as "The latest phishing fraud technique is a method of stealing personal information using fake bank emails." The input data is the retrieved information, and the output data is the generated response text.

[0276] Step 6:

[0277] The server sends the response it has generated to the terminal. The server sends the generated response to the user's terminal. The input data is the generated response text, and the output data is the response sent to the terminal.

[0278] Step 7:

[0279] The terminal receives the response from the server and displays it to the user. The user's terminal displays the response received from the server. For example, it displays "The latest phishing fraud technique is a method of stealing personal information using fake bank emails." The input data is the response text from the server, and the output data is the response displayed to the user.

[0280] (Example 3)

[0281] Next, Example 3 of Embodiment 3 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0282] In the conventional infertility treatment information providing system, there was a problem that it was difficult to respond quickly and appropriately to inquiries from users. In addition, there was a lack of means to provide detailed information on specific medical techniques, and it was difficult for users to obtain the information they needed in a timely manner. Furthermore, since there was no inquiry response function in the chat format, the user experience was degraded.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0284] In this invention, the server includes means for receiving an inquiry from a user, means for analyzing the inquiry, means for obtaining information from a database based on the analysis result, means for transmitting a prompt sentence to an AI model generated based on the obtained information, and means for returning a response from the generated AI model to the user. Thereby, it becomes possible to respond quickly and appropriately to an inquiry from a user. In addition, by including means for providing detailed information on a specific medical technique, the user can obtain the information they need in a timely manner. Furthermore, by including an inquiry response function in the chat format, the user experience can be improved.

[0285] The "means for receiving an inquiry from a user" is a function for the server to receive an inquiry sent by a user through a web browser or a mobile application.

[0286] The "means for analyzing the inquiry" is a function for analyzing the received inquiry content and extracting keywords and intentions.

[0287] The "means for obtaining information from a database" is a function for obtaining necessary information from a database based on the analysis result.

[0288] The "means for sending a prompt sentence to the generative AI model" is a function for sending the prompt sentence generated based on the acquired information to the generative AI model.

[0289] The "means for returning the response from the generative AI model to the user" is a function for returning the response received from the generative AI model to the user.

[0290] The "means for providing information on a specific medical technique" is a function for providing the user with detailed information on a specific medical technique.

[0291] The "means for responding to user inquiries in a chat format" is a function for responding in real time to user inquiries in a chat format.

[0292] Mode for Carrying Out the Invention

[0293] This invention is a system for quickly and appropriately responding to user inquiries. The following describes specific embodiments of this system.

[0294] 1. Generation of the System Program

[0295] The system program is developed using Python and operates as a web server using the Flask framework. MySQL is used for the database, and a general generative AI model (e.g., GPT-3 (registered trademark)) is used for the generative AI model.

[0296] 2. Program Processing

[0297] The server receives an inquiry from the user and analyzes the inquiry. For the analysis, a text analysis library (e.g., NLTK or spaCy) is used. Based on the analysis result, the server acquires the necessary information from the database. Based on the acquired information, the server sends a prompt sentence to the generative AI model and returns the response from the generative AI model to the user.

[0298] 3. Specific Example

[0299] Consider the case where a user sends a query "What are the advantages and disadvantages of two - stage transplantation?" using a web browser or a mobile app. In this case, the server processes as follows.

[0300] 1. The user sends a query in chat format: "What are the advantages and disadvantages of two - stage transplantation?"

[0301] 2. The server receives and analyzes this query.

[0302] 3. The server executes an SQL query to obtain information about "the advantages and disadvantages of two - stage transplantation" from the MySQL database.

[0303] 4. Based on the obtained information, the following prompt sentence is input into the generative AI model.

[0304] Example of prompt sentence: "Please tell me about the advantages and disadvantages of two - stage transplantation. The advantages are 〇〇 and the disadvantages are △△."

[0305] 5. The generative AI model (e.g., GPT - 3) generates a response based on this prompt sentence.

[0306] 6. The server returns the generated response to the user in real - time.

[0307] In this way, the system can respond quickly and appropriately to the user's query. The flow of the specific process in Example 3 will be described with reference to Figure 15.

[0308] Step 1:

[0309] The user sends a query

[0310] The user sends an inquiry in chat format using a web browser or a mobile app. For example, the user enters "What are the advantages and disadvantages of two-stage transplantation?" and clicks the send button. The input is the content of the user's inquiry, and the output is an HTTP request to the server.

[0311] Step 2:

[0312] The server receives the inquiry

[0313] The server receives the HTTP request from the user using the Flask framework. The received request contains the content of the user's inquiry. The input is the HTTP request from the user, and the output is the text data of the inquiry content.

[0314] Step 3:

[0315] The server analyzes the inquiry

[0316] The server analyzes the received inquiry content using a text analysis library (such as NLTK or spaCy). Through the analysis, keywords and intentions are extracted. The input is the text data of the inquiry content, and the output is the analysis result (keywords and intentions).

[0317] Step 4:

[0318] The server retrieves information from the database

[0319] The server retrieves the necessary information from the MySQL database based on the analysis result. For example, to retrieve information about "the advantages and disadvantages of two-stage transplantation", an SQL query is executed. The input is the analysis result, and the output is the information retrieved from the database.

[0320] Step 5:

[0321] The server sends a prompt sentence to the generative AI model

[0322] Based on the acquired information, the server generates a prompt sentence and sends it to the generative AI model. For example, it generates a prompt sentence such as "Please tell me the advantages and disadvantages of two-stage transplantation. The advantages are 〇〇, and the disadvantages are △△." The input is the information acquired from the database, and the output is the prompt sentence to the generative AI model.

[0323] Step 6:

[0324] The generative AI model generates a response

[0325] Based on the received prompt sentence, the generative AI model generates a response. For example, it generates a response such as "The advantages of two-stage transplantation are a high success rate and a low burden on the patient. On the other hand, the disadvantages are that the surgery is complex and time-consuming." The input is the prompt sentence, and the output is the generated response.

[0326] Step 7:

[0327] The server returns the response to the user

[0328] The server returns the response received from the generative AI model to the user. Specifically, it returns the response as an HTTP response and displays it on the user's screen. The input is the generated response, and the output is the HTTP response to the user.

[0329] (Application Example 3)

[0330] Next, Application Example 3 of Morphological Example 3 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0331] In the conventional infertility treatment information providing system, there has been a problem that it is difficult to provide a prompt and accurate response to inquiries from users. In addition, due to the lack of detailed information provision regarding specific infertility treatment methods, there has also been a problem that it takes time for users to obtain the necessary information. Furthermore, there has been a lack of technology for generating appropriate responses to users' questions.

[0332] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following respective means.

[0333] In this invention, the server includes means for referring to a database including past treatment records, statistical information, and information disclosures at research institutions, means for providing information regarding infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, and means for generating an appropriate response to users' questions using a generative AI model. As a result, users can obtain a prompt and accurate response, and detailed information regarding specific infertility treatment methods is also provided, enabling them to quickly obtain the necessary information.

[0334] "Past treatment records" refer to data regarding the results and progress of infertility treatments performed previously.

[0335] "Statistical information" refers to data indicating the results of aggregating and analyzing a plurality of treatment data.

[0336] "Information disclosures at research institutions" refer to research results and reports regarding infertility treatment publicly disclosed by academic institutions and medical institutions.

[0337] "Database" is a system for systematically managing and storing data such as past treatment records, statistical information, and information disclosures at research institutions.

[0338] "Information regarding infertility treatment" refers to detailed data regarding methods, effects, side effects, success rates, etc. of infertility treatment.

[0339] "Inquiries from users" refer to the act of an individual using the system to seek questions and information regarding infertility treatment.

[0340] "Generative AI model" refers to an algorithm or program that uses artificial intelligence to generate appropriate responses to users' questions.

[0341] "Appropriate response" refers to an answer that provides accurate and useful information in response to a user's question.

[0342] The system for implementing this invention is configured as follows. The server includes means for referring to a database containing past treatment records, statistical information, and information disclosures from research institutions, means for providing information regarding infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, and means for generating an appropriate response to a user's question using a generative AI model.

[0343] Hardware and Software to be Used

[0344] Hardware: Server, Smartphone

[0345] Software: Python, SQLite, OpenAI (registered trademark) API

[0346] Data Processing and Data Calculation

[0347] The server first connects to a database containing past treatment records, statistical information, and information disclosures from research institutions using SQLite. When a user accesses the system using a smartphone and makes an inquiry in chat format, the server analyzes the content of the inquiry.

[0348] Information Acquisition from the Database

[0349] If the user's inquiry is about a specific infertility treatment method, the server retrieves the corresponding information from the database and provides it to the user. For example, if the user asks, "What are the advantages and disadvantages of two-stage transplantation?", the server retrieves information about two-stage transplantation from the database and generates a response based on it.

[0350] Use of the generation AI model

[0351] If the user's inquiry is not directly related to the database, the server uses the generation AI model to generate an appropriate response. Specifically, the OpenAI API is used to generate a prompt sentence for the user's question, and based on that prompt sentence, the AI generates a response.

[0352] Specific example

[0353] For example, if the user asks, "Tell me the specifications of the iPhone (registered trademark) 13", the server retrieves the specification information of the iPhone 13 from the database and returns that information to the user. Also, if the user asks, "What are the advantages and disadvantages of two-stage transplantation?", the server sends the following prompt sentence to the generation AI model:

[0354] User's question: What are the advantages and disadvantages of two-stage transplantation?

[0355] Answer:

[0356] Based on this prompt sentence, the generation AI model generates an appropriate response and provides it to the user. As a result, the user can obtain quick and accurate information.

[0357] The flow of the specific process in Application Example 3 will be described with reference to FIG. 16.

[0358] Step 1:

[0359] The user accesses the system using a smartphone and makes an inquiry in a chat format.

[0360] Input: User's question (e.g., "What are the advantages and disadvantages of two-stage transplantation?")

[0361] Output: The content of the user's question is sent to the server.

[0362] Specific operation: The user opens the chat application on the smartphone, enters the question, and presses the send button.

[0363] Step 2:

[0364] The server receives the user's question and analyzes the content.

[0365] Input: Content of the user's question

[0366] Output: Analysis result of the question content (e.g., "Question about two-stage transplantation")

[0367] Specific operation: The server analyzes the received text data using a natural language processing algorithm to identify the intention of the question.

[0368] Step 3:

[0369] The server connects to the database and searches for the relevant information.

[0370] Input: Analysis result of the question content

[0371] Output: Information obtained from the database (e.g., "Information about the advantages and disadvantages of two-stage transplantation")

[0372] Specific operation: The server sends a query to the SQLite database to obtain the relevant information.

[0373] Step 4:

[0374] The server generates a response based on the information retrieved from the database.

[0375] Input: Information retrieved from the database

[0376] Output: Content of the response to the user (e.g., "The advantages of two-stage transplantation are..., and the disadvantages are...")

[0377] Specific operation: The server formats the retrieved information into text format and generates a response for sending to the user.

[0378] Step 5:

[0379] The server uses the generated AI model to generate an appropriate response to the user's question.

[0380] Input: Content of the user's question

[0381] Output: Response content by the generated AI model (e.g., "The advantages and disadvantages of two-stage transplantation are as follows...")

[0382] Specific operation: The server sends the prompt text to the OpenAI API and receives the generated response.

[0383] Step 6:

[0384] The server sends the generated response to the user.

[0385] Input: Generated response content

[0386] Output: Response message displayed on the user's smartphone

[0387] Specific operation: The server sends the generated response to the user through the chat application and is displayed on the user's smartphone.

[0388] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion specific model 59 and perform specific processing using the user's emotion.

[0389] "Form Example 1"

[0390] As an embodiment of the present invention, there is a infertility treatment information providing system combined with an emotion engine for recognizing the user's emotion. When the user makes an inquiry to the system, this system recognizes the user's emotion by the emotion engine. The emotion engine analyzes the emotion from the user's text input or voice input, and the system uses the result. For example, when the user shows an anxious emotion, the system recognizes the emotion and provides information to relieve the anxiety.

[0391] "Form Example 2"

[0392] Also, as another embodiment of the present invention, there is a system in which an emotion engine provides information on infertility treatment based on the user's emotion. In this system, the emotion engine analyzes the user's emotion and provides information suitable for that emotion. For example, when the user shows a hopeful emotion, the system provides information such as success cases and new treatment methods.

[0393] "Form Example 3"

[0394] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine responds to an inquiry from the user based on the user's emotion. In this system, the emotion engine analyzes the user's emotion and generates a response suitable for that emotion. For example, when the user is discouraged, the system generates a response including words of encouragement.

[0395] The processing flow of each form example will be described below.

[0396] "Form Example 1"

[0397] Step 1: The user makes an inquiry to the system.

[0398] Step 2: The emotion engine analyzes the emotion from the user's text input or voice input.

[0399] Step 3: The system uses the analysis result of the emotion engine to provide information suitable for the user's emotion.

[0400] "Form Example 2"

[0401] Step 1: The emotion engine analyzes the user's emotion.

[0402] Step 2: The system uses the analysis result of the emotion engine to provide information suitable for the user's emotion.

[0403] "Form Example 3"

[0404] Step 1: The emotion engine analyzes the user's emotion.

[0405] Step 2: The system uses the analysis result of the emotion engine to generate a response suitable for the user's emotion.

[0406] (Example 1)

[0407] Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0408] In the conventional infertility treatment information providing system, since information is provided without considering the user's emotion, the anxiety and stress felt by the user cannot be sufficiently reduced. Also, since appropriate information provision according to the user's emotion is not performed, there is a problem that the user's satisfaction decreases.

[0409] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following respective means.

[0410] In this invention, the server includes means for referring to a database containing past treatment records, statistical information, and information disclosures by research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, means for analyzing emotions to recognize the emotions of users, and means for providing appropriate information based on the emotions recognized by the emotion analysis means. As a result, it becomes possible to provide appropriate information according to the emotions of users, reduce the anxiety and stress of users, and improve the satisfaction level.

[0411] The "past treatment records" refer to data regarding the results and processes of infertility treatments conducted in the past.

[0412] The "statistical information" refers to the results of aggregating and analyzing data related to infertility treatment.

[0413] The "information disclosures by research institutions" refer to research results and reports on infertility treatment publicly disclosed by research institutions.

[0414] The "database" is a system for organizing and storing information including past treatment records, statistical information, and information disclosures by research institutions.

[0415] The "means for analyzing emotions" is a technology for analyzing emotions from the text input or voice input of users.

[0416] The "means for providing appropriate information" is a technology for selecting and providing information beneficial to users based on the results of emotion analysis of users.

[0417] The "means for responding to inquiries" is a technology for providing answers based on the information obtained from the database in response to questions or requests from users.

[0418] The present invention is a system for providing infertility treatment information, which refers to a database including past treatment records, statistical information, and information disclosures by research institutions, and provides appropriate information to users. Furthermore, it has a function of recognizing the emotions of users and providing information based on those emotions.

[0419] Hardware and software to be used

[0420] 1. Server

[0421] The server uses a database management system (e.g., MySQL, PostgreSQL) to manage data including past treatment records, statistical information, and information disclosures by research institutions.

[0422] The server uses web server software (e.g., Apache, Nginx) to receive and process HTTP requests from users.

[0423] 2. Emotion analysis means

[0424] As the emotion analysis means, a natural language processing API (e.g., Google (registered trademark) Cloud Natural Language API, IBM Watson (registered trademark) Tone Analyzer) is used. Thereby, emotions are analyzed from the text input or voice input of users.

[0425] 3. Terminal

[0426] Users access the system using a web browser (e.g., GOOGLE CHROME (registered trademark), Safari) or a mobile application.

[0427] Data processing and data calculation

[0428] 1. Database reference

[0429] The server uses a database management system to refer to data including past treatment records, statistical information, and information disclosure at research institutions. Thereby, it obtains the basic data for providing appropriate information in response to user inquiries.

[0430] 2. Sentiment Analysis

[0431] The server sends the user's text input or voice input to the sentiment analysis means to analyze the user's sentiment. The analysis result is returned to the server in JSON format.

[0432] 3. Information Provision

[0433] Based on the sentiment analysis result, the server searches for appropriate information from the database and provides it to the user. For example, when the user shows anxiety, it provides information on success stories and relaxation methods to relieve the anxiety.

[0434] Specific Example

[0435] For example, when the user enters the text "I'm anxious because my recent treatment isn't going well", the process proceeds as follows.

[0436] 1. The user accesses the system using Google Chrome.

[0437] 2. The user enters "I'm anxious because my recent treatment isn't going well" in the text box.

[0438] 3. The server receives this input through Apache.

[0439] 4. The server calls the Google Cloud Natural Language API and sends the input data.

[0440] 5. The sentiment analysis means analyzes the sentiment of "anxiety".

[0441] 6. The server receives the analysis result in JSON format.

[0442] 7. The server refers to the MySQL database.

[0443] 8. The server searches for information on success stories and relaxation methods for relieving anxiety.

[0444] 9. The server displays the search results on a web page and provides them to the user.

[0445] Examples of prompt sentences

[0446] Examples of prompt sentences to be input into the generation AI model are as follows:

[0447] When the user inputs "I'm anxious because my recent treatment isn't going well", please explain how the emotion engine will react and what information the server will provide.

[0448] By using this prompt sentence, the generation AI model can recognize the user's emotion and understand the operation of the system that provides appropriate information.

[0449] The flow of the specific process in Example 1 will be described with reference to FIG. 17.

[0450] Step 1:

[0451] The user accesses the system.

[0452] The user accesses the system using a web browser or a mobile app. For example, a browser such as Google Chrome or Safari is used. The input is the user's access request, and the output is the display of the system's home page.

[0453] Step 2:

[0454] The user inputs an inquiry.

[0455] The user uses a text box or voice input function to input an inquiry. For example, the user inputs "I'm worried because the recent treatment isn't going well." The input is the user's text or voice data, and the output is that the data is sent to the server.

[0456] Step 3:

[0457] The server receives the user's input.

[0458] The server receives an HTTP request and obtains the user's input data. For example, it uses a web server such as Apache or Nginx. The input is the user's inquiry data, and the output is that the data is ready to be processed within the server.

[0459] Step 4:

[0460] The server calls the emotion engine.

[0461] The server calls the API of the emotion engine and sends the user's input data. For example, it uses the Google Cloud Natural Language API or the IBM Watson Tone Analyzer. The input is the user's text or voice data, and the output is that the emotion analysis result is returned.

[0462] Step 5:

[0463] The emotion engine analyzes the user's emotion.

[0464] The emotion engine analyzes the user's text input or voice input to identify the emotion. For example, it recognizes the emotion of "anxiety". The input is the user's text or voice data, and the output is the analyzed emotion data.

[0465] Step 6:

[0466] The server receives the analysis result.

[0467] The server receives the analysis result from the emotion engine and proceeds to the next process. For example, it receives the result in JSON format. The input is the emotion analysis result, and the output is that the result becomes available within the server.

[0468] Step 7:

[0469] The server references the database.

[0470] The server uses a database management system such as MySQL or PostgreSQL to reference the database. The input is the emotion analysis result and the content of the user's inquiry, and the output is that relevant information is retrieved from the database.

[0471] Step 8:

[0472] The server searches for appropriate information.

[0473] The server searches for appropriate information from the database based on the user's emotion. For example, it searches for success stories or relaxation methods to relieve anxiety. The input is the information retrieved from the database, and the output is the appropriate information to provide to the user.

[0474] Step 9:

[0475] The server provides the search result to the user.

[0476] The server returns the search result to the user. For example, it displays the result on a web page or reads the result aloud. The input is the appropriate information, and the output is the information provided to the user.

[0477] (Application Example 1)

[0478] Next, Application Example 1 of Embodiment 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0479] In an information providing system related to infertility treatment, since information provision considering the user's feelings is insufficient, the user may feel anxiety and stress. Further, in the conventional system, information provision within a virtual space is not performed, and there is a problem that it is difficult for the user to obtain information more intuitively.

[0480] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0481] In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions; means for providing information related to infertility treatment based on the information obtained from the database; means for responding to an inquiry from the user based on the information obtained from the database; means for recognizing the user's feelings using an emotion engine that analyzes the user's feelings; means for providing appropriate information according to the recognized feelings; and means for providing an interface for browsing information within a virtual space. Thereby, it becomes possible to provide appropriate information according to the user's feelings, and the user can obtain information intuitively within the virtual space.

[0482] The "database" is a system that organizes and stores information including past treatment results, statistical information, and information disclosure at research institutions, and can be referred to as necessary.

[0483] The "infertility treatment information providing means" is a function for providing the user with information related to infertility treatment based on the information obtained from the database.

[0484] The "inquiry response means" is a function for responding to an inquiry from the user based on the information obtained from the database.

[0485] The "Emotion Engine" is a technology that analyzes emotions from a user's text input or voice input and makes the results available for the system to use.

[0486] The "Emotion Recognition Means" is a function that recognizes a user's emotions using the Emotion Engine.

[0487] The "Emotion Response Means" is a function that provides appropriate information according to the recognized emotions.

[0488] The "Virtual Interface" is an interface for a user to view information within a virtual space.

[0489] The system for implementing this invention has the following configuration.

[0490] Configuration of the System

[0491] 1. Database Reference Means

[0492] The server refers to a database including past treatment records, statistical information, and information disclosures at research institutions. This database organizes and stores various information related to infertility treatment and can be accessed quickly as needed.

[0493] 2. Infertility Treatment Information Providing Means

[0494] The server provides information related to infertility treatment to the user based on the information obtained from the database. This information provision is carried out based on the specific treatment methods and statistical data requested by the user.

[0495] 3. Inquiry Response Means

[0496] The server responds to inquiries from the user based on the information obtained from the database. As a result, the user can obtain the necessary information in real time.

[0497] 4. Emotion recognition means

[0498] The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes emotions from the user's text input or voice input and makes the results available for the system to use.

[0499] 5. Emotion response means

[0500] The server provides appropriate information according to the recognized emotions. For example, when the user is feeling anxious, it provides reassuring information.

[0501] 6. Virtual interface

[0502] The terminal provides an interface for the user to view information within the virtual space. This enables the user to obtain information intuitively.

[0503] Hardware and software used

[0504] Hardware: Smartphones, head-mounted displays

[0505] Software: Python, emotion recognition library (EmotionEngine), database management system (TreatmentDatabase)

[0506] Data processing and calculation

[0507] 1. Acquisition of user input

[0508] The terminal acquires text or voice input from the user.

[0509] 2. Emotion analysis

[0510] The server analyzes emotions from the user's input using an emotion engine.

[0511] 3. Information Provision

[0512] Based on the results of sentiment analysis, the server retrieves appropriate information from the database and provides it to the user.

[0513] Specific Example

[0514] When the user inputs "I'm worried about my recent treatment results", the sentiment engine analyzes it as "uneasy", and the server provides reassuring information.

[0515] When the user inputs "I want to know about the latest treatment methods", the server provides general treatment information.

[0516] Examples of Prompt Sentences

[0517] When the user inputs "I'm worried about my recent treatment results", the sentiment engine analyzes it as "uneasy", and please provide reassuring information.

[0518] In this way, it becomes possible to provide appropriate information according to the user's sentiment, and a system is realized that can intuitively obtain information within the virtual space.

[0519] The flow of specific processing in Application Example 1 will be described with reference to FIG. 18.

[0520] Step 1:

[0521] The user inputs an inquiry to the terminal in text or voice.

[0522] Input: User's text or voice input (e.g., "I'm worried about my recent treatment results")[[]]END]]

[0523] Output: User input data

[0524] Specific operation: The terminal receives the user's input and saves it as text data or voice data.

[0525] Step 2:

[0526] The terminal sends the user's input data to the server.

[0527] Input: User input data

[0528] Output: User input data sent to the server

[0529] Specific operation: The terminal sends the user's input data to the server via the network.

[0530] Step 3:

[0531] The server analyzes the emotion from the user's input data using an emotion engine.

[0532] Input: User input data

[0533] Output: User emotion data (e.g., "uneasy")

[0534] Specific operation: The server activates the emotion engine and analyzes the user's input data to identify the emotion. The emotion engine performs text analysis and voice analysis, and classifies the user's emotion into categories such as "uneasy", "relieved", "interested".

[0535] Step 4:

[0536] The server obtains appropriate information from the database based on the emotion data.

[0537] Input: User emotion data (e.g., "uneasy")

[0538] Output: Appropriate information data (e.g., "information to relieve uneasiness")

[0539] Specific operation: The server searches the database based on the emotion data and obtains information corresponding to the user's emotion. For example, if it is analyzed as "uneasy", information for calming the user is extracted from the database.

[0540] Step 5:

[0541] The server transmits the information obtained to the terminal.

[0542] Input: Appropriate information data

[0543] Output: Information data transmitted to the terminal

[0544] Specific operation: The server transmits the obtained information data to the terminal via the network.

[0545] Step 6:

[0546] The terminal displays the information received to the user.

[0547] Input: Received information data

[0548] Output: Information displayed to the user

[0549] Specific operation: The terminal displays the received information data to the user. The display methods include text display, voice reading, or display using a virtual interface, etc.

[0550] In this way, an appropriate information provision according to the user's emotion becomes possible, and a system is realized in which information can be obtained intuitively within the virtual space.

[0551] (Embodiment 2)

[0552] Next, Embodiment 2 of Form Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0553] In a conventional infertility treatment information providing system, it may be difficult to respond appropriately and promptly to inquiries from users. In addition, since information is not provided according to the user's emotions, the user's satisfaction may decrease. Furthermore, since there is a lack of means for providing detailed information on specific infertility treatment methods, users may not be able to obtain sufficient information they need.

[0554] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0555] In this invention, the server includes means for receiving an inquiry from a user, means for analyzing the content of the received inquiry, means for obtaining information from a database, means for providing the obtained information to the user, and means for analyzing the user's emotion using an emotion engine and providing information suitable for the emotion. As a result, it becomes possible to respond quickly and appropriately to an inquiry from a user, and since information is provided according to the user's emotion, the user's satisfaction is improved. In addition, detailed information on a specific infertility treatment method can be provided, and it becomes possible for the user to obtain sufficient information they need.

[0556] The "means for receiving an inquiry from a user" is an interface for the system to receive questions and requests input by the user.

[0557] The "means for analyzing the content of the received inquiry" is a function for understanding the received user inquiry using technologies such as natural language processing and extracting appropriate information.

[0558] The "means for obtaining information from a database" is a function for searching and obtaining relevant information from the database based on the analyzed inquiry content.

[0559] The "means for providing the acquired information to the user" is an interface for presenting the information acquired from the database to the user in an easy-to-understand manner.

[0560] The "means for analyzing the user's emotions using an emotion engine and providing information suitable for the emotions" is a function for selecting and providing information according to the user's emotional state by using a technology for analyzing the user's emotions.

[0561] The "means for providing information on specific infertility treatment methods" is a function for providing the user with detailed information on specific infertility treatment methods such as PGTA and two-stage transplantation.

[0562] The "means for responding to inquiries from the user in a chat format" is an interface for interacting with the user in a chat format and responding to inquiries in real time.

[0563] Mode for Carrying Out the Invention

[0564] This invention is a system that responds to inquiries from the user based on information acquired from a database. Specifically, when the user inquires about a specific infertility treatment method, the system acquires information on the corresponding treatment method from the database and responds to the user based on that. It also includes a function for analyzing the user's emotions using an emotion engine and providing information suitable for the emotions.

[0565] Hardware and Software to be Used

[0566] The server uses the following hardware and software.

[0567] Hardware: High-performance server machine (e.g., Intel Xeon processor, 32GB RAM, 1TB SSD)

[0568] Software:

[0569] Database management system (e.g., MySQL)

[0570] Natural language processing engine (e.g., spaCy, NLTK)

[0571] Sentiment analysis engine (e.g., IBM Watson's sentiment analysis API)

[0572] The terminal is a device for the user to input inquiries and receive responses from the system. As the terminal, a personal computer, a smartphone, a tablet, etc. are used.

[0573] Description of program processing

[0574] When the server receives an inquiry from the user, it analyzes the content of the inquiry using the natural language processing engine. Based on the analysis result, the server retrieves the corresponding information from the MySQL database. The retrieved information is sent to the terminal and displayed to the user.

[0575] Furthermore, the server analyzes the user's sentiment using the sentiment analysis engine. Based on the analysis result, it selects information suitable for the user's sentiment and sends it to the terminal. The terminal displays the selected information to the user.

[0576] Specific example

[0577] When the user inquires "What is the success rate of PGTA?", the processing is performed in the following steps.

[0578] 1. The terminal receives the user's inquiry.

[0579] 2. The server extracts the keywords "PGTA" and "success rate" using the natural language processing engine.

[0580] 3. The server connects to the MySQL database and executes the following SQL query.

[0581] sql

[0582] SELECT success_rate FROM fertility_treatments WHERE treatment_name = 'PGTA';

[0583] 4. The server sends the obtained success rate data to the terminal.

[0584] 5. The terminal displays to the user that "The success rate of PGTA is 70%".

[0585] Also, when the user shows a desired emotion, the server uses an emotion analysis engine to select information about successful cases and new treatment methods based on the analysis results and sends it to the terminal. The terminal displays that "In recent research, a new treatment method has been developed".

[0586] Example of prompt sentence

[0587] Examples of prompt sentences for the generative AI model are shown below.

[0588] When the user asks "What is the success rate of PGTA?", generate a program that retrieves information about the success rate of PGTA from the database and provides it to the user.

[0589]

[0590] When the user shows a desired emotion, generate a program that uses an emotion engine to provide information such as successful cases and new treatment methods.

[0591] The above is the form for implementing this invention.

[0592] The flow of specific processing in Example 2 will be described with reference to FIG. 19.

[0593] Flow of program processing

[0594] Step 1: Receive the user's inquiry

[0595] The terminal receives the inquiry from the user. For example, the user enters "What is the success rate of PGTA?". The entered inquiry is sent from the terminal to the server.

[0596] Input: User's inquiry (e.g., "What is the success rate of PGTA?")

[0597] Output: Inquiry data sent to the server

[0598] Step 2: Analyze the content of the inquiry

[0599] The server analyzes the received inquiry content using a natural language processing engine. Specifically, NLP tools such as spaCy or NLTK are used to understand the intention of the inquiry and extract important keywords.

[0600] Input: Inquiry data sent from the terminal

[0601] Data processing: Extract keywords using a natural language processing engine (e.g., "PGTA", "success rate")

[0602] Output: Extracted keywords

[0603] Step 3: Retrieve information from the database

[0604] The server retrieves the corresponding information from the MySQL database based on the analysis results. For example, to retrieve information about "the success rate of PGTA", an SQL query is executed.

[0605] Input: Extracted keywords (e.g., "PGTA", "success rate")

[0606] Data calculation: Execute an SQL query to retrieve information from the database (example: SELECT success_rate FROM fertility_treatments WHERE treatment_name = 'PGTA';)

[0607] Output: Retrieved information (example: "The success rate of PGTA is 70%")

[0608] Step 4: Provide the information to the user

[0609] The server sends the retrieved information to the terminal. The terminal displays the received information to the user. For example, it displays "The success rate of PGTA is 70%".

[0610] Input: Retrieved information (example: "The success rate of PGTA is 70%")

[0611] Output: Information to be displayed to the user

[0612] Step 5: Provide information using the emotion engine (if necessary)

[0613] The server analyzes the user's emotion using the emotion engine. For example, it uses the emotion analysis API of IBM Watson. If the user shows a positive emotion, the server selects information about successful cases or new treatment methods and sends it to the terminal. The terminal displays the selected information to the user.

[0614] Input: User's emotion data

[0615] Data processing: Analyze the emotion using the emotion analysis engine and select appropriate information

[0616] Output: Information suitable for the user's displayed emotion (example: "In recent research, a new treatment method has been developed")

[0617] The above is the processing flow of the program of this system.

[0618] (Application Example 2)

[0619] Next, Application Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0620] In an information providing system related to infertility treatment, it is required to provide appropriate information according to the user's feelings. However, in the conventional system, since the same information is provided without considering the user's feelings, there is a problem that it is difficult to reduce the user's psychological burden.

[0621] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0622] In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions, means for providing information related to infertility treatment based on the information obtained from the database, means for responding to an inquiry from a user based on the information obtained from the database, means for analyzing the user's feelings, and means for providing appropriate information based on the feelings analysis means. As a result, it is possible to provide appropriate information according to the user's feelings, and the user's psychological burden can be reduced.

[0623] The "system for providing infertility treatment information" is a system that refers to a database including past treatment results, statistical information, and information disclosure at research institutions, and provides appropriate information related to infertility treatment in response to an inquiry from a user.

[0624] The "means for referring to the database" is means for obtaining necessary information from a database including past treatment results, statistical information, and information disclosure at research institutions.

[0625] The "means for providing information on infertility treatment" is a means for providing appropriate information on infertility treatment to users based on information obtained from a database.

[0626] The "means for responding to inquiries from users" is a means for responding based on information obtained from a database when a user inquires about a specific infertility treatment method.

[0627] The "means for analyzing the user's emotions" is a means for analyzing the user's facial expressions, tone of voice, etc. to determine the user's emotions.

[0628] The "means for providing appropriate information based on the emotion analysis means" is a means for providing information on infertility treatment suitable for the user's emotions based on the results of analyzing the user's emotions.

[0629] This invention is a system for providing infertility treatment information, which refers to a database including past treatment records, statistical information, and information disclosures by research institutions, and provides appropriate information on infertility treatment in response to inquiries from users. Furthermore, it has a function of analyzing the user's emotions and providing appropriate information based on those emotions.

[0630] Configuration of the System

[0631] This system is composed of the following main components.

[0632] 1. Database reference means:

[0633] The server refers to a database including past treatment records, statistical information, and information disclosures by research institutions. This database stores various information on infertility treatment.

[0634] 2. Information providing means:

[0635] Based on the information obtained from the database, the server provides users with information regarding infertility treatment. As a result, users can obtain information such as the latest treatment methods and success rates.

[0636] 3. Inquiry Response Means:

[0637] Based on the information obtained from the database, the server responds to inquiries from users. For example, when a user asks "What is the success rate of PGTA?", the server retrieves the corresponding information from the database and provides it to the user.

[0638] 4. Sentiment Analysis Means:

[0639] The server analyzes the user's facial expressions and tone of voice to judge the user's sentiment. For this purpose, the camera and microphone installed on the smart glasses are used.

[0640] 5. Information Provision Means Based on Sentiment:

[0641] Based on the sentiment analysis means, the server provides information suitable for the user's sentiment. For example, when the user shows a positive sentiment, information regarding successful cases and new treatment methods is provided.

[0642] Hardware and Software to be Used

[0643] Hardware:

[0644] Smart glasses (with camera and microphone)

[0645] Server

[0646] Software:

[0647] Python

[0648] OpenCV (image processing library)

[0649] Emotion Recognizer (Emotion Recognition Library)

[0650] Database (Database Access Library)

[0651] Process Flow

[0652] The server uses the camera and microphone of the smart glasses to obtain the user's expression and voice. The obtained data is used by the emotion recognition model to analyze the user's emotion. The user's inquiry is obtained, and the corresponding information is retrieved from the database. Based on the emotion analysis result, additional information (success cases and new treatment methods) is provided. Finally, the obtained information is displayed on the smart glasses.

[0653] Specific Example

[0654] For example, if the patient asks "What is the success rate of PGTA?" and shows a hopeful emotion, the smart glasses will display "The success rate of PGTA is 70%. Also, information on recent success cases and new treatment methods will be introduced."

[0655] Example of Prompt Sentence

[0656] Develop a smart glasses application that analyzes the patient's expression and voice and provides information on infertility treatment based on emotion. When the patient asks "What is the success rate of PGTA?", retrieve information from the database and also provide information on success cases and new treatment methods if the patient shows a hopeful emotion.

[0657] The specific process flow in Application Example 2 will be described with reference to Figure 20.

[0658] Step 1:

[0659] The server uses the camera and microphone of the smart glasses to obtain the user's expression and voice. The input is the user's face image and voice data, and the output is these data. Specifically, it takes a picture of the user's face with the camera and records the voice with the microphone.

[0660] Step 2:

[0661] The server runs an emotion recognition model using the obtained face image and voice data. The input is the face image and voice data obtained in Step 1, and the output is the user's emotion (e.g., hopeful, pessimistic, etc.). Specifically, it uses the EmotionRecognizer library to analyze the emotion from the image and voice.

[0662] Step 3:

[0663] The server obtains the user's inquiry. The input is the user's voice or text, and the output is the content of the inquiry. Specifically, it uses voice recognition technology to convert the user's voice into text and extracts the content of the inquiry.

[0664] Step 4:

[0665] The server obtains the corresponding information from the database. The input is the content of the inquiry obtained in Step 3, and the output is the information related to the corresponding infertility treatment. Specifically, it uses the Database library to search for the information corresponding to the content of the inquiry from the database.

[0666] Step 5:

[0667] The server selects additional information based on the emotion analysis result. The input is the emotion data obtained in Step 2 and the infertility treatment information obtained in Step 4, and the output is the additional information suitable for the emotion. Specifically, in the case of a hopeful emotion, it selects information about success cases and new treatment methods.

[0668] Step 6:

[0669] The server displays the final information on the smart glasses. The input is the information selected in step 5, and the output is the information displayed on the display of the smart glasses. Specifically, the acquired information is displayed on the display of the smart glasses in text form.

[0670] Step 7:

[0671] The user checks the information provided through the smart glasses. The input is the information displayed on the display of the smart glasses, and the output is the user's understanding and the next action. Specifically, the user reads the displayed information and considers the next treatment step or question.

[0672] (Example 3)

[0673] Next, Example 3 of Form Example 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0674] In the conventional infertility treatment information providing system, it has been difficult to provide a quick and appropriate response to inquiries from users. In addition, a function for generating a response according to the user's feelings is lacking, and an improvement in the user experience has been demanded. Furthermore, the provision of detailed information regarding specific infertility treatment methods has been insufficient.

[0675] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0676] In this invention, the server includes means for referring to a database containing past treatment records, statistical information, and information disclosures from research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, means for generating a response in natural language using a generative AI model, and means for analyzing the user's emotions and generating a response suitable for that emotion. This makes it possible to provide a quick and appropriate response to inquiries from users, and furthermore, by generating a response according to the user's emotions, the user experience can be improved.

[0677] The "database" is an aggregate of information including past treatment records, statistical information, and information disclosures from research institutions.

[0678] The "means for providing information on infertility treatment" is a function for providing users with information on infertility treatment based on the information obtained from the database.

[0679] The "means for responding to inquiries from users" is a function for returning a response to the inquiries input by users based on the information obtained from the database.

[0680] The "generative AI model" is an artificial intelligence model used to generate a response in natural language.

[0681] The "means for generating a response in natural language" is a function for generating an appropriate response to a user's inquiry in natural language using a generative AI model.

[0682] The "means for analyzing emotions" is a function for analyzing the user's emotions and generating an appropriate response based on those emotions.

[0683] The "means for responding in chat format" is a function for returning a response in real time through a chat interface to an inquiry from a user.

[0684] Mode for Carrying Out the Invention

[0685] This invention is an infertility treatment information providing system that provides real-time responses to inquiries from users. The system refers to a database including past treatment records, statistical information, and information disclosures from research institutions, and generates responses based on the acquired information. Additionally, it uses a generative AI model to generate natural language responses and analyzes the user's emotions to provide appropriate responses.

[0686] Hardware and Software to be Used

[0687] Server

[0688] The server accesses the database, receives, and processes inquiries from users. The server uses the following software:

[0689] Database Management System (DBMS)

[0690] Generative AI Model (e.g., GPT-4 (registered trademark))

[0691] Emotion Analysis Software (e.g., Tone Analyzer of IBM Watson)

[0692] Terminal

[0693] The terminal is a device for users to input inquiries and receive and display responses from the server. The terminal uses the following software:

[0694] Chat Interface

[0695] Data Processing and Data Calculation

[0696] Database Access

[0697] When the server receives an inquiry from a user, it accesses the database to obtain relevant information. For example, in response to an inquiry such as "What are the advantages and disadvantages of two-stage transplantation?", the server searches the database for information on two-stage transplantation and obtains information on the advantages and disadvantages.

[0698] Response generation by the generative AI model

[0699] Based on the information obtained, the server uses a generative AI model (GPT-4) to generate a natural language response. The generative AI model receives the inquiry content and the obtained information as inputs and generates an appropriate response.

[0700] Sentiment analysis

[0701] The server uses sentiment analysis software to analyze the user's sentiment. For example, if the user is discouraged, the sentiment analysis software detects that sentiment and generates a response that includes words of encouragement.

[0702] Specific example

[0703] Specific example 1: Inquiry regarding the advantages and disadvantages of two-stage transplantation

[0704] 1. The user enters "What are the advantages and disadvantages of two-stage transplantation?" into the chat.

[0705] 2. The terminal sends this inquiry to the server.

[0706] 3. The server receives the inquiry and obtains information on two-stage transplantation from the database.

[0707] 4. Based on the information obtained, the server uses a generative AI model (GPT-4) to generate a response.

[0708] 5. The server sends the generated response to the terminal.

[0709] 6. The terminal displays to the user, "The advantage of two-stage transplantation is that the success rate is high. The disadvantage is that the surgery becomes more complex."

[0710] Specific Example 2: Response Using an Emotion Engine

[0711] 1. The user enters in the chat, "Recently, work hasn't been going well and I'm feeling down."

[0712] 2. The terminal sends this inquiry to the server.

[0713] 3. The server receives the inquiry, and emotion analysis software analyzes the user's emotion.

[0714] 4. The emotion analysis software detects the user's discouragement and generates a response containing encouraging words.

[0715] 5. The server sends the generated response to the terminal.

[0716] 6. The terminal displays to the user, "That's really tough. But you've overcome many difficulties before. Surely you can overcome this one too."

[0717] In this way, the system can provide a quick and appropriate response to the user's inquiry, and by generating a response according to the user's emotion, it can improve the user experience. The flow of specific processing in Example 3 will be described with reference to FIG. 21.

[0718] Step 1:

[0719] The user inputs an inquiry in chat format.

[0720] Specific operation: The user uses the chat interface of the terminal to input questions or inquiries. For example, the user inputs, "What are the advantages and disadvantages of two-stage transplantation?"

[0721] Input: The content of the user's inquiry

[0722] Output: Data for which the inquiry content is sent to the terminal

[0723] Step 2:

[0724] The terminal sends the inquiry to the server.

[0725] Specific operation: The terminal sends the inquiry input by the user to the server in an appropriate format.

[0726] Input: The content of the user's inquiry

[0727] Output: Data for which the inquiry content is sent to the server

[0728] Step 3:

[0729] The server receives the inquiry and accesses the database to obtain relevant information.

[0730] Specific operation: The server receives the inquiry sent from the terminal and accesses the database to search for relevant information. For example, obtain information on the advantages and disadvantages of "two-stage transplantation".

[0731] Input: The content of the user's inquiry

[0732] Output: Relevant information obtained from the database

[0733] Step 4:

[0734] Based on the information obtained by the server, an AI model is used to generate a response.

[0735] Specific operation: Based on the acquired information, the server uses a generative AI model (e.g., GPT-4) to generate a natural language response. The generative AI model receives the query content and the acquired information as inputs and generates an appropriate response.

[0736] Input: Related information obtained from the database, the user's query content

[0737] Output: Natural language response generated by the generative AI model

[0738] Step 5:

[0739] The server sends the response generated to the terminal.

[0740] Specific operation: The server sends the response generated by the generative AI model to the terminal. This response is sent in a format that is easy for the user to understand.

[0741] Input: Natural language response generated by the generative AI model

[0742] Output: Response data sent to the terminal

[0743] Step 6:

[0744] The terminal displays the response to the user.

[0745] Specific operation: The terminal displays the response received from the server to the user. The user can view the response from the server through the chat interface.

[0746] Input: Response data sent from the server

[0747] Output: Response displayed to the user

[0748] Step 7:

[0749] The emotion engine analyzes the user's emotions and generates responses suitable for the emotions as needed.

[0750] Specific operations: The emotion engine analyzes the user's emotions. For example, when the user is discouraged, the emotion engine detects the emotion and generates a response containing words of encouragement. This emotion analysis uses emotion analysis software (e.g., IBM Watson's Tone Analyzer).

[0751] Input: User's emotion data

[0752] Output: Response data suitable for the emotion

[0753] (Application Example 3)

[0754] Next, Application Example 3 of Morphological Example 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0755] In a conventional infertility treatment information providing system, although appropriate information can be provided in response to an inquiry from a user, there is a problem that it is impossible to sufficiently eliminate the user's anxiety and doubts because it is impossible to generate a response according to the user's emotions. Also, in the security service, although it is required to provide appropriate support according to the user's emotions, there is a problem that it is difficult to achieve this with the current system.

[0756] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure by research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, and means including an emotion engine for analyzing the emotions of users and generating responses suitable for those emotions. Thereby, it becomes possible to provide appropriate information and support according to the emotions of users.

[0757] A "database" is a system that accumulates information including past treatment results, statistical information, and information disclosure by research institutions and can be referred to as necessary.

[0758] "Information providing means" is a function for providing users with information on infertility treatment based on the information obtained from the database.

[0759] "Response means" is a function for generating a response based on the information obtained from the database in response to an inquiry from a user and returning the response to the user.

[0760] An "emotion engine" is a system for analyzing the emotions of users and generating responses suitable for those emotions.

[0761] A "chat format" is a communication format in which a user makes an inquiry in a text-based manner and a response is returned in real time.

[0762] The system for implementing this invention mainly consists of a server, a user terminal, and a database. The server refers to a database including past treatment results, statistical information, and information disclosure by research institutions, and provides appropriate information in response to inquiries from users. In addition, it uses an emotion engine to analyze the emotions of users and generates responses suitable for those emotions.

[0763] Hardware and Software to be Used

[0764] Hardware: Servers, user terminals (such as smartphones, tablets, personal computers, etc.)

[0765] Software: Python, OpenAI API, EmotionRecognizer library, SecurityDatabase class

[0766] Data Processing and Data Calculation

[0767] When the server receives an inquiry from a user, it first analyzes the content of the inquiry. Next, it retrieves relevant information from the database and uses the EmotionRecognizer library to analyze the user's emotions. Based on the results of the emotion analysis, it generates an appropriate response using the OpenAI API.

[0768] Specific Example

[0769] For example, when a user inputs "The security camera at home is not working", the server processes it according to the following steps.

[0770] 1. Receive the user's input.

[0771] 2. Retrieve information about "security camera troubleshooting" from the database.

[0772] 3. Analyze the user's emotions using the EmotionRecognizer library.

[0773] 4. If the user is feeling anxious, generate a response such as "Please don't worry. Check the power of the camera and restart it. If the problem is not solved, please contact support." using the OpenAI API.

[0774] Examples of Prompt Sentences

[0775] Examples of prompt sentences when the user inputs "The home security camera is not operating" are as follows.

[0776] user_input = "The home security camera is not operating"

[0777] response = generate_response(user_input)

[0778] print(response)

[0779] In this way, it becomes possible to provide appropriate information and support according to the user's feelings.

[0780] The flow of the specific process in Application Example 3 will be described with reference to FIG. 22.

[0781] Step 1:

[0782] The user uses the terminal to input a security-related inquiry. For example, input "The home security camera is not operating". This input is sent to the server.

[0783] Input: User's inquiry (e.g., "The home security camera is not operating")

[0784] Output: User's inquiry sent to the server

[0785] Step 2:

[0786] The server analyzes the received user's inquiry. Specifically, it performs text analysis on the inquiry content and extracts relevant keywords.

[0787] Input: User's inquiry

[0788] Output: Extracted keywords (e.g., "security camera", "not operating")

[0789] Step 3:

[0790] The server searches the database based on the extracted keywords and retrieves relevant information. For example, it retrieves information regarding "troubleshooting security cameras".

[0791] Input: Extracted keywords

[0792] Output: Relevant information retrieved from the database (e.g., "Check the power of the camera and restart it.")

[0793] Step 4:

[0794] The server uses the EmotionRecognizer library to analyze the emotion from the user's inquiry. For example, it determines whether the user is feeling anxious.

[0795] Input: User's inquiry

[0796] Output: Analyzed user emotion (e.g., "anxious")

[0797] Step 5:

[0798] The server uses the OpenAI API to generate an appropriate response based on the analyzed emotion. For example, if the user is feeling anxious, it generates a response to reassure the user.

[0799] Input: Relevant information retrieved from the database, Analyzed user emotion

[0800] Output: Generated response (e.g., "Don't worry. Check the power of the camera and restart it. If the problem persists, contact support.")

[0801] Step 6:

[0802] The server sends the generated response to the user's terminal. The user can view the response on the terminal.

[0803] Input: Generated response

[0804] Output: Response sent to the user's terminal

[0805] In this way, it becomes possible to provide appropriate information and support according to the user's feelings.

[0806] The specific processing unit 290 sends 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 a voice indicating a user input with respect to the result of the specific processing. The control unit 46A sends voice 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 voice data.

[0807] The data generation model 58 is a so-called generative AI (Artificial Intelligence).

[0808] Examples of the data generation model 58 include generative AIs such as ChatGPT (registered trademark) (Internet search <URL: https: / / openai.com / blog / chatgpt>). The data generation model 58

[0809] It is obtained by performing deep learning on a neural network. In the data generation model 58, a prompt including an instruction is input, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is input. The data generation model 58 infers the input inference data according to 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 summary, etc.

[0810] As another example of generative AI, there is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) can be mentioned.

[0811] In the above embodiment, an example form in which specific processing is performed by the data processing device 12 has been given. However, the technology of the present disclosure is not limited to this, and specific processing may be performed by the smart device 14.

[0812] [Second Embodiment]

[0813] FIG. 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0814] As shown in FIG. 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0815] 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 the "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. Also, the database 24 and the communication I / F 26 are 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).

[0816] 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. Also, the microphone 238, the speaker 240, and the camera 42 are connected to the bus 52.

[0817] The microphone 238 receives instructions and the like from the user 20 by receiving the voice emitted by the user 20. The microphone 238 captures the voice emitted by the user 20, converts the captured voice into voice data, and outputs it to the processor 46. The speaker 240 outputs voice according to an instruction from the processor 46.

[0818] The camera 42 is a small digital camera equipped with an optical system such as a lens, a diaphragm, and a shutter, and an imaging device such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and images the surroundings of the user 20 (for example, an imaging range defined by an angle of view corresponding to the field of view of a general healthy person).

[0819] The communication I / F 44 is connected to the 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 performed in a secure state.

[0820] 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, specific processing is performed by the processor 28. The specific processing program 56 is stored in the storage 32.

[0821] The specific processing program 56 is an example of the "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 operating as the specific processing unit 290 according to the specific processing program 56 executed by the processor 28 on the RAM 30.

[0822] 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 specific processing unit 290.

[0823] In the smart glasses 214, input / output processing for reception is performed by the processor 46. The storage 50 stores an input / output program 60 for reception. The processor 46 reads out the input / output program 60 for reception from the storage 50 and executes the read input / output program 60 for reception on the RAM 48. The input / output processing for reception is realized by operating as a control unit 46A according to the input / output program 60 for reception that the processor 46 executes on the RAM 48.

[0824] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0825] "Embodiment 1"

[0826] As an embodiment of the present invention, there is a system for providing infertility treatment information. This system has means for referring to a database including past treatment records, statistical information, and information disclosure at research institutions. Specifically, the database collects and organizes information on various infertility treatment methods, information on the treatment results and treatment processes of patients to whom those treatment methods have been applied, research results on infertility treatment published at various research institutions, and the like.

[0827] "Embodiment 2"

[0828] The above system has means for responding to an inquiry from a user based on information obtained from the database. Specifically, when the user inquires about a specific infertility treatment method, the system obtains information on the corresponding treatment method from the database and responds to the user based on that. For example, when the user inquires, "What is the success rate of PGT-A?", the system obtains information on the success rate of PGT-A from the database and provides it to the user.

[0829] "Form Example 3"

[0830] Furthermore, the above system has means for responding to inquiries from users in a chat format. Specifically, when a user makes an inquiry in a chat format, the system returns a real-time response thereto. This response is generated based on information obtained from a database. For example, when a user inquires, "What are the advantages and disadvantages of two-stage transplantation?", the system obtains information regarding the advantages and disadvantages of two-stage transplantation from the database and returns a response to the user based thereon.

[0831] The processing flow of each form example will be described below.

[0832] "Form Example 1"

[0833] Step 1: The system refers to a database including past treatment records, statistical information, and information disclosure at research institutions.

[0834] Step 2: Based on the information obtained from the database, information regarding infertility treatment is provided. "Form Example 2"

[0835] Step 1: Receive an inquiry from the user.

[0836] Step 2: Obtain information corresponding to the inquiry from the database.

[0837] Step 3: Based on the obtained information, return a response to the user.

[0838] "Form Example 3"

[0839] Step 1: Receive a chat-format inquiry from the user.

[0840] Step 2: Obtain information corresponding to the inquiry from the database.

[0841] Step 3: Based on the acquired information, return a real-time response to the user.

[0842] (Example 1)

[0843] Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0844] Information related to infertility treatment is diverse, and it is difficult for patients and medical staff to quickly and accurately obtain the necessary information. In addition, there is a lack of a system for effectively utilizing past treatment records, statistical information, and information disclosures by research institutions. Furthermore, even when a user inputs specific search conditions, the means for appropriately providing relevant information are limited. As a result, it has become difficult for users to make decisions for selecting the optimal treatment method.

[0845] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following respective means.

[0846] In this invention, the server includes means for referring to a database including past treatment records, statistical information, and information disclosures by research institutions, means for providing information related to infertility treatment based on the information acquired from the database, means for responding to an inquiry from a user based on the information acquired from the database, means for sorting the collected data by category and storing it in the database, means for analyzing the search conditions input by the user and sending a request to the server, and means for displaying the data returned from the server to the user. As a result, the user can quickly and accurately obtain the necessary infertility treatment information and make a decision for selecting the optimal treatment method.

[0847] The "database" is an aggregate of information that stores and can refer to information including past treatment records, statistical information, and information disclosures by research institutions.

[0848] The "referencing means" is a method or technology for searching for information in a database and obtaining the necessary data.

[0849] The "providing means" is a method or technology for displaying the acquired information to the user and providing it in a usable form.

[0850] The "responding means" is a method or technology for returning an answer based on the information acquired from the database in response to an inquiry from the user.

[0851] The "sorting means" is a method or technology for classifying the collected data by category and efficiently storing it in a database.

[0852] The "analyzing means" is a method or technology for understanding the search conditions input by the user and generating an appropriate request based on them.

[0853] The "transmitting means" is a method or technology for transmitting the analyzed request to the server and obtaining the necessary information.

[0854] The "displaying means" is a method or technology for displaying the data returned from the server in a user-friendly format.

[0855] This invention is a system for providing infertility treatment information, in which the server, the terminal, and the user cooperate to operate. The specific operations of each entity will be described below.

[0856] Operations of the server

[0857] The server plays a central role in collecting, sorting, and providing information related to infertility treatment. The server uses the following hardware and software.

[0858] Hardware: High-performance processor, sufficient memory, storage device

[0859] Software: Database Management System (DBMS), API Interface, Data Analysis Tools

[0860] The server automatically collects information on infertility treatment from the Internet or partner research institutions. For example, it accesses the databases of research institutions through APIs and obtains data on "the success rate of treatment method A" and "the side effects of treatment method B". The collected data is sorted by category and stored in the database. Duplicate and inconsistent data is checked, and the data is cleansed as necessary.

[0861] In response to a request from the user, the server extracts appropriate information from the database and returns it to the terminal. The data is filtered based on the content of the request to provide the information most relevant to the user.

[0862] Terminal Operations

[0863] The terminal provides an interface for the user to search for and view infertility treatment information. The terminal uses the following hardware and software.

[0864] Hardware: Personal Computer, Smartphone, Tablet

[0865] Software: Web Browser, Mobile Application

[0866] The terminal provides an interface that allows the user to easily search for information. For example, it displays a web page or application with a search bar and filtering function. When the user enters search criteria, the terminal sends the request to the server. When sending the request, the user's input content is converted into an appropriate format so that the server can understand it.

[0867] The terminal receives the data sent from the server and displays it to the user. The displayed information is provided in a visual form such as graphs and charts so that the user can intuitively understand the information.

[0868] User actions

[0869] The user uses this system to obtain information about infertility treatment. The user operates the system according to the following procedure.

[0870] 1. Input of search conditions: The user inputs search conditions through the interface of the terminal. For example, conditions such as "treatment methods suitable for women over 40 years old" or "side effects of treatment method D" are input. Filtering options for setting search conditions in detail can also be used.

[0871] 2. Browsing of information: The user browses the information provided by the server on the terminal. For example, when the user searches for "success rate of treatment method E", the result is confirmed on the terminal. The function of scrolling the displayed information to check the details and saving the information as needed can also be used.

[0872] 3. Support for decision-making: The user considers options for infertility treatment based on the provided information. For example, the user makes a decision such as "confirming that the success rate of treatment method F is high and deciding to try that method". Tools for comparing multiple treatment methods and finding the optimal option can also be used.

[0873] Specific examples and prompt texts

[0874] For example, when the user searches for "infertility treatment methods suitable for women over 35 years old", the process is carried out according to the following procedure.

[0875] 1. The user enters "infertility treatment methods suitable for women over 35 years old" in the search bar of the terminal.

[0876] 2. The terminal sends the request to the server.

[0877] 3. The server extracts the corresponding information from the database and returns it to the terminal.

[0878] 4. The terminal displays the information to the user.

[0879] 5. The user considers an appropriate treatment method based on the displayed information.

[0880] By inputting the following prompt sentence to the generative AI model, specific infertility treatment information can be obtained.

[0881] "Please tell me about infertility treatment methods suitable for women over 35 years old. Provide detailed information based on past treatment records, statistical information, and information disclosures from research institutions."

[0882] By inputting this prompt sentence, the generative AI model provides the corresponding information and supports the user's decision-making.

[0883] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0884] Step 1:

[0885] Data collection

[0886] The server automatically collects information on infertility treatment from the Internet or partner research institutions. As input, it accesses the databases of research institutions through APIs and obtains data on "the success rate of treatment method A" and "the side effects of treatment method B". As output, the collected data is stored in the server's temporary storage. As a specific operation, the server regularly sets a data collection schedule and updates the database whenever new information is published.

[0887] Step 2:

[0888] Data arrangement

[0889] The server sorts the collected data by category and stores it in a database. As input, it receives the data stored in the temporary storage. As output, the sorted data is stored in the database. As a specific operation, the server checks for data duplication and inconsistencies and cleans the data as necessary. For example, if data for the same patient is collected multiple times, it integrates them into one.

[0890] Step 3:

[0891] Provision of User Interface

[0892] The terminal provides an interface that enables the user to easily search for information. As input, it receives the user's search criteria. As output, the search criteria are sent to the server. As a specific operation, the terminal displays a web page or application with a search bar and filtering functions. It analyzes the search criteria entered by the user in real time and provides a suggestion function.

[0893] Step 4:

[0894] Sending of Request

[0895] The terminal sends the search criteria entered by the user to the server. As input, it receives the user's search criteria. As output, a request converted into an appropriate format is sent to the server. As a specific operation, the terminal converts the user's input content into an appropriate format when sending the request so that the server can understand it.

[0896] Step 5:

[0897] Data Provision

[0898] The server extracts appropriate information from the database in response to a request from the user and returns it to the terminal. As input, it receives the request sent from the terminal. As output, the corresponding information is returned to the terminal. As a specific operation, the server filters the data based on the content of the request and provides the information most relevant to the user.

[0899] Step 6:

[0900] Display of Results

[0901] The terminal displays the data returned from the server to the user. As input, it receives the data returned from the server. As output, the information is displayed in a user-friendly format. As a specific operation, the terminal provides the displayed information in a visual format such as graphs or charts so that the user can intuitively understand the information.

[0902] Step 7:

[0903] Viewing of Information

[0904] The user views the information displayed on the terminal. As input, it receives the information displayed on the terminal. As output, the user checks the information and saves it if necessary. As a specific operation, the user scrolls through the displayed information to check the details and uses the function to save the information if necessary.

[0905] Step 8:

[0906] Support for Decision Making

[0907] The user considers the infertility treatment options based on the provided information. As input, it receives the information displayed on the terminal. As output, a decision is made for the user to select the optimal treatment method. As a specific operation, the user compares multiple treatment methods and uses tools to find the optimal option. For example, a comparison table for comparing the success rates and side effects of each treatment method is used.

[0908] (Application Example 1)

[0909] Next, Application Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0910] Couples and individuals considering infertility treatment need to collect and compare a lot of information in order to find the optimal treatment method and medical institution. However, this information is scattered and difficult to collect efficiently. In addition, it is difficult to obtain information based on the latest research results and treatment performance, and there is a lack of judgment materials when selecting an appropriate treatment method and medical institution. For this reason, there is a demand for a system that can be easily accessed by users and provides reliable information.

[0911] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0912] In this invention, the server includes means for referring to a database including past treatment performance, statistical information, and information disclosure at research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, means for proposing an optimal treatment method based on the symptoms input by the user and the treatment method desired by the user, and means for searching for an optimal medical institution based on the location information of the user and the treatment method desired by the user. As a result, the user can efficiently obtain highly reliable infertility treatment information and can select an optimal treatment method and medical institution.

[0913] "Past treatment performance" refers to data regarding the results and processes of infertility treatment performed in the past.

[0914] "Statistical information" refers to information obtained by aggregating and analyzing numerical data regarding treatment results and treatment processes.

[0915] "Disclosure of information by research institutions" refers to information such as research results and papers on infertility treatment publicly available by research institutions.

[0916] "Database" is a system for organizing and storing information including past treatment records, statistical information, and disclosure of information by research institutions.

[0917] "Information on infertility treatment" refers to information such as infertility treatment methods, treatment results, treatment processes, and the latest research results.

[0918] "Inquiries from users" refer to questions and information requests made by users to the system.

[0919] "Symptoms" refer to the physical and medical conditions related to infertility experienced by users.

[0920] "Desired treatment method" refers to the method of infertility treatment that a user wishes to receive.

[0921] "Optimal treatment method" refers to the method of infertility treatment that best suits the user's symptoms and wishes.

[0922] "Location information" refers to data related to the location where a user is currently located.

[0923] "Medical institutions" refer to facilities such as clinics and hospitals that provide infertility treatment.

[0924] "Chat format" is a format for real-time communication using text messages.

[0925] The system for implementing this invention includes a server, a user terminal, and a database. The server refers to a database including past treatment records, statistical information, and disclosure of information by research institutions, and provides information on infertility treatment to users. The user terminal is a device such as a smartphone or tablet, and provides an interface for users to access the system.

[0926] The server includes the following means:

[0927] 1. Database reference means: Refer to a database including past treatment records, statistical information, and information disclosures at research institutions.

[0928] 2. Information providing means: Provide information regarding infertility treatment based on the information obtained from the database.

[0929] 3. Inquiry response means: Respond to inquiries from users based on the information obtained from the database.

[0930] 4. Treatment method proposal means: Propose an optimal treatment method based on the symptoms and desired treatment method input by the user.

[0931] 5. Medical institution search means: Search for an optimal medical institution based on the user's location information and desired treatment method.

[0932] Hardware and software to be used:

[0933] Hardware: Server, smartphone, tablet

[0934] Software: Flask (Python web framework), requests (Python library for sending HTTP requests)

[0935] Data processing and data calculation:

[0936] The server receives input data (symptoms, desired treatment method, location information) from the user and searches for relevant information from the database. The search results are proposed to the user as an optimal treatment method and medical institution. Specifically, a web application is constructed using Flask, and communication with the database is performed using the requests library.

[0937] Specific example:

[0938] When the user opens the "Infertility Treatment Navigator" app and enters their symptoms (e.g., polycystic ovary syndrome) and desired treatment method (e.g., in vitro fertilization), the server searches the database for the optimal treatment method and medical institution and proposes them to the user.

[0939] Example of a prompt sentence:

[0940] The user has symptoms of polycystic ovary syndrome and hopes for in vitro fertilization. Please propose the optimal treatment method and medical institution.

[0941] In this way, the user can efficiently obtain highly reliable infertility treatment information and select the optimal treatment method and medical institution.

[0942] The flow of the specific process in Application Example 1 will be described with reference to FIG. 12.

[0943] Step 1:

[0944] The user launches the application on a smartphone or tablet and enters symptoms, desired treatment method, and location information.

[0945] Input: Symptoms, desired treatment method, location information

[0946] Output: User input data

[0947] Specific operation: The user enters symptoms (e.g., polycystic ovary syndrome), desired treatment method (e.g., in vitro fertilization), and location information into the input form of the application and presses the send button.

[0948] Step 2:

[0949] The user terminal sends the input data to the server.

[0950] Input: User input data

[0951] Output: Request to Server

[0952] Specific operation: The user terminal sends the input data to the server as an HTTP request.

[0953] Step 3:

[0954] The server analyzes the user input data received and searches for relevant treatment method information from the database.

[0955] Input: User input data

[0956] Output: Treatment method information

[0957] Specific operation: The server uses Flask to analyze the received data, sends a query to the database using the requests library, and obtains relevant treatment method information.

[0958] Step 4:

[0959] Based on the treatment method information obtained by the server, propose the most suitable treatment method for the user's symptoms and desired treatment method.

[0960] Input: Treatment method information, user input data

[0961] Output: Proposal for the most suitable treatment method

[0962] Specific operation: The server analyzes the treatment method information obtained, selects and proposes the treatment method that best suits the user's symptoms and wishes.

[0963] Step 5:

[0964] The server searches for the most suitable medical institution based on the user's location information and desired treatment method.

[0965] Input: Location information, desired treatment method

[0966] Output: Medical institution information

[0967] Specific operation: The server searches the database based on the location information and the desired treatment method, and obtains the information of the optimal medical institution.

[0968] Step 6:

[0969] The server sends the optimal treatment method proposal and medical institution information to the user terminal.

[0970] Input: Optimal treatment method proposal, medical institution information

[0971] Output: Response to the user terminal

[0972] Specific operation: The server sends the optimal treatment method proposal and medical institution information to the user terminal as an HTTP response.

[0973] Step 7:

[0974] The user terminal receives the response from the server and displays it to the user.

[0975] Input: Response from the server

[0976] Output: Display information to the user

[0977] Specific operation: The user terminal receives the response from the server and displays the optimal treatment method proposal and medical institution information on the interface of the application.

[0978] In this way, the user can efficiently obtain highly reliable infertility treatment information and select the optimal treatment method and medical institution.

[0979] (Example 2)

[0980] Next, Example 2 of the second morphological example will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0981] In the conventional infertility treatment information providing system, it has been difficult for users to quickly and accurately obtain the information they need. In addition, there has been a lack of means to provide detailed information on specific infertility treatment methods, and it has been impossible to appropriately respond to user inquiries. Furthermore, the user interface has been insufficient, and the environment in which users can easily obtain information has not been established.

[0982] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0983] In this invention, the server includes means for a user to input an inquiry from a terminal, means for the terminal to send the inquiry to the server, means for the server to analyze the inquiry, means for the server to access a database to obtain information, means for the server to send the obtained information to the terminal, and means for the terminal to display the information to the user. Thereby, it becomes possible for the user to quickly and accurately obtain the necessary infertility treatment information.

[0984] A "user" is an individual or group that attempts to obtain information using the system.

[0985] A "terminal" is an electronic device used by a user to input an inquiry and receive information.

[0986] A "server" is a computer system that has the role of receiving an inquiry from a user, analyzing it, accessing a database to obtain information, and sending it to the terminal.

[0987] An "inquiry" is a question or request input by a user to the system through the terminal.

[0988] A "database" is a data storage system for storing information including past treatment results, statistical information, and information disclosure at research institutions.

[0989] The "means for acquiring information" is a process by which a server accesses a database, searches for and acquires necessary information.

[0990] The "means for displaying information" is a function for a terminal to display the information received from the server in a user-friendly format.

[0991] The "specific infertility treatment method" refers to specific infertility treatment methods such as PGTA and two-stage transplantation.

[0992] The "chat format" is an interface format for a user to make inquiries in an interactive manner with the system and receive responses.

[0993] This invention is a system that enables a user to quickly and accurately acquire information related to infertility treatment using a terminal. The system operates when the user inputs an inquiry from the terminal and sends the inquiry to the server. The server analyzes the inquiry, accesses the database to acquire the necessary information, and sends the acquired information to the terminal. The terminal displays the received information to the user.

[0994] This system uses the following hardware and software:

[0995] Terminal: Electronic devices such as smartphones, tablets, and personal computers

[0996] Server: High-performance computer system

[0997] Database management system (DBMS): MySQL

[0998] Server software: Apache

[0999] Programming language: Python

[1000] As a specific example of the operation, the user inputs "What is the success rate of PGTA?" into the input field of the terminal. This inquiry is sent from the terminal to the server, and the server accesses the MySQL database to obtain information regarding the success rate of PGTA. Subsequently, the obtained information is sent to the terminal, and the terminal displays to the user "The success rate of PGTA is 60%."

[1001] Example of a prompt sentence:

[1002] User: What is the success rate of PGTA?

[1003] Server: Retrieving information from the database...

[1004] Server: The success rate of PGTA is approximately 60%.

[1005] With this system, the user can quickly and accurately obtain detailed information regarding a specific infertility treatment method. Additionally, since it has a function for inquiry and response in a chat format, the user can obtain information in an interactive manner. As a result, the convenience for the user is significantly improved.

[1006] The flow of the specific process in Example 2 will be described with reference to FIG. 13.

[1007] Step 1:

[1008] The user inputs an inquiry from the terminal.

[1009] As a specific operation, the user opens a browser on a smartphone or a personal computer and inputs "What is the success rate of PGTA?" into the search bar. The input inquiry is displayed in the input field of the terminal.

[1010] Input: The inquiry input by the user (e.g., "What is the success rate of PGTA?")

[1011] Output: The inquiry displayed in the input field of the terminal

[1012] Step 2:

[1013] The terminal sends the inquiry to the server.

[1014] The terminal sends the inquiry entered by the user to the server as an HTTP request. At this time, the terminal sends the inquiry content to the server in JSON format.

[1015] Input: Inquiry entered by the user (e.g., "What is the success rate of PGTA?")

[1016] Output: HTTP request sent to the server (e.g., {"query": "What is the success rate of PGTA?"})

[1017] Step 3:

[1018] The server analyzes the inquiry.

[1019] The server analyzes the received HTTP request and extracts the inquiry content. For example, it recognizes that the inquiry is "What is the success rate of PGTA?".

[1020] Input: HTTP request sent from the terminal (e.g., {"query": "What is the success rate of PGTA?"})

[1021] Output: Analyzed inquiry content (e.g., "What is the success rate of PGTA?")

[1022] Step 4:

[1023] The server accesses the database to obtain information.

[1024] The server sends a query to the database based on the inquiry content. For example, it executes a query like "SELECT success_rate FROM treatments WHERE name='PGTA'". The database returns a success rate of "60%".

[1025] Input: Parsed inquiry content (e.g., "What is the success rate of PGTA?")

[1026] Output: Information retrieved from the database (e.g., "60%")

[1027] Step 5:

[1028] The server sends the information it has obtained to the terminal.

[1029] The server converts the information retrieved from the database into JSON format and sends it to the terminal as an HTTP response. For example, it sends the information "The success rate of PGTA is 60%".

[1030] Input: Information retrieved from the database (e.g., "60%")

[1031] Output: HTTP response sent to the terminal (e.g., {"response": "The success rate of PGTA is 60%"})

[1032] Step 6:

[1033] The terminal displays the information to the user.

[1034] The terminal analyzes the information received from the server and displays it in a user-friendly format. For example, it displays "The success rate of PGTA is 60%" on the screen.

[1035] Input: HTTP response sent from the server (e.g., {"response": "The success rate of PGTA is 60%"})

[1036] Output: Information displayed to the user (e.g., "The success rate of PGTA is 60%")

[1037] (Application Example 2)

[1038] Next, Application Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1039] Since the conventional infertility treatment information providing system is specialized in providing information regarding infertility treatment, there has been a problem that users cannot obtain information regarding security. Further, a separate system for providing security information is required, which also causes a problem of reduced convenience for users.

[1040] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following respective means. In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions, means for providing information regarding infertility treatment based on the information obtained from the database, means for responding to an inquiry from a user based on the information obtained from the database, means for referring to a database for providing security information, and means for responding to the user based on the security information obtained from the database. Thereby, it becomes possible to provide both infertility treatment information and security information in one system.

[1041] "Infertility treatment information" refers to all information regarding infertility treatment, including past treatment results, statistical information, and information disclosure at research institutions.

[1042] "Database" refers to an aggregate of information in which specific information is systematically organized and stored so that it can be searched and acquired as needed.

[1043] "Inquiry from a user" refers to a question or request made by a person using the system to obtain specific information.

[1044] "Means for responding" refers to a method or device for providing appropriate information in response to an inquiry from a user.

[1045] "Security information" refers to the latest methods and countermeasure information related to security such as phishing fraud and unauthorized access.

[1046] "Chat format" refers to a method of real-time information exchange in a text-based dialogue format.

[1047] The system for implementing this invention consists of a server, user terminals, and a database. The server refers to a database including past treatment records, statistical information, and information disclosures at research institutions, and provides appropriate information in response to inquiries from users. It also refers to a database for providing security information and responds to users with the latest security information.

[1048] The server constructs a web application using the Flask framework and manages information using an SQLite database. The user terminal is a device such as a smartphone or a personal computer and accesses the server via the Internet. When a user inquires about specific information, the server retrieves the corresponding information from the database and provides it to the user.

[1049] As a specific processing flow, when a user makes an inquiry such as "What are the latest phishing fraud methods?" from a terminal, the server retrieves information related to the latest phishing fraud from the SQLite database and returns that information to the user. Thereby, the user can quickly obtain the necessary information.

[1050] The hardware used is a computer as the server and a smartphone or personal computer as the user terminal. The software used is Flask (Python framework) and SQLite (database).

[1051] As a specific example, when a user inquires "What are the latest phishing fraud methods?", the server retrieves information related to the latest phishing fraud from the database and responds as follows.

[1052] "The latest phishing scam involves using fake bank emails to steal personal information."

[1053] An example of a prompt for a generative AI model is as follows:

[1054] When a user asks, "What are the latest phishing scams?", retrieve information about the latest phishing scams from your database and respond with the following:

[1055] "The latest phishing scam involves using fake bank emails to steal personal information."

[1056] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1057] Step 1:

[1058] The user inputs a query from a device. Using a smartphone or computer, the user inputs a question that requests specific information. For example, the user might input, "What are the latest phishing scam methods?" The input data is a query in text format.

[1059] Step 2:

[1060] The terminal sends a query to the server. The query entered by the user is sent to the server via the Internet. The input data is the user's query text, and the output data is the query sent to the server.

[1061] Step 3:

[1062] The server receives an inquiry and accesses the database. The server uses the Flask framework to receive the inquiry and accesses the SQLite database. The input data is the user's inquiry text, and the output data is the execution result of the database query.

[1063] Step 4:

[1064] The server retrieves the relevant information from the database. The server executes an SQL query to retrieve the information relevant to the user's inquiry from the database. For example, it retrieves information about "the latest phishing fraud methods". The input data is the SQL query, and the output data is the retrieved information.

[1065] Step 5:

[1066] The server generates a response based on the retrieved information. The server generates a response to the user based on the retrieved information. For example, it generates a response such as "The latest phishing fraud method is to steal personal information using fake bank emails." The input data is the retrieved information, and the output data is the generated response text.

[1067] Step 6:

[1068] The server sends the generated response to the terminal. The server sends the generated response to the user's terminal. The input data is the generated response text, and the output data is the response sent to the terminal.

[1069] Step 7:

[1070] The terminal receives the response from the server and displays it to the user. The user's terminal displays the response received from the server. For example, it displays "The latest phishing fraud method is to steal personal information using fake bank emails." The input data is the response text from the server, and the output data is the response displayed to the user.

[1071] (Example 3)

[1072] Next, Example 3 of Form Example 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1073] In the conventional infertility treatment information providing system, there has been a problem that it is difficult to respond quickly and appropriately to inquiries from users. In addition, there is a lack of means for providing detailed information on specific medical techniques, and it has been difficult for users to obtain the information they need in a timely manner. Furthermore, since there is no inquiry response function in the chat format, the user experience has been degraded.

[1074] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1075] In this invention, the server includes means for receiving an inquiry from a user, means for analyzing the inquiry, means for obtaining information from a database based on the analysis result, means for transmitting a prompt sentence to a generated AI model based on the obtained information, and means for returning a response from the generated AI model to the user. Thereby, it becomes possible to respond quickly and appropriately to an inquiry from a user. In addition, by including means for providing detailed information on a specific medical technique, it is possible to obtain the information required by the user in a timely manner. Furthermore, by including an inquiry response function in the chat format, the user experience can be improved.

[1076] The "means for receiving an inquiry from a user" is a function for the server to receive an inquiry transmitted by a user through a web browser or a mobile application.

[1077] The "means for analyzing the inquiry" is a function for analyzing the received inquiry content and extracting keywords and intentions.

[1078] "The means for obtaining information from a database" is a function for obtaining necessary information from a database based on the analysis results.

[1079] "The means for sending a prompt sentence to a generative AI model" is a function for sending a prompt sentence generated based on the obtained information to a generative AI model.

[1080] "The means for returning the response from the generative AI model to the user" is a function for returning the response received from the generative AI model to the user.

[1081] "The means for providing information on a specific medical technique" is a function for providing detailed information on a specific medical technique to the user.

[1082] "The means for responding to user inquiries in a chat format" is a function for responding in real time to user inquiries in a chat format.

[1083] Mode for carrying out the invention

[1084] This invention is a system for quickly and appropriately responding to user inquiries. The specific embodiments of this system will be described below.

[1085] 1. Generation of the system program

[1086] The system program is developed using Python and operates as a web server using the Flask framework. MySQL is used for the database, and a general generative AI model (e.g., GPT-3) is used for the generative AI model.

[1087] 2. Program processing

[1088] The server receives inquiries from users and analyzes them. For the analysis, text analysis libraries (e.g., NLTK or spaCy) are used. Based on the analysis results, the server retrieves the necessary information from the database. Based on the retrieved information, the server sends a prompt text to the generative AI model and returns the response from the generative AI model to the user.

[1089] 3. Specific Example

[1090] Consider the case where a user sends an inquiry "What are the advantages and disadvantages of two-stage transplantation?" using a web browser or a mobile app. In this case, the server processes as follows.

[1091] 1. The user sends an inquiry in chat form: "What are the advantages and disadvantages of two-stage transplantation?"

[1092] 2. The server receives and analyzes this inquiry.

[1093] 3. The server executes an SQL query to retrieve information about "the advantages and disadvantages of two-stage transplantation" from the MySQL database.

[1094] 4. Based on the retrieved information, the following prompt text is input into the generative AI model.

[1095] Example of prompt text: "Please tell me about the advantages and disadvantages of two-stage transplantation. The advantages are 〇〇 and the disadvantages are △△."

[1096] 5. The generative AI model (e.g., GPT-3) generates a response based on this prompt text.

[1097] 6. The server returns the generated response to the user in real time.

[1098] In this way, the system can respond quickly and appropriately to inquiries from users. The flow of the specific process in Example 3 will be described with reference to FIG. 15.

[1099] Step 1:

[1100] The user sends an inquiry.

[1101] The user sends an inquiry in chat format using a web browser or a mobile app. For example, the user enters "What are the advantages and disadvantages of two-stage transplantation?" and clicks the send button. The input is the content of the user's inquiry, and the output is an HTTP request to the server.

[1102] Step 2:

[1103] The server receives the inquiry.

[1104] The server receives the HTTP request from the user using the Flask framework. The received request contains the content of the user's inquiry. The input is the HTTP request from the user, and the output is the text data of the inquiry content.

[1105] Step 3:

[1106] The server analyzes the inquiry.

[1107] The server analyzes the received inquiry content using a text analysis library (e.g., NLTK or spaCy). Through the analysis, keywords and intentions are extracted. The input is the text data of the inquiry content, and the output is the analysis result (keywords and intentions).

[1108] Step 4:

[1109] The server retrieves information from the database.

[1110] The server obtains the necessary information from the MySQL database based on the analysis results. For example, to obtain information about "the advantages and disadvantages of two-stage transplantation", it executes an SQL query. The input is the analysis result, and the output is the information obtained from the database.

[1111] Step 5:

[1112] The server sends a prompt sentence to the generative AI model.

[1113] The server generates a prompt sentence based on the obtained information and sends it to the generative AI model. For example, it generates a prompt sentence such as "Please tell me about the advantages and disadvantages of two-stage transplantation. The advantages are 〇〇, and the disadvantages are △△." The input is the information obtained from the database, and the output is the prompt sentence for the generative AI model.

[1114] Step 6:

[1115] The generative AI model generates a response.

[1116] The generative AI model generates a response based on the received prompt sentence. For example, it generates a response such as "The advantages of two-stage transplantation are a high success rate and less burden on the patient. On the other hand, the disadvantages are that the surgery is complex and time-consuming." The input is the prompt sentence, and the output is the generated response.

[1117] Step 7:

[1118] The server returns the response to the user.

[1119] The server returns the response received from the generative AI model to the user. Specifically, it returns the response as an HTTP response, which is displayed on the user's screen. The input is the generated response, and the output is the HTTP response to the user.

[1120] (Application Example 3)

[1121] Next, Application Example 3 of Embodiment 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1122] In the conventional infertility treatment information providing system, there has been a problem that it is difficult to give a prompt and accurate response to an inquiry from a user. Further, since detailed information on a specific infertility treatment method is insufficient, there has also been a problem that it takes time for the user to obtain necessary information. Furthermore, there has been a lack of technology for generating an appropriate response to the user's question.

[1123] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1124] In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosures at research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to an inquiry from a user based on the information obtained from the database, and means for generating an appropriate response to the user's question using a generative AI model. As a result, the user can obtain a prompt and accurate response, and detailed information on a specific infertility treatment method is also provided, so that necessary information can be obtained quickly.

[1125] "Past treatment results" are data regarding the results and progress of infertility treatment performed previously.

[1126] "Statistical information" is data indicating the result of aggregating and analyzing a plurality of treatment data.

[1127] "Information disclosures at research institutions" are research results and reports on infertility treatment published by academic institutions and medical institutions.

[1128] A "database" is a system that systematically manages and stores data such as past treatment records, statistical information, and information disclosures from research institutions.

[1129] "Information on infertility treatment" refers to detailed data on infertility treatment methods, effects, side effects, success rates, etc.

[1130] "Inquiries from users" refer to the act of individuals using the system to ask questions or seek information regarding infertility treatment.

[1131] A "generative AI model" is an algorithm or program that uses artificial intelligence to generate appropriate responses to users' questions.

[1132] An "appropriate response" is an answer that provides accurate and useful information in response to a user's question.

[1133] The system for implementing this invention is configured as follows. The server includes means for referring to a database containing past treatment records, statistical information, and information disclosures from research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, and means for generating appropriate responses to users' questions using a generative AI model.

[1134] Hardware and Software to be Used

[1135] Hardware: Server, Smartphone

[1136] Software: Python, SQLite, OpenAI API

[1137] Data Processing and Data Calculation

[1138] The server first connects to a database containing past treatment records, statistical information, and information disclosures at research institutions using SQLite. When a user accesses the system using a smartphone and makes an inquiry in a chat format, the server analyzes the content of the inquiry.

[1139] Retrieving Information from the Database

[1140] If the user's inquiry is about a specific infertility treatment method, the server retrieves the corresponding information from the database and provides it to the user. For example, if the user asks, "What are the advantages and disadvantages of two-stage transplantation?", the server retrieves information about two-stage transplantation from the database and generates a response based on it.

[1141] Using the Generated AI Model

[1142] If the user's inquiry is not directly related to the database, the server uses the generated AI model to generate an appropriate response. Specifically, it uses the OpenAI API to generate a prompt sentence for the user's question, and based on that prompt sentence, the AI generates a response.

[1143] Specific Examples

[1144] For example, if the user asks, "Tell me the specifications of the iPhone 13", the server retrieves the specification information of the iPhone 13 from the database and returns that information to the user. Also, if the user asks, "What are the advantages and disadvantages of two-stage transplantation?", the server sends the following prompt sentence to the generated AI model:

[1145] User's question: What are the advantages and disadvantages of two-stage transplantation?

[1146] Answer:

[1147] Based on this prompt text, the generative AI model generates an appropriate response and provides it to the user. This enables the user to obtain rapid and accurate information.

[1148] The flow of the specific process in Application Example 3 will be described with reference to FIG. 16.

[1149] Step 1:

[1150] The user accesses the system using a smartphone and makes an inquiry in a chat format.

[1151] Input: User's question (e.g., "What are the advantages and disadvantages of two-stage transplantation?")

[1152] Output: The content of the user's question is sent to the server.

[1153] Specific operation: The user opens the chat application on the smartphone, enters the question, and presses the send button.

[1154] Step 2:

[1155] The server receives the user's question and analyzes its content.

[1156] Input: Content of the user's question

[1157] Output: Analysis result of the question content (e.g., "Question regarding two-stage transplantation")

[1158] Specific operation: The server analyzes the received text data using a natural language processing algorithm to identify the intent of the question.

[1159] Step 3:

[1160] The server connects to the database and searches for the relevant information.

[1161] Input: Analysis result of the question content

[1162] Output: Information retrieved from the database (e.g., "Information on the advantages and disadvantages of two-stage transplantation")

[1163] Specific operation: The server sends a query to the SQLite database and retrieves the corresponding information.

[1164] Step 4:

[1165] The server generates a response based on the information retrieved from the database.

[1166] Input: Information retrieved from the database

[1167] Output: Response content for the user (e.g., "The advantages of two-stage transplantation are..., and the disadvantages are...")

[1168] Specific operation: The server formats the information it has retrieved into text form and generates a response to send to the user.

[1169] Step 5:

[1170] The server uses the generated AI model to generate an appropriate response to the user's question.

[1171] Input: Content of the user's question

[1172] Output: Response content from the generated AI model (e.g., "The advantages and disadvantages of two-stage transplantation are as follows...")

[1173] Specific operation: The server sends the prompt text to the OpenAI API and receives the generated response.

[1174] Step 6:

[1175] The server sends the generated response to the user.

[1176] Input: Generated response content

[1177] Output: The response message displayed on the user's smartphone

[1178] Specific operation: The response generated by the server is sent to the user through the chat application and displayed on the user's smartphone.

[1179] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[1180] "Form Example 1"

[1181] As an embodiment of the present invention, there is a infertility treatment information providing system combined with an emotion engine for recognizing the user's emotion. When the user makes an inquiry to the system, this system has the emotion engine recognize the user's emotion. The emotion engine analyzes the emotion from the user's text input or voice input, and the system uses the result. For example, when the user shows an anxious emotion, the system recognizes the emotion and provides information to soothe the anxiety.

[1182] "Form Example 2"

[1183] Also, as another embodiment of the present invention, there is a system in which the emotion engine provides information regarding infertility treatment based on the user's emotion. In this system, the emotion engine analyzes the user's emotion and provides information suitable for that emotion. For example, when the user shows a hopeful emotion, the system provides information such as success stories and new treatment methods.

[1184] "Form Example 3"

[1185] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine responds to inquiries from a user based on the user's emotions. In this system, the emotion engine analyzes the user's emotions and generates a response suitable for those emotions. For example, when the user is discouraged, the system generates a response that includes words of encouragement.

[1186] The processing flow of each exemplary embodiment will be described below.

[1187] "Exemplary Embodiment 1"

[1188] Step 1: The user makes an inquiry to the system.

[1189] Step 2: The emotion engine analyzes the emotion from the user's text input or voice input.

[1190] Step 3: The system uses the analysis result of the emotion engine to provide information suitable for the user's emotion.

[1191] "Exemplary Embodiment 2"

[1192] Step 1: The emotion engine analyzes the user's emotion.

[1193] Step 2: The system uses the analysis result of the emotion engine to provide information suitable for the user's emotion.

[1194] "Exemplary Embodiment 3"

[1195] Step 1: The emotion engine analyzes the user's emotion.

[1196] Step 2: The system uses the analysis result of the emotion engine to generate a response suitable for the user's emotion.

[1197] (Example 1)

[1198] Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1199] In the conventional infertility treatment information providing system, since information is provided without considering the user's feelings, the anxiety and stress felt by the user cannot be sufficiently reduced. In addition, since appropriate information is not provided according to the user's feelings, there is a problem that the user's satisfaction decreases.

[1200] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1201] In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosures at research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, means for recognizing the user's feelings, and means for providing appropriate information based on the feelings recognized by the means for recognizing feelings. Thereby, it becomes possible to provide appropriate information according to the user's feelings, reduce the user's anxiety and stress, and improve the satisfaction.

[1202] "Past treatment results" refer to data regarding the results and processes of infertility treatment performed in the past.

[1203] "Statistical information" refers to the results of aggregating and analyzing data related to infertility treatment.

[1204] "Information disclosures at research institutions" refer to research results and reports on infertility treatment publicly disclosed by research institutions.

[1205] "Database" refers to a system for organizing and storing information including past treatment results, statistical information, and information disclosures at research institutions.

[1206] The "emotion analysis means" is a technology for analyzing emotions from a user's text input or voice input.

[1207] The "means for providing appropriate information" is a technology for selecting and providing information beneficial to the user based on the result of analyzing the user's emotions.

[1208] The "means for responding to inquiries" is a technology for providing an answer based on information obtained from a database in response to a question or request from the user.

[1209] The present invention is a system for providing infertility treatment information, which refers to a database including past treatment records, statistical information, and information disclosures at research institutions, and provides appropriate information to the user. Furthermore, it has a function of recognizing the user's emotions and providing information based on those emotions.

[1210] Hardware and software to be used

[1211] 1. Server

[1212] The server uses a database management system (e.g., MySQL, PostgreSQL) to manage data including past treatment records, statistical information, and information disclosures at research institutions.

[1213] The server uses web server software (e.g., Apache, Nginx) to receive and process HTTP requests from the user.

[1214] 2. Emotion analysis means

[1215] As the emotion analysis means, a natural language processing API (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) is used. Thereby, emotions are analyzed from the user's text input or voice input.

[1216] 3. Terminal

[1217] Users access the system using a web browser (e.g., Google Chrome, Safari) or a mobile app.

[1218] Data processing and data calculation

[1219] 1. Database reference

[1220] The server uses a database management system to reference data including past treatment records, statistical information, and information disclosures at research institutions. Thereby, basic data for providing appropriate information in response to user inquiries is obtained.

[1221] 2. Sentiment analysis

[1222] The server sends the user's text input or voice input to sentiment analysis means to analyze the user's sentiment. The analysis result is returned to the server in JSON format.

[1223] 3. Information provision

[1224] The server searches for appropriate information from the database based on the sentiment analysis result and provides it to the user. For example, when the user shows anxiety, information on success stories and relaxation methods for alleviating anxiety is provided.

[1225] Specific example

[1226] For example, when the user enters the text "I'm anxious because my recent treatment isn't going well", the process proceeds as follows.

[1227] 1. The user accesses the system using Google Chrome.

[1228] 2. The user enters "I'm anxious because my recent treatment isn't going well" in the text box.

[1229] 3. The server receives this input through Apache.

[1230] 4. The server calls the Google Cloud Natural Language API and sends the input data.

[1231] 5. The sentiment analysis means analyzes the sentiment of "uneasy".

[1232] 6. The server receives the analysis result in JSON format.

[1233] 7. The server refers to the MySQL database.

[1234] 8. The server searches for information on success stories and relaxation methods to relieve uneasiness.

[1235] 9. The server displays the search results on a web page and provides them to the user.

[1236] Examples of prompt sentences

[1237] Examples of prompt sentences to be input into the generative AI model include the following:

[1238] When the user inputs "I'm uneasy because the recent treatment isn't going well", please explain how the sentiment engine will react and what information the server will provide.

[1239] By using this prompt sentence, the generative AI model can recognize the user's sentiment and understand the operation of the system that provides appropriate information.

[1240] The flow of specific processing in Example 1 will be described with reference to FIG. 17.

[1241] Step 1:

[1242] The user accesses the system.

[1243] The user accesses the system using a web browser or a mobile app. For example, browsers such as Google Chrome or Safari are used. The input is the user's access request, and the output is the display of the system's homepage.

[1244] Step 2:

[1245] The user enters an inquiry.

[1246] The user enters an inquiry using a text box or a voice input function. For example, the user enters "I'm worried because the recent treatment isn't going well." The input is the user's text or voice data, and the output is the transmission of that data to the server.

[1247] Step 3:

[1248] The server receives the user's input.

[1249] The server receives an HTTP request and obtains the user's input data. For example, web servers such as Apache or Nginx are used. The input is the user's inquiry data, and the output is that the data is ready to be processed within the server.

[1250] Step 4:

[1251] The server calls the emotion engine.

[1252] The server calls the API of the emotion engine and sends the user's input data. For example, Google Cloud Natural Language API or IBM Watson Tone Analyzer is used. The input is the user's text or voice data, and the output is the return of the emotion analysis result.

[1253] Step 5:

[1254] The emotion engine analyzes the user's emotions.

[1255] The emotion engine analyzes the user's text input and voice input to identify emotions. For example, it recognizes the emotion of "anxiety". The input is the user's text or voice data, and the output is the analyzed emotion data.

[1256] Step 6:

[1257] The server receives the analysis result.

[1258] The server receives the analysis result from the emotion engine and proceeds to the next process. For example, it receives the result in JSON format. The input is the emotion analysis result, and the output is that the result becomes available within the server.

[1259] Step 7:

[1260] The server references the database.

[1261] The server uses a database management system such as MySQL or PostgreSQL to reference the database. The input is the emotion analysis result and the user's inquiry content, and the output is that relevant information is retrieved from the database.

[1262] Step 8:

[1263] The server searches for appropriate information.

[1264] The server searches for appropriate information from the database based on the user's emotion. For example, it searches for success stories or relaxation methods to relieve anxiety. The input is the information retrieved from the database, and the output is the appropriate information to provide to the user.

[1265] Step 9:

[1266] The server provides the search result to the user.

[1267] The server returns the search results to the user. For example, it displays the results on a web page or reads the results aloud. The input is appropriate information, and the output is the information provided to the user.

[1268] (Application Example 1)

[1269] Next, Application Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1270] In an information providing system related to infertility treatment, since information providing considering the user's feelings is insufficient, the user may feel anxiety and stress. Also, in the conventional system, there is a problem that information is not provided in the virtual space, and it is difficult for the user to obtain information more intuitively.

[1271] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[1272] In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions, means for providing information related to infertility treatment based on the information obtained from the database, means for responding to an inquiry from the user based on the information obtained from the database, means for recognizing the user's feelings using an emotion engine that analyzes the user's feelings, means for providing appropriate information according to the recognized feelings, and means for providing an interface for browsing information in the virtual space. Thereby, it becomes possible to provide appropriate information according to the user's feelings, and information can be obtained intuitively in the virtual space.

[1273] The "database" is a system that organizes and stores information including past treatment results, statistical information, and information disclosure at research institutions, and can be referred to as needed.

[1274] The "infertility treatment information providing means" is a function that provides users with information on infertility treatment based on the information obtained from the database.

[1275] The "inquiry response means" is a function that responds to inquiries from users based on the information obtained from the database.

[1276] The "emotion engine" is a technology that analyzes emotions from the user's text input or voice input and makes the results available for the system to use.

[1277] The "emotion recognition means" is a function that recognizes the user's emotions using the emotion engine.

[1278] The "emotion response means" is a function that provides appropriate information according to the recognized emotions.

[1279] The "virtual interface" is an interface for users to view information in the virtual space.

[1280] The system for implementing this invention has the following configuration.

[1281] Configuration of the system

[1282] 1. Database reference means

[1283] The server refers to a database including past treatment records, statistical information, and information disclosure by research institutions. This database organizes and stores various information on infertility treatment and can be accessed quickly as needed.

[1284] 2. Infertility treatment information providing means

[1285] The server provides users with information on infertility treatment based on the information obtained from the database. This information provision is carried out based on the specific treatment methods and statistical data required by the users.

[1286] 3. Inquiry Response Means

[1287] The server responds to inquiries from users based on information retrieved from the database. As a result, users can obtain the necessary information in real time.

[1288] 4. Emotion Recognition Means

[1289] The server uses an emotion engine to recognize the emotions of users. The emotion engine analyzes emotions from the user's text input or voice input and makes the results available for the system to use.

[1290] 5. Emotion Response Means

[1291] The server provides appropriate information according to the recognized emotions. For example, when a user is feeling anxious, information that can reassure the user is provided.

[1292] 6. Virtual Interface

[1293] The terminal provides an interface for users to view information within the virtual space. As a result, users can obtain information intuitively.

[1294] Hardware and Software Used

[1295] Hardware: Smartphones, Head-Mounted Displays

[1296] Software: Python, Emotion Recognition Library (EmotionEngine), Database Management System (TreatmentDatabase)

[1297] Data Processing and Calculation

[1298] 1. Acquisition of User Input

[1299] The terminal acquires text or voice input from the user.

[1300] 2. Sentiment Analysis

[1301] The server analyzes the sentiment from the user's input using a sentiment engine.

[1302] 3. Information Provision

[1303] The server acquires appropriate information from the database based on the result of the sentiment analysis and provides it to the user.

[1304] Specific Example

[1305] When the user inputs "I'm worried about my recent treatment results", the sentiment engine analyzes it as "uneasy", and the server provides reassuring information.

[1306] When the user inputs "I want to know about the latest treatment methods", the server provides general treatment information.

[1307] Example of Prompt Sentence

[1308] When the user inputs "I'm worried about my recent treatment results", the sentiment engine analyzes it as "uneasy", and please provide reassuring information.

[1309] In this way, it becomes possible to provide appropriate information according to the user's sentiment, and a system is realized in which information can be obtained intuitively within the virtual space.

[1310] The flow of the specific process in Application Example 1 will be described with reference to FIG. 18.

[1311] Step 1:

[1312] The user inputs an inquiry to the terminal in text or voice.

[1313] Input: User's text or voice input (e.g., "I'm worried about my recent treatment results")

[1314] Output: User's input data

[1315] Specific operation: The terminal receives the user's input and saves it as text data or voice data.

[1316] Step 2:

[1317] The terminal sends the user's input data to the server.

[1318] Input: User's input data

[1319] Output: User's input data sent to the server

[1320] Specific operation: The terminal sends the user's input data to the server via the network.

[1321] Step 3:

[1322] The server analyzes the emotion from the user's input data using an emotion engine.

[1323] Input: User's input data

[1324] Output: User's emotion data (e.g., "Anxiety")

[1325] Specific operation: The server activates the emotion engine and analyzes the user's input data to identify the emotion. The emotion engine performs text analysis and voice analysis and classifies the user's emotion into categories such as "Anxiety", "Relief", "Interest", etc.

[1326] Step 4:

[1327] The server retrieves appropriate information from the database based on the emotion data.

[1328] Input: User's emotional data (e.g., "uneasy")

[1329] Output: Appropriate information data (e.g., "reassuring information")

[1330] Specific operation: The server searches the database based on the emotional data and obtains information corresponding to the user's emotion. For example, when analyzed as "uneasy", information for reassurance is extracted from the database.

[1331] Step 5:

[1332] The server transmits the information obtained to the terminal.

[1333] Input: Appropriate information data

[1334] Output: Information data transmitted to the terminal

[1335] Specific operation: The server transmits the obtained information data to the terminal via the network.

[1336] Step 6:

[1337] The terminal displays the information received to the user.

[1338] Input: Received information data

[1339] Output: Information displayed to the user

[1340] Specific operation: The terminal displays the received information data to the user. The display methods include text display, voice reading, or display using a virtual interface, etc.

[1341] In this way, an appropriate information provision according to the user's emotion becomes possible, and a system is realized that enables the user to intuitively obtain information within the virtual space.

[1342] (Example 2)

[1343] Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1344] In a conventional infertility treatment information providing system, it may be difficult to respond appropriately and promptly to inquiries from users. In addition, since information is not provided according to the user's emotions, the user's satisfaction may decrease. Furthermore, since there is a lack of means for providing detailed information on specific infertility treatment methods, users may not be able to obtain sufficient information they need.

[1345] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1346] In this invention, the server includes means for receiving an inquiry from a user, means for analyzing the content of the received inquiry, means for obtaining information from a database, means for providing the obtained information to the user, and means for analyzing the user's emotions using an emotion engine and providing information suitable for the emotions. As a result, it becomes possible to respond quickly and appropriately to inquiries from users, and since information is provided according to the user's emotions, the user's satisfaction is improved. In addition, detailed information on specific infertility treatment methods can be provided, and it becomes possible for users to obtain sufficient information they need.

[1347] The "means for receiving an inquiry from a user" is an interface for the system to receive questions and requests input by the user.

[1348] The "means for analyzing the content of the received inquiry" is a function for understanding the received user's inquiry using technologies such as natural language processing and extracting appropriate information.

[1349] The "means for obtaining information from a database" is a function for searching and obtaining relevant information from a database based on the analyzed inquiry content.

[1350] The "means for providing the obtained information to the user" is an interface for clearly displaying the information obtained from the database to the user.

[1351] The "means for analyzing the user's emotion using an emotion engine and providing information suitable for that emotion" is a function for selecting and providing information according to the user's emotional state using a technology for analyzing the user's emotion.

[1352] The "means for providing information on specific infertility treatment methods" is a function for providing users with detailed information on specific infertility treatment methods such as PGTA and two-stage transplantation.

[1353] The "means for responding to inquiries from the user in a chat format" is an interface for interacting with the user in a chat format and responding to inquiries in real time.

[1354] Mode for Carrying Out the Invention

[1355] This invention is a system that responds to inquiries from users based on information obtained from a database. Specifically, when a user inquires about a specific infertility treatment method, the system obtains information on the corresponding treatment method from the database and responds to the user based on that. It also includes a function for analyzing the user's emotion using an emotion engine and providing information suitable for that emotion.

[1356] Hardware and Software to be Used

[1357] The server uses the following hardware and software.

[1358] Hardware: High-performance server machine (e.g., Intel Xeon processor, 32GB RAM, 1TB SSD)

[1359] Software:

[1360] Database management system (e.g., MySQL)

[1361] Natural language processing engine (e.g., spaCy, NLTK)

[1362] Sentiment analysis engine (e.g., IBM Watson's sentiment analysis API)

[1363] The terminal is a device for the user to input inquiries and receive responses from the system. As the terminal, a personal computer, a smartphone, a tablet, etc. are used.

[1364] Processing description of the program

[1365] When the server receives an inquiry from the user, it analyzes the content of the inquiry using the natural language processing engine. Based on the analysis result, the server retrieves the corresponding information from the MySQL database. The retrieved information is sent to the terminal and displayed to the user.

[1366] Furthermore, the server analyzes the user's sentiment using the sentiment analysis engine. Based on the analysis result, it selects information suitable for the user's sentiment and sends it to the terminal. The terminal displays the selected information to the user.

[1367] Specific example

[1368] When the user inquires "What is the success rate of PGTA?", the processing is performed according to the following procedure.

[1369] 1. The terminal receives the user's inquiry.

[1370] 2. The server extracts the keywords "PGTA" and "success rate" using a natural language processing engine.

[1371] 3. The server connects to the MySQL database and executes the following SQL query.

[1372] sql

[1373] SELECT success_rate FROM fertility_treatments WHERE treatment_name = 'PGTA';

[1374] 4. The server sends the obtained success rate data to the terminal.

[1375] 5. The terminal displays to the user "The success rate of PGTA is 70%".

[1376] Also, when the user shows a desired emotion, the server selects information on successful cases and new treatment methods based on the analysis result using an emotion analysis engine and sends it to the terminal. The terminal displays "In recent research, a new treatment method has been developed".

[1377] Examples of prompt sentences

[1378] Examples of prompt sentences for the generative AI model are shown below.

[1379] When the user asks "What is the success rate of PGTA?", generate a program that retrieves information on the success rate of PGTA from the database and provides it to the user.

[1380]

[1381] When the user shows a desired emotion, generate a program that provides information such as successful cases and new treatment methods using an emotion engine.

[1382] The above is the embodiment for carrying out this invention.

[1383] The flow of the specific process in Example 2 will be described with reference to FIG. 19.

[1384] Flow of program processing

[1385] Step 1: Receive user inquiries

[1386] The terminal receives an inquiry from the user. For example, the user enters "What is the success rate of PGTA?". The input inquiry is sent from the terminal to the server.

[1387] Input: User inquiry (e.g., "What is the success rate of PGTA?")

[1388] Output: Inquiry data sent to the server

[1389] Step 2: Analyze the content of the inquiry

[1390] The server analyzes the received inquiry content using a natural language processing engine. Specifically, NLP tools such as spaCy or NLTK are used to understand the intention of the inquiry and extract important keywords.

[1391] Input: Inquiry data sent from the terminal

[1392] Data processing: Extract keywords using a natural language processing engine (e.g., "PGTA", "success rate")

[1393] Output: Extracted keywords

[1394] Step 3: Retrieve information from the database

[1395] The server retrieves the corresponding information from the MySQL database based on the analysis results. For example, to retrieve information about the "success rate of PGTA", an SQL query is executed.

[1396] Input: Extracted keywords (e.g., "PGTA", "success rate")

[1397] Data calculation: Execute an SQL query to retrieve information from the database (e.g., SELECT success_rate FROM fertility_treatments WHERE treatment_name = 'PGTA';)

[1398] Output: Retrieved information (e.g., "The success rate of PGTA is 70%")

[1399] Step 4: Provide information to the user

[1400] The server sends the retrieved information to the terminal. The terminal displays the received information to the user. For example, it displays "The success rate of PGTA is 70%".

[1401] Input: Retrieved information (e.g., "The success rate of PGTA is 70%")

[1402] Output: Information displayed to the user

[1403] Step 5: Provide information using the sentiment engine (if necessary)

[1404] The server analyzes the user's sentiment using the sentiment engine. For example, it uses the sentiment analysis API of IBM Watson. If the user shows a positive sentiment, the server selects information about successful cases and new treatment methods and sends it to the terminal. The terminal displays the selected information to the user.

[1405] Input: User's sentiment data

[1406] Data processing: Analyze emotions using an emotion analysis engine and select appropriate information

[1407] Output: Information suitable for the emotions to be displayed to the user (e.g., "In recent research, a new treatment method has been developed.")

[1408] The above is the processing flow of the program of this system.

[1409] (Application Example 2)

[1410] Next, Application Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1411] In an information providing system for infertility treatment, it is required to provide appropriate information according to the user's emotions. However, in the conventional system, since the same information is provided without considering the user's emotions, there is a problem that it is difficult to reduce the user's psychological burden

[1412] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1413] In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions, means for providing information on infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, means for analyzing the user's emotions, and means for providing appropriate information based on the emotion analysis means. Thereby, it becomes possible to provide appropriate information according to the user's emotions and reduce the user's psychological burden.

[1414] The "system for providing infertility treatment information" is a system that refers to a database including past treatment records, statistical information, and information disclosures from research institutions, and provides appropriate information on infertility treatment in response to inquiries from users.

[1415] The "means for referring to a database" is a means for obtaining necessary information from a database including past treatment records, statistical information, and information disclosures from research institutions.

[1416] The "means for providing information on infertility treatment" is a means for providing appropriate information on infertility treatment to users based on the information obtained from the database.

[1417] The "means for responding to inquiries from users" is a means for responding based on the information obtained from the database when a user inquires about a specific infertility treatment method.

[1418] The "means for analyzing the user's emotions" is a means for analyzing the user's facial expressions, voice tones, etc., and determining the user's emotions.

[1419] The "means for providing appropriate information based on the emotion analysis means" is a means for providing information on infertility treatment suitable for the user's emotions based on the result of analyzing the user's emotions.

[1420] This invention is a system for providing infertility treatment information, which refers to a database including past treatment records, statistical information, and information disclosures from research institutions, and provides appropriate information on infertility treatment in response to inquiries from users. Furthermore, it has a function of analyzing the user's emotions and providing appropriate information based on the emotions.

[1421] Configuration of the System

[1422] This system is composed of the following main components.

[1423] 1. Database reference means:

[1424] The server refers to a database containing past treatment records, statistical information, and information disclosures from research institutions. This database stores various information related to infertility treatment.

[1425] 2. Information provision means:

[1426] The server provides users with information related to infertility treatment based on the information obtained from the database. As a result, users can obtain information such as the latest treatment methods and success rates.

[1427] 3. Inquiry response means:

[1428] The server responds to inquiries from users based on the information obtained from the database. For example, when a user asks "What is the success rate of PGT-A?", the server retrieves the corresponding information from the database and provides it to the user.

[1429] 4. Sentiment analysis means:

[1430] The server analyzes the user's facial expressions and voice tones to judge the user's sentiment. For this purpose, cameras and microphones installed on smart glasses are used.

[1431] 5. Information provision means based on sentiment:

[1432] The server provides information suitable for the user's sentiment based on the sentiment analysis means. For example, when the user shows a hopeful sentiment, information on success stories and new treatment methods is provided.

[1433] Hardware and software used

[1434] Hardware:

[1435] Smart glasses (with camera and microphone)

[1436] Server

[1437] Software:

[1438] Python

[1439] OpenCV (Image processing library)

[1440] EmotionRecognizer (Emotion recognition library)

[1441] Database (Database access library)

[1442] Flow of processing

[1443] The server uses the camera and microphone of the smart glasses to obtain the user's expression and voice. Using the acquired data, an emotion recognition model analyzes the user's emotion. The user's inquiry is obtained, and the corresponding information is retrieved from the database. Based on the emotion analysis result, additional information (success cases and new treatment methods) is provided. Finally, the acquired information is displayed on the smart glasses.

[1444] Specific example

[1445] For example, if the patient asks "What is the success rate of PGTA?" and shows a hopeful emotion, the smart glasses will display "The success rate of PGTA is 70%. Also, information on recent success cases and new treatment methods will be introduced."

[1446] Example of prompt sentence

[1447] Develop a smart glasses application that analyzes the patient's expression and voice and provides information on infertility treatment based on emotion. When the patient asks "What is the success rate of PGTA?", retrieve information from the database and also provide information on success cases and new treatment methods if the patient shows a hopeful emotion.

[1448] The flow of the specific process in Application Example 2 will be described with reference to FIG. 20.

[1449] Step 1:

[1450] The server uses the camera and microphone of the smart glasses to acquire the user's facial expression and voice. The input is the user's face image and voice data, and the output is these data. Specifically, the camera captures the user's face, and the microphone records the voice.

[1451] Step 2:

[1452] The server executes an emotion recognition model using the acquired face image and voice data. The input is the face image and voice data acquired in Step 1, and the output is the user's emotion (e.g., hopeful, pessimistic, etc.). Specifically, the EmotionRecognizer library is used to analyze the emotion from the image and voice.

[1453] Step 3:

[1454] The server acquires the user's inquiry. The input is the user's voice or text, and the output is the content of the inquiry. Specifically, speech recognition technology is used to convert the user's voice into text and extract the content of the inquiry.

[1455] Step 4:

[1456] The server acquires the corresponding information from the database. The input is the content of the inquiry acquired in Step 3, and the output is the information regarding the corresponding infertility treatment. Specifically, the Database library is used to search the database for the information corresponding to the content of the inquiry.

[1457] Step 5:

[1458] The server selects additional information based on the sentiment analysis results. The input is the sentiment data obtained in step 2 and the infertility treatment information obtained in step 4, and the output is the additional information suitable for the sentiment. Specifically, in the case of a positive sentiment, information regarding successful cases and new treatment methods is selected.

[1459] Step 6:

[1460] The server displays the final information on the smart glasses. The input is the information selected in step 5, and the output is the information displayed on the display of the smart glasses. Specifically, the acquired information is displayed in text format on the display of the smart glasses.

[1461] Step 7:

[1462] The user checks the information provided through the smart glasses. The input is the information displayed on the display of the smart glasses, and the output is the user's understanding and the next action. Specifically, the user reads the displayed information and considers the next treatment steps and questions.

[1463] (Example 3)

[1464] Next, Example 3 of Form Example 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1465] In a conventional infertility treatment information providing system, it has been difficult to provide a prompt and appropriate response to an inquiry from a user. In addition, a function for generating a response according to the user's sentiment is lacking, and an improvement in the user experience has been demanded. Furthermore, the provision of detailed information regarding a specific infertility treatment method has been insufficient.

[1466] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following respective means.

[1467] In this invention, the server includes means for referring to a database containing past treatment records, statistical information, and information disclosures by research institutions; means for providing information on infertility treatment based on the information obtained from the database; means for responding to inquiries from users based on the information obtained from the database; means for generating a response in natural language using a generative AI model; and means for analyzing the user's emotions and generating a response suitable for those emotions. This enables the provision of a prompt and appropriate response to inquiries from users, and furthermore, by generating a response according to the user's emotions, the user experience can be improved.

[1468] The "database" is a collection of information including past treatment records, statistical information, and information disclosures by research institutions.

[1469] The "means for providing information on infertility treatment" is a function for providing information on infertility treatment to users based on the information obtained from the database.

[1470] The "means for responding to inquiries from users" is a function for returning a response to an inquiry input by a user based on the information obtained from the database.

[1471] The "generative AI model" is an artificial intelligence model used to generate a response in natural language.

[1472] The "means for generating a response in natural language" is a function for generating an appropriate response to a user's inquiry in natural language using a generative AI model.

[1473] The "means for analyzing emotions" is a function for analyzing the user's emotions and generating an appropriate response based on those emotions.

[1474] The "means for responding in chat format" is a function for returning a response in real time to an inquiry from a user through a chat interface.

[1475] Mode for Carrying Out the Invention

[1476] This invention is an infertility treatment information providing system that provides real-time responses to inquiries from users. The system refers to a database containing past treatment records, statistical information, and information disclosures from research institutions, and generates responses based on the information obtained. Additionally, it uses a generative AI model to generate responses in natural language and analyzes the user's emotions to provide appropriate responses.

[1477] Hardware and Software to be Used

[1478] Server

[1479] The server accesses the database, receives, and processes inquiries from users. The server uses the following software:

[1480] Database Management System (DBMS)

[1481] Generative AI Model (e.g., GPT-4)

[1482] Emotion Analysis Software (e.g., IBM Watson's Tone Analyzer)

[1483] Terminal

[1484] The terminal is a device for users to input inquiries and receive and display responses from the server. The terminal uses the following software:

[1485] Chat Interface

[1486] Data Processing and Data Calculation

[1487] Database Access

[1488] When the server receives an inquiry from a user, it accesses the database to obtain relevant information. For example, in response to an inquiry such as "What are the advantages and disadvantages of two-stage transplantation?", the server searches the database for information on two-stage transplantation and obtains information on the advantages and disadvantages.

[1489] Response generation by the generative AI model

[1490] Based on the information obtained, the server uses a generative AI model (GPT-4) to generate a natural language response. The generative AI model receives the inquiry content and the obtained information as inputs and generates an appropriate response.

[1491] Sentiment analysis

[1492] The server uses sentiment analysis software to analyze the user's sentiment. For example, if the user is discouraged, the sentiment analysis software detects that sentiment and generates a response containing words of encouragement.

[1493] Specific example

[1494] Specific example 1: Inquiry about the advantages and disadvantages of two-stage transplantation

[1495] 1. The user enters "What are the advantages and disadvantages of two-stage transplantation?" into the chat.

[1496] 2. The terminal sends this inquiry to the server.

[1497] 3. The server receives the inquiry and obtains information on two-stage transplantation from the database.

[1498] 4. Based on the information obtained, the server uses a generative AI model (GPT-4) to generate a response.

[1499] 5. The server sends the generated response to the terminal.

[1500] 6. The terminal displays to the user, "The advantage of two-stage transplantation is that the success rate is high. The disadvantage is that the surgery becomes complicated."

[1501] Specific Example 2: Response Using an Emotion Engine

[1502] 1. The user enters in the chat, "Recently, my work has not been going well and I'm feeling down."

[1503] 2. The terminal sends this inquiry to the server.

[1504] 3. The server receives the inquiry, and the emotion analysis software analyzes the user's emotion.

[1505] 4. The emotion analysis software detects the user's discouragement and generates a response containing encouraging words.

[1506] 5. The server sends the generated response to the terminal.

[1507] 6. The terminal displays to the user, "That's really tough. But you've overcome many difficulties so far. Surely you can overcome this one too."

[1508] In this way, the system can provide a quick and appropriate response to the user's inquiry, and by generating a response according to the user's emotion, it can improve the user experience. The flow of the specific process in Example 3 will be described with reference to FIG. 21.

[1509] Step 1:

[1510] The user inputs an inquiry in chat format.

[1511] Specific operation: The user uses the chat interface of the terminal to input questions or inquiries. For example, the user inputs, "What are the advantages and disadvantages of two-stage transplantation?"

[1512] Input: The content of the user's inquiry

[1513] Output: Data for which the inquiry content is sent to the terminal

[1514] Step 2:

[1515] The terminal sends the inquiry to the server

[1516] Specific operation: The terminal sends the inquiry input by the user to the server in an appropriate format

[1517] Input: The content of the user's inquiry

[1518] Output: Data for which the inquiry content is sent to the server

[1519] Step 3:

[1520] The server receives the inquiry and accesses the database to obtain relevant information

[1521] Specific operation: The server receives the inquiry sent from the terminal and accesses the database to search for relevant information. For example, obtain information on the advantages and disadvantages of "two-stage transplantation"

[1522] Input: The content of the user's inquiry

[1523] Output: Relevant information obtained from the database

[1524] Step 4:

[1525] Based on the information obtained by the server, an AI model is used to generate a response

[1526] Specific operation: Based on the acquired information, the server uses a generative AI model (e.g., GPT-4) to generate a natural language response. The generative AI model receives the query content and the acquired information as inputs and generates an appropriate response.

[1527] Input: Related information acquired from the database, the user's query content

[1528] Output: Natural language response generated by the generative AI model

[1529] Step 5:

[1530] The server sends the response generated to the terminal.

[1531] Specific operation: The server sends the response generated by the generative AI model to the terminal. This response is sent in a format that is easy for the user to understand.

[1532] Input: Natural language response generated by the generative AI model

[1533] Output: Response data sent to the terminal

[1534] Step 6:

[1535] The terminal displays the response to the user.

[1536] Specific operation: The terminal displays the response received from the server to the user. The user can view the response from the server through the chat interface.

[1537] Input: Response data sent from the server

[1538] Output: Response displayed to the user

[1539] Step 7:

[1540] The emotion engine analyzes the user's emotions and generates responses suitable for the emotions as needed.

[1541] Specific operations: The emotion engine analyzes the user's emotions. For example, when the user is discouraged, the emotion engine detects that emotion and generates a response containing encouraging words. This emotion analysis uses emotion analysis software (e.g., IBM Watson's Tone Analyzer).

[1542] Input: User emotion data

[1543] Output: Response data suitable for the emotion

[1544] (Application Example 3)

[1545] Next, Application Example 3 of Morphological Example 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[1546] In the conventional infertility treatment information providing system, although appropriate information can be provided in response to inquiries from users, there is a problem that it is impossible to sufficiently eliminate the users' anxiety and doubts because responses according to the users' emotions cannot be generated. Also, in the security service, although it is required to provide appropriate support according to the users' emotions, there is a problem that it is difficult to achieve this with the current system.

[1547] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure by research institutions, means for providing information regarding infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, and means including an emotion engine for analyzing the emotions of the user and generating a response suitable for the emotion. Thereby, it becomes possible to provide appropriate information and support according to the emotions of the user.

[1548] The "database" is a system that accumulates information including past treatment results, statistical information, and information disclosure by research institutions, and can be referred to as needed.

[1549] The "information providing means" is a function for providing information regarding infertility treatment to the user based on the information obtained from the database.

[1550] The "response means" is a function for generating a response based on the information obtained from the database in response to an inquiry from the user and replying to the user.

[1551] The "emotion engine" is a system for analyzing the emotions of the user and generating a response suitable for the emotion.

[1552] The "chat format" is a communication format in which the user makes an inquiry in a text-based manner and receives a real-time response thereto.

[1553] The system for implementing this invention mainly consists of a server, a user terminal, and a database. The server refers to a database including past treatment results, statistical information, and information disclosure by research institutions, and provides appropriate information in response to inquiries from users. Further, it analyzes the emotions of the user using an emotion engine and generates a response suitable for the emotion.

[1554] Hardware and Software to be Used

[1555] Hardware: Servers, user terminals (such as smartphones, tablets, personal computers, etc.)

[1556] Software: Python, OpenAI API, EmotionRecognizer library, SecurityDatabase class

[1557] Data Processing and Data Calculation

[1558] When the server receives an inquiry from a user, it first analyzes the content of the inquiry. Next, it retrieves relevant information from the database and uses the EmotionRecognizer library to analyze the user's emotions. Based on the results of the emotion analysis, it generates an appropriate response using the OpenAI API.

[1559] Specific Example

[1560] For example, when a user inputs "The security camera at home is not working", the server processes it according to the following steps.

[1561] 1. Receive the user's input.

[1562] 2. Retrieve information about "security camera troubleshooting" from the database.

[1563] 3. Analyze the user's emotions using the EmotionRecognizer library.

[1564] 4. If the user is feeling anxious, use the OpenAI API to generate a response such as "Please don't worry. Check the power of the camera and restart it. If the problem is not solved, please contact support."

[1565] Examples of Prompt Sentences

[1566] Examples of prompt sentences when the user inputs "The home security camera is not operating" are as follows.

[1567] user_input = "The home security camera is not operating"

[1568] response = generate_response(user_input)

[1569] print(response)

[1570] In this way, it becomes possible to provide appropriate information and support according to the user's feelings.

[1571] The flow of specific processing in Application Example 3 will be described with reference to FIG. 22.

[1572] Step 1:

[1573] The user uses the terminal to input a security-related inquiry. For example, input "The home security camera is not operating". This input is sent to the server.

[1574] Input: User's inquiry (e.g., "The home security camera is not operating")

[1575] Output: User's inquiry sent to the server

[1576] Step 2:

[1577] The server analyzes the received user's inquiry. Specifically, it performs text analysis on the inquiry content and extracts relevant keywords.

[1578] Input: User's inquiry

[1579] Output: Extracted keywords (e.g., "security camera", "not working")

[1580] Step 3:

[1581] The server searches the database based on the extracted keywords and retrieves relevant information. For example, it retrieves information regarding "troubleshooting of security cameras".

[1582] Input: Extracted keywords

[1583] Output: Relevant information retrieved from the database (e.g., "Check the power of the camera and restart it.")

[1584] Step 4:

[1585] The server uses the EmotionRecognizer library to analyze the emotion from the user's inquiry. For example, it determines whether the user is feeling anxious.

[1586] Input: User's inquiry

[1587] Output: Analyzed user emotion (e.g., "anxious")

[1588] Step 5:

[1589] The server uses the OpenAI API to generate an appropriate response based on the analyzed emotion. For example, if the user is feeling anxious, it generates a response to reassure the user.

[1590] Input: Relevant information retrieved from the database, Analyzed user emotion

[1591] Output: Generated response (e.g., "Don't worry. Check the power of the camera and restart it. If the problem persists, contact support.")

[1592] Step 6:

[1593] The server sends the generated response to the user's terminal. The user can check the response on the terminal.

[1594] Input: Generated response

[1595] Output: Response sent to the user's terminal

[1596] In this way, it becomes possible to provide appropriate information and support according to the user's feelings.

[1597] The specific processing unit 290 sends 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 a voice indicating a user input for the result of the specific processing. The control unit 46A sends voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1598] The data generation model 58 is a so-called generative AI (Artificial Intelligence).

[1599] As an example of the data generation model 58, generative AIs such as ChatGPT (Internet search <URL: https: / / openai.com / blog / chatgpt>) can be mentioned. The data generation model 58

[1600] It is obtained by performing deep learning on a neural network. In the data generation model 58, a prompt including instructions is input, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is input. The data generation model 58 infers the input inference data according to the instructions 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 summary, etc.

[1601] As another example of generative AI, Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) can be mentioned.

[1602] In the above embodiment, an example of a form in which specific processing is performed by the data processing device 12 is given. However, the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1603] [Third Embodiment]

[1604] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1605] As shown in FIG. 5, the data processing system 310 includes a data processing device 12 and a headset-type terminal 314. An example of the data processing device 12 is a server.

[1606] 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 the "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. Also, the database 24 and the communication I / F 26 are 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).

[1607] 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. Also, the microphone 238, the speaker 240, the camera 42, and the display 343 are connected to the bus 52.

[1608] The microphone 238 receives instructions and the like from the user 20 by receiving the voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into voice data, and outputs the voice data to the processor 46. The speaker 240 outputs voice according to an instruction from the processor 46.

[1609] The camera 42 is a small digital camera equipped with an optical system such as a lens, an aperture, and a shutter, and an imaging device such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and images the surroundings of the user 20 (for example, an imaging range defined by an angle of view corresponding to the field of view of a general healthy person).

[1610] The communication I / F 44 is connected to the 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 performed in a secure state.

[1611] 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, specific processing is performed by the processor 28. The specific processing program 56 is stored in the storage 32.

[1612] The specific processing program 56 is an example of the "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 operating as the specific processing unit 290 according to the specific processing program 56 executed by the processor 28 on the RAM 30.

[1613] 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 specific processing unit 290

[1614] .

[1615] In the headset type terminal 314, input / output processing is performed by the processor 46. The storage 50 stores an input / output program 60. The processor 46 reads the input / output program 60 from the storage 50 and executes the read input / output program 60 on the RAM 48. The input / output processing is realized by operating as a control unit 46A according to the input / output program 60 executed by the processor 46 on the RAM 48.

[1616] Next, the specific processing by the specific processing unit 290 of the data processing apparatus 12 will be described.

[1617] "Embodiment 1"

[1618] As an embodiment of the present invention, there is a system for providing infertility treatment information. This system has means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions. Specifically, the database collects and organizes information on various infertility treatment methods, information on the treatment results and treatment processes of patients to whom those treatment methods have been applied, research results on infertility treatment published at various research institutions, and the like.

[1619] "Embodiment 2"

[1620] The above system has a means to respond to inquiries from users based on information obtained from a database. Specifically, when a user inquires about a specific infertility treatment method, the system obtains information about the corresponding treatment method from the database and responds to the user based on it. For example, when a user inquires "What is the success rate of PGTA?", the system obtains information about the success rate of PGTA from the database and provides it to the user.

[1621] "Form Example 3"

[1622] Furthermore, the above system has a means to respond to inquiries from users in a chat format. Specifically, when a user makes an inquiry in a chat format, the system returns a response to it in real time. This response is generated based on information obtained from the database. For example, when a user inquires "What are the advantages and disadvantages of two-stage transplantation?", the system obtains information about the advantages and disadvantages of two-stage transplantation from the database and returns a response to the user based on it.

[1623] The processing flow of each form example will be described below.

[1624] "Form Example 1"

[1625] Step 1: The system refers to a database including past treatment records, statistical information, and information disclosures at research institutions.

[1626] Step 2: Based on the information obtained from the database, provide information about infertility treatment. "Form Example 2"

[1627] Step 1: Receive an inquiry from the user.

[1628] Step 2: Obtain information corresponding to the inquiry from the database.

[1629] Step 3: Based on the acquired information, return a response to the user.

[1630] "Form Example 3"

[1631] Step 1: Receive a chat-based inquiry from the user.

[1632] Step 2: Retrieve information corresponding to the inquiry from the database.

[1633] Step 3: Based on the acquired information, return a real-time response to the user.

[1634] (Example 1)

[1635] Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the headset-type terminal 314 is referred to as the "terminal".

[1636] Information regarding infertility treatment is diverse, and it is difficult for patients and medical staff to obtain the necessary information quickly and accurately. In addition, there is a lack of a system for effectively utilizing past treatment records, statistical information, and information disclosure by research institutions. Furthermore, even when a user inputs specific search conditions, the means for appropriately providing relevant information are limited. As a result, it has become difficult for users to make decisions for selecting the optimal treatment method.

[1637] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following respective means.

[1638] In this invention, the server includes means for referring to a database containing past treatment records, statistical information, and information disclosures from research institutions; means for providing information on infertility treatment based on the information obtained from the database; means for responding to inquiries from users based on the information obtained from the database; means for sorting the collected data by category and storing it in the database; means for analyzing the search conditions input by the user and sending a request to the server; and means for displaying the data returned from the server to the user. As a result, users can quickly and accurately obtain the necessary infertility treatment information and make decisions to select the optimal treatment method.

[1639] The "database" is a collection of information that stores and can be referred to information including past treatment records, statistical information, and information disclosures from research institutions.

[1640] The "means for referring" is a method or technique for searching for information in the database and obtaining the necessary data.

[1641] The "means for providing" is a method or technique for displaying the obtained information to the user and providing it in a usable form.

[1642] The "means for responding" is a method or technique for returning an answer based on the information obtained from the database in response to an inquiry from the user.

[1643] The "means for sorting" is a method or technique for classifying the collected data by category and efficiently storing it in the database.

[1644] The "means for analyzing" is a method or technique for understanding the search conditions input by the user and generating an appropriate request based on them.

[1645] The "means for sending" is a method or technique for sending the analyzed request to the server and obtaining the necessary information.

[1646] The "display means" refers to the methods and technologies for displaying the data returned from the server in a user-friendly format.

[1647] This invention is a system for providing infertility treatment information, in which the server, the terminal, and the user cooperate and operate. The specific operations of each entity are described below.

[1648] Server Operations

[1649] The server plays a central role in collecting, organizing, and providing information related to infertility treatment. The server uses the following hardware and software.

[1650] Hardware: High-performance processors, sufficient memory, storage devices

[1651] Software: Database management system (DBMS), API interface, data analysis tools

[1652] The server automatically collects information related to infertility treatment from the Internet or partnering research institutions. For example, it accesses the databases of research institutions through APIs and obtains data on "the success rate of treatment method A" and "the side effects of treatment method B". The collected data is organized by category and stored in the database. Duplicate and inconsistent data are checked, and data cleansing is performed as necessary.

[1653] In response to requests from users, the server extracts appropriate information from the database and returns it to the terminal. The data is filtered based on the content of the request to provide the most relevant information to the user.

[1654] Terminal Operations

[1655] The terminal provides an interface for users to search for and view infertility treatment information. The terminal uses the following hardware and software.

[1656] Hardware: Personal computer, smartphone, tablet

[1657] Software: Web browser, mobile application

[1658] The terminal provides an interface that enables the user to easily search for information. For example, it displays web pages and applications with a search bar and filtering functions. When the user enters search criteria, the terminal sends that request to the server. When sending the request, the terminal converts the user's input into an appropriate format so that the server can understand it.

[1659] Upon receiving the data returned from the server, the terminal displays it to the user. The displayed information is provided in a visual format such as graphs and charts to enable the user to intuitively understand the information.

[1660] User operations

[1661] The user utilizes this system to obtain information regarding infertility treatment. The user operates the system according to the following procedure.

[1662] 1. Input of search criteria: The user enters search criteria through the terminal's interface. For example, the user enters conditions such as "treatment methods suitable for women aged 40 and above" or "side effects of treatment method D". Filtering options for setting search criteria in detail can also be utilized.

[1663] 2. Browsing of information: The user browses the information provided by the server on the terminal. For example, when the user searches for "success rate of treatment method E", the user checks the result on the terminal. The user can scroll through the displayed information to check the details and utilize the function to save the information as needed.

[1664] 3. Decision-making support: Based on the information provided, the user considers options for infertility treatment. For example, the user makes a decision such as "confirming that treatment method F has a high success rate and deciding to try that method." Tools can also be used to compare multiple treatment methods and find the optimal option.

[1665] Specific examples and prompt sentences

[1666] For example, when the user searches for "infertility treatment methods suitable for women aged 35 or older," the processing is performed in the following steps.

[1667] 1. The user enters "infertility treatment methods suitable for women aged 35 or older" in the search bar of the terminal.

[1668] 2. The terminal sends the request to the server.

[1669] 3. The server extracts the relevant information from the database and returns it to the terminal.

[1670] 4. The terminal displays the information to the user.

[1671] 5. Based on the displayed information, the user considers an appropriate treatment method.

[1672] By inputting the following prompt sentence to the generative AI model, specific infertility treatment information can be obtained.

[1673] "Please tell me about infertility treatment methods suitable for women aged 35 or older. Provide detailed information based on past treatment records, statistical information, and information disclosures from research institutions."

[1674] By inputting this prompt sentence, the generative AI model provides the relevant information and supports the user's decision-making.

[1675] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[1676] Step 1:

[1677] Data collection

[1678] The server automatically collects information on infertility treatment from the Internet or partner research institutions. As input, it accesses the research institution's database through an API and obtains data on "the success rate of treatment method A" and "the side effects of treatment method B". As output, the collected data is stored in the server's temporary storage. As a specific operation, the server periodically sets a data collection schedule and updates the database whenever new information is published.

[1679] Step 2:

[1680] Data sorting

[1681] The server sorts the collected data by category and stores it in the database. As input, it receives the data stored in the temporary storage. As output, the sorted data is stored in the database. As a specific operation, the server checks for data duplication and inconsistencies and cleans the data as needed. For example, if data for the same patient is collected multiple times, it is integrated into one.

[1682] Step 3:

[1683] Providing a user interface

[1684] The terminal provides an interface that allows users to easily search for information. As input, it receives the user's search criteria. As output, the search criteria are sent to the server. As a specific operation, the terminal displays a web page or application with a search bar and filtering functions. It analyzes the search criteria entered by the user in real time and provides a suggestion function.

[1685] Step 4:

[1686] Sending a Request

[1687] The terminal sends the search conditions entered by the user to the server. As input, it receives the user's search conditions. As output, a request converted into an appropriate format is sent to the server. As a specific operation, when sending the request, the terminal converts the input content of the user into an appropriate format so that the server can understand it.

[1688] Step 5:

[1689] Data Provision

[1690] The server extracts appropriate information from the database in response to the request from the user and returns it to the terminal. As input, it receives the request sent from the terminal. As output, the corresponding information is returned to the terminal. As a specific operation, the server filters the data based on the content of the request and provides the information most relevant to the user.

[1691] Step 6:

[1692] Display of Results

[1693] The terminal displays the data returned from the server to the user. As input, it receives the data returned from the server. As output, the information is displayed in a user-friendly format. As a specific operation, the terminal provides the displayed information in a visual format such as graphs or charts so that the user can intuitively understand the information.

[1694] Step 7:

[1695] Viewing of Information

[1696] The user views the information displayed on the terminal. As input, the user receives the information displayed on the terminal. As output, the user checks the information and saves it if necessary. As a specific operation, the user scrolls the displayed information to check the details and uses the function to save the information if necessary.

[1697] Step 8:

[1698] Support for decision-making

[1699] Based on the provided information, the user considers the options for infertility treatment. As input, the user receives the information displayed on the terminal. As output, a decision is made for the user to select the optimal treatment method. As a specific operation, the user compares multiple treatment methods and uses tools to find the optimal option. For example, a comparison table for comparing the success rates and side effects of each treatment method is used.

[1700] (Application Example 1)

[1701] Next, Application Example 1 of the morphological example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the headset-type terminal 314 is referred to as a "terminal".

[1702] Couples or individuals considering infertility treatment need to collect and compare a lot of information to find the optimal treatment method and medical institution. However, this information is scattered and difficult to collect efficiently. In addition, it is difficult to obtain information based on the latest research results and treatment records, and there is a lack of judgment materials when selecting an appropriate treatment method and medical institution. For this reason, a system that can be easily accessed by users and provides reliable information is required.

[1703] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1704] In this invention, the server includes means for referring to a database containing past treatment records, statistical information, and information disclosures by research institutions; means for providing information on infertility treatment based on the information obtained from the database; means for responding to inquiries from users based on the information obtained from the database; means for proposing an optimal treatment method based on the symptoms and desired treatment methods input by the user; and means for searching for an optimal medical institution based on the user's location information and desired treatment method. Thereby, the user can efficiently obtain highly reliable infertility treatment information and select an optimal treatment method and medical institution.

[1705] "Past treatment records" refer to data regarding the results and processes of infertility treatments performed in the past.

[1706] "Statistical information" refers to information obtained by aggregating and analyzing numerical data regarding treatment results and treatment processes.

[1707] "Information disclosures by research institutions" refer to information such as research results and papers on infertility treatment publicly disclosed by research institutions.

[1708] "Database" refers to a system for organizing and storing information including past treatment records, statistical information, and information disclosures by research institutions.

[1709] "Information on infertility treatment" refers to information such as infertility treatment techniques, treatment results, treatment processes, and the latest research results.

[1710] "Inquiries from users" refer to questions and requests for information made by users to the system.

[1711] "Symptoms" refer to physical and medical conditions related to infertility experienced by the user.

[1712] "Desired treatment method" refers to the method of infertility treatment that the user wishes to receive.

[1713] The "optimal treatment method" refers to the method of infertility treatment that best suits the user's symptoms and wishes.

[1714] The "location information" refers to the data regarding the place where the user is currently located.

[1715] The "medical institution" refers to facilities such as clinics and hospitals that provide infertility treatment.

[1716] The "chat format" refers to the format of communicating in real time using text messages.

[1717] The system for implementing this invention includes a server, a user terminal, and a database. The server refers to a database including past treatment records, statistical information, and information disclosures from research institutions, and provides information regarding infertility treatment to the user. The user terminal is a device such as a smartphone or a tablet, and provides an interface for the user to access the system.

[1718] The server includes the following means:

[1719] 1. Database reference means: Refer to a database including past treatment records, statistical information, and information disclosures from research institutions.

[1720] 2. Information providing means: Provide information regarding infertility treatment based on the information obtained from the database.

[1721] 3. Inquiry response means: Respond to inquiries from the user based on the information obtained from the database.

[1722] 4. Treatment method proposal means: Propose the optimal treatment method based on the symptoms input by the user and the treatment method the user desires.

[1723] 5. Medical institution search means: Search for the optimal medical institution based on the user's location information and the treatment method the user desires.

[1724] Hardware and Software to be Used:

[1725] Hardware: Server, Smartphone, Tablet

[1726] Software: Flask (a Python web framework), requests (a Python library for sending HTTP requests)

[1727] Data Processing and Data Calculation:

[1728] The server receives input data (symptoms, desired treatment methods, location information) from users and searches for relevant information in the database. The search results are proposed as the optimal treatment methods and medical institutions for the users. Specifically, a web application is built using Flask, and the requests library is used to communicate with the database.

[1729] Specific Example:

[1730] When a user opens the "Infertility Treatment Navigator" app and enters their symptoms (e.g., polycystic ovary syndrome) and desired treatment method (e.g., in vitro fertilization), the server searches the database for the optimal treatment method and medical institution and proposes them to the user.

[1731] Example of a Prompt Sentence:

[1732] The user has symptoms of polycystic ovary syndrome and desires in vitro fertilization. Please propose the optimal treatment method and medical institution.

[1733] In this way, users can efficiently obtain reliable infertility treatment information and select the optimal treatment methods and medical institutions.

[1734] The flow of specific processing in Application Example 1 will be described with reference to FIG. 12.

[1735] Step 1:

[1736] The user launches an application on a smartphone or tablet and enters symptoms, desired treatment methods, and location information.

[1737] Input: Symptoms, desired treatment methods, location information

[1738] Output: User input data

[1739] Specific operation: The user enters symptoms (e.g., polycystic ovary syndrome), desired treatment methods (e.g., in vitro fertilization), and location information into the input form of the application and presses the send button.

[1740] Step 2:

[1741] The user terminal sends the input data to the server.

[1742] Input: User input data

[1743] Output: Request to the server

[1744] Specific operation: The user terminal sends the input data to the server as an HTTP request.

[1745] Step 3:

[1746] The server analyzes the received user input data and searches for relevant treatment method information from the database.

[1747] Input: User input data

[1748] Output: Treatment method information

[1749] Specific operation: The server uses Flask to analyze the received data, sends a query to the database using the requests library, and obtains relevant treatment method information.

[1750] Step 4:

[1751] Based on the treatment method information obtained by the server, propose the most suitable treatment method for the user's symptoms and desired treatment method.

[1752] Input: Treatment method information, user input data

[1753] Output: Proposal for the most suitable treatment method

[1754] Specific operation: Analyze the treatment method information obtained by the server, select and propose the treatment method that best suits the user's symptoms and wishes.

[1755] Step 5:

[1756] The server searches for the most suitable medical institution based on the user's location information and desired treatment method.

[1757] Input: Location information, desired treatment method

[1758] Output: Medical institution information

[1759] Specific operation: The server searches the database based on the location information and desired treatment method, and obtains the information of the most suitable medical institution.

[1760] Step 6:

[1761] The server sends the proposal for the most suitable treatment method and medical institution information to the user terminal.

[1762] Input: Proposal for the most suitable treatment method, medical institution information

[1763] Output: Response to the user terminal

[1764] Specific operation: The server sends the proposal for the most suitable treatment method and medical institution information to the user terminal as an HTTP response.

[1765] Step 7:

[1766] The user terminal receives the response from the server and displays it to the user.

[1767] Input: Response from the server

[1768] Output: Display information to the user

[1769] Specific operation: The user terminal receives the response from the server and displays the optimal treatment proposal and medical institution information on the interface of the application.

[1770] In this way, the user can efficiently obtain highly reliable infertility treatment information and select the optimal treatment method and medical institution.

[1771] (Example 2)

[1772] Next, Example 2 of the second morphological example will be described. In the following description, the data processing device 12 is referred to as the "server", and the headset type terminal 314 is referred to as the "terminal".

[1773] In the conventional infertility treatment information providing system, it was difficult for users to quickly and accurately obtain the information they needed. In addition, there was a lack of means to provide detailed information on specific infertility treatment methods, and it was impossible to appropriately respond to user inquiries. Furthermore, the user interface was insufficient, and the environment in which users could easily obtain information was not well-established.

[1774] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1775] In this invention, the server includes means for a user to input an inquiry from a terminal, means for the terminal to send the inquiry to the server, means for the server to analyze the inquiry, means for the server to access a database to obtain information, means for the server to send the obtained information to the terminal, and means for the terminal to display the information to the user. Thereby, the user can obtain necessary infertility treatment information quickly and accurately.

[1776] A "user" is an individual or group who attempts to obtain information using the system.

[1777] A "terminal" is an electronic device used by a user to input an inquiry and receive information.

[1778] A "server" is a computer system that has the role of receiving, analyzing, accessing a database to obtain information, and sending it to the terminal in response to an inquiry from a user.

[1779] An "inquiry" is a question or request input by a user to the system through the terminal.

[1780] A "database" is a data storage system for storing information including past treatment results, statistical information, and information disclosures by research institutions.

[1781] "Means for obtaining information" is a process for the server to access the database, search for, and obtain necessary information.

[1782] "Means for displaying information" is a function for the terminal to display the information received from the server in an easy-to-view format for the user.

[1783] "Specific infertility treatment methods" refer to specific infertility treatment methods such as PGTA and two-stage transplantation.

[1784] The "chat format" is an interface format for users to make inquiries in an interactive manner with the system and receive responses.

[1785] This invention is a system that enables users to quickly and accurately obtain information regarding infertility treatment using a terminal. The system operates when a user inputs an inquiry from the terminal and transmits the inquiry to the server. The server analyzes the inquiry, accesses a database to obtain the necessary information, and transmits the obtained information to the terminal. The terminal displays the received information to the user.

[1786] This system uses the following hardware and software:

[1787] Terminal: Electronic devices such as smartphones, tablets, and personal computers

[1788] Server: High-performance computer system

[1789] Database Management System (DBMS): MySQL

[1790] Server software: Apache

[1791] Programming language: Python

[1792] As a specific example of operation, a user inputs "What is the success rate of PGTA?" into the input field of the terminal. This inquiry is transmitted from the terminal to the server, and the server accesses the MySQL database to obtain information regarding the success rate of PGTA. Subsequently, the obtained information is transmitted to the terminal, and the terminal displays to the user "The success rate of PGTA is 60%."

[1793] Examples of prompt sentences:

[1794] User: What is the success rate of PGTA?

[1795] Server: Retrieving information from the database...

[1796] Server: The success rate of PGTA is about 60%.

[1797] With this system, users can quickly and accurately obtain detailed information on specific infertility treatment methods. In addition, since it has a function of answering inquiries in a chat format, users can obtain information in an interactive manner. This greatly improves the convenience for users.

[1798] The flow of the specific process in Example 2 will be described with reference to FIG. 13.

[1799] Step 1:

[1800] The user inputs an inquiry from the terminal.

[1801] As a specific operation, the user opens a browser on a smartphone or a personal computer and inputs "What is the success rate of PGTA?" in the search bar. The input inquiry is displayed in the input field of the terminal.

[1802] Input: Inquiry input by the user (e.g., "What is the success rate of PGTA?")

[1803] Output: Inquiry displayed in the input field of the terminal

[1804] Step 2:

[1805] The terminal sends the inquiry to the server.

[1806] The terminal sends the inquiry input by the user to the server as an HTTP request. At this time, the terminal sends the inquiry content to the server in JSON format.

[1807] Input: Inquiry input by the user (e.g., "What is the success rate of PGTA?")

[1808] Output: HTTP request sent to the server (example: {"query": "What is the success rate of PGTA?"})

[1809] Step 3:

[1810] The server analyzes the query.

[1811] The server analyzes the received HTTP request and extracts the query content. For example, it recognizes that the query is "What is the success rate of PGTA?".

[1812] Input: HTTP request sent from the terminal (example: {"query": "What is the success rate of PGTA?"})

[1813] Output: Analyzed query content (example: "What is the success rate of PGTA?")

[1814] Step 4:

[1815] The server accesses the database to obtain information.

[1816] The server sends a query to the database based on the query content. For example, it executes a query like "SELECT success_rate FROM treatments WHERE name='PGTA'". The database returns a success rate of "60%".

[1817] Input: Analyzed query content (example: "What is the success rate of PGTA?")

[1818] Output: Information obtained from the database (example: "60%")

[1819] Step 5:

[1820] The server sends the obtained information to the terminal.

[1821] The server converts the information obtained from the database into JSON format and sends it to the terminal as an HTTP response. For example, it sends information such as "The success rate of PGTA is 60%".

[1822] Input: Information obtained from the database (example: "60%")

[1823] Output: HTTP response sent to the terminal (example: {"response": "The success rate of PGTA is 60%"})

[1824] Step 6:

[1825] The terminal displays the information to the user.

[1826] The terminal analyzes the information received from the server and displays it in a user-friendly format. For example, it displays "The success rate of PGTA is 60%" on the screen.

[1827] Input: HTTP response sent from the server (example: {"response": "The success rate of PGTA is 60%"})

[1828] Output: Information displayed to the user (example: "The success rate of PGTA is 60%")

[1829] (Application Example 2)

[1830] Next, Application Example 2 of Embodiment 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the headset-type terminal 314 is referred to as the "terminal".

[1831] The conventional infertility treatment information providing system is specialized in providing information related to infertility treatment, so there is a problem that users cannot obtain information related to security. In addition, a separate system for providing security information is required, which also causes a problem of reduced convenience for users

[1832] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for referring to a database including past treatment results, statistical information, and information disclosure at research institutions; means for providing information regarding infertility treatment based on the information obtained from the database; means for responding to an inquiry from a user based on the information obtained from the database; means for referring to a database for providing security information; and means for responding to the user based on the security information obtained from the database. Thereby, it becomes possible to provide both infertility treatment information and security information in one system.

[1833] "Infertility treatment information" refers to all information regarding infertility treatment, including past treatment results, statistical information, and information disclosure at research institutions.

[1834] "Database" refers to an aggregate of information that systematically organizes and stores specific information so that it can be retrieved and obtained as needed.

[1835] "Inquiry from a user" refers to a question or request made by a person using the system to obtain specific information.

[1836] "Means for responding" refers to a method or apparatus for providing appropriate information in response to an inquiry from a user.

[1837] "Security information" refers to the latest methods and countermeasure information regarding security such as phishing fraud and unauthorized access.

[1838] "Chat format" refers to a method of real-time information exchange in a text-based dialogue format.

[1839] The system for implementing this invention consists of a server, a user terminal, and a database. The server refers to a database including past treatment records, statistical information, and information disclosures at research institutions, and provides appropriate information in response to inquiries from users. It also refers to a database for providing security information and responds to users with the latest security information.

[1840] The server uses the Flask framework to build a web application and manages information using an SQLite database. The user terminal is a device such as a smartphone or a personal computer and accesses the server via the Internet. When a user inquires about specific information, the server retrieves the corresponding information from the database and provides it to the user.

[1841] As a specific processing flow, when a user makes an inquiry such as "What are the latest phishing fraud methods?" from the terminal, the server retrieves information on the latest phishing fraud from the SQLite database and returns that information to the user. As a result, the user can quickly obtain the necessary information.

[1842] The hardware used is a computer as the server and a smartphone or personal computer as the user terminal. The software used is Flask (Python framework) and SQLite (database).

[1843] As a specific example, when a user inquires "What are the latest phishing fraud methods?", the server retrieves information on the latest phishing fraud from the database and responds as follows.

[1844] "The latest phishing fraud method is to steal personal information using fake bank emails."

[1845] Examples of prompt texts for the generative AI model are as follows.

[1846] When the user inquires "What are the latest phishing fraud methods?", obtain information on the latest phishing fraud from the database and respond as follows.

[1847] "The latest phishing fraud method is to steal personal information using fake bank emails."

[1848] The flow of the specific process in Application Example 2 will be described with reference to FIG. 14.

[1849] Step 1:

[1850] The user inputs an inquiry from the terminal. The user uses a smartphone or a personal computer to input a question seeking specific information. For example, input "What are the latest phishing fraud methods?". The input data is a text-based inquiry.

[1851] Step 2:

[1852] The terminal sends the inquiry to the server. The inquiry input by the user is sent to the server via the Internet. The input data is the user's inquiry text, and the output data is the inquiry sent to the server.

[1853] Step 3:

[1854] The server receives the inquiry and accesses the database. The server uses the Flask framework to receive the inquiry and accesses the SQLite database. The input data is the user's inquiry text, and the output data is the execution result of the database query.

[1855] Step 4:

[1856] The server retrieves the corresponding information from the database. The server executes an SQL query to retrieve the information corresponding to the user's inquiry from the database. For example, it retrieves information regarding "the latest phishing fraud methods". The input data is the SQL query, and the output data is the retrieved information.

[1857] Step 5:

[1858] The server generates a response based on the information it has retrieved. The server generates a response to the user based on the retrieved information. For example, it generates a response such as "The latest phishing fraud method is a technique of stealing personal information using fake bank emails." The input data is the retrieved information, and the output data is the generated response text.

[1859] Step 6:

[1860] The server sends the response it has generated to the terminal. The server sends the generated response to the user's terminal. The input data is the generated response text, and the output data is the response sent to the terminal.

[1861] Step 7:

[1862] The terminal receives the response from the server and displays it to the user. The user's terminal displays the response received from the server. For example, it displays "The latest phishing fraud method is a technique of stealing personal information using fake bank emails." The input data is the response text from the server, and the output data is the response displayed to the user.

[1863] (Example 3)

[1864] Next, Example 3 of Form Example 3 will be described. In the following description, the data processing device 12 is referred to as the "server", and the headset type terminal 314 is referred to as the "terminal".

[1865] In the conventional infertility treatment information providing system, there was a problem that it was difficult to respond promptly and appropriately to inquiries from users. In addition, there was a lack of means to provide detailed information on specific medical techniques, making it difficult for users to obtain the information they needed in a timely manner. Furthermore, since there was no inquiry response function in the chat format, the user experience had deteriorated.

[1866] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1867] In this invention, the server includes means for receiving an inquiry from a user, means for analyzing the inquiry, means for obtaining information from a database based on the analysis result, means for transmitting a prompt sentence to a generated AI model based on the obtained information, and means for returning a response from the generated AI model to the user. Thereby, it becomes possible to respond promptly and appropriately to an inquiry from a user. In addition, by including means for providing detailed information on a specific medical technique, the user can obtain the information they need in a timely manner. Furthermore, by including an inquiry response function in the chat format, the user experience can be improved.

[1868] The "means for receiving an inquiry from a user" is a function for the server to receive an inquiry transmitted by a user through a web browser or a mobile application.

[1869] The "means for analyzing the inquiry" is a function for analyzing the received inquiry content and extracting keywords and intentions.

[1870] The "means for obtaining information from a database" is a function for obtaining necessary information from a database based on the analysis result.

[1871] The "means for sending a prompt sentence to the generative AI model" is a function for sending the prompt sentence generated based on the acquired information to the generative AI model.

[1872] The "means for returning the response from the generative AI model to the user" is a function for returning the response received from the generative AI model to the user.

[1873] The "means for providing information on a specific medical technique" is a function for providing the user with detailed information on a specific medical technique.

[1874] The "means for responding to user inquiries in chat format" is a function for responding in real time to user inquiries in chat format.

[1875] Mode for Carrying Out the Invention

[1876] This invention is a system for quickly and appropriately responding to user inquiries. The following describes specific embodiments of this system.

[1877] 1. Generation of the System Program

[1878] The system program is developed using Python and operates as a web server using the Flask framework. MySQL is used for the database, and a general generative AI model (e.g., GPT-3) is used for the generative AI model.

[1879] 2. Program Processing

[1880] The server receives an inquiry from the user and analyzes the inquiry. For the analysis, a text analysis library (e.g., NLTK or spaCy) is used. Based on the analysis result, the server acquires the necessary information from the database. Based on the acquired information, the server sends a prompt sentence to the generative AI model and returns the response from the generative AI model to the user.

[1881] 3. Specific Example

[1882] Consider the case where a user sends a query "What are the advantages and disadvantages of two-stage transplantation?" using a web browser or a mobile app. In this case, the server processes as follows.

[1883] 1. The user sends a query in chat format "What are the advantages and disadvantages of two-stage transplantation?".

[1884] 2. The server receives and analyzes this query.

[1885] 3. The server executes an SQL query to obtain information about "the advantages and disadvantages of two-stage transplantation" from the MySQL database.

[1886] 4. Based on the obtained information, input the following prompt sentence into the generative AI model.

[1887] Example of prompt sentence: "Please tell me about the advantages and disadvantages of two-stage transplantation. The advantages are 〇〇, and the disadvantages are △△."

[1888] 5. The generative AI model (e.g., GPT-3) generates a response based on this prompt sentence.

[1889] 6. The server returns the generated response to the user in real time.

[1890] In this way, the system can respond quickly and appropriately to the user's query. The flow of specific processing in Example 3 will be described with reference to FIG. 15.

[1891] Step 1:

[1892] The user sends a query

[1893] The user sends an inquiry in chat format using a web browser or a mobile app. For example, the user enters "What are the advantages and disadvantages of two-stage transplantation?" and clicks the send button. The input is the content of the user's inquiry, and the output is an HTTP request to the server.

[1894] Step 2:

[1895] The server receives the inquiry.

[1896] The server uses the Flask framework to receive the HTTP request from the user. The received request contains the content of the user's inquiry. The input is the HTTP request from the user, and the output is the text data of the inquiry content.

[1897] Step 3:

[1898] The server analyzes the inquiry.

[1899] The server analyzes the received inquiry content using a text analysis library (such as NLTK or spaCy). Through the analysis, keywords and intentions are extracted. The input is the text data of the inquiry content, and the output is the analysis result (keywords and intentions).

[1900] Step 4:

[1901] The server obtains information from the database.

[1902] The server obtains the necessary information from the MySQL database based on the analysis result. For example, to obtain information about "the advantages and disadvantages of two-stage transplantation," an SQL query is executed. The input is the analysis result, and the output is the information obtained from the database.

[1903] Step 5:

[1904] The server sends a prompt sentence to the generative AI model.

[1905] Based on the acquired information, the server generates a prompt sentence and sends it to the generative AI model. For example, it generates a prompt sentence such as "Please tell me the advantages and disadvantages of two-stage transplantation. The advantages are 〇〇, and the disadvantages are △△." The input is the information acquired from the database, and the output is the prompt sentence for the generative AI model.

[1906] Step 6:

[1907] The generative AI model generates a response

[1908] Based on the received prompt sentence, the generative AI model generates a response. For example, it generates a response such as "The advantages of two-stage transplantation are a high success rate and less burden on the patient. On the other hand, the disadvantages are that the surgery is complex and time-consuming." The input is the prompt sentence, and the output is the generated response.

[1909] Step 7:

[1910] The server returns the response to the user

[1911] The server returns the response received from the generative AI model to the user. Specifically, it returns the response as an HTTP response, which is displayed on the user's screen. The input is the generated response, and the output is the HTTP response to the user.

[1912] (Application Example 3)

[1913] Next, Application Example 3 of Embodiment Example 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the headset-type terminal 314 is referred to as a "terminal".

[1914] In the conventional infertility treatment information providing system, there has been a problem that it is difficult to provide a prompt and accurate response to inquiries from users. In addition, due to the lack of detailed information provision regarding specific infertility treatment methods, there has also been a problem that it takes time for users to obtain the necessary information. Furthermore, there has been a lack of technology for generating appropriate responses to users' questions.

[1915] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following respective means.

[1916] In this invention, the server includes means for referring to a database including past treatment records, statistical information, and information disclosures at research institutions, means for providing information regarding infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, and means for generating an appropriate response to users' questions using a generative AI model. As a result, users can obtain a prompt and accurate response, and detailed information regarding specific infertility treatment methods is also provided, so that it becomes possible to quickly obtain the necessary information.

[1917] "Past treatment records" refer to data regarding the results and progress of infertility treatments performed previously.

[1918] "Statistical information" refers to data indicating the results of aggregating and analyzing a plurality of treatment data.

[1919] "Information disclosures at research institutions" refer to research results and reports regarding infertility treatment publicly disclosed by academic institutions and medical institutions.

[1920] "Database" refers to a system for systematically managing and storing data such as past treatment records, statistical information, and information disclosures at research institutions.

[1921] "Information regarding infertility treatment" refers to detailed data regarding the methods, effects, side effects, success rates, etc. of infertility treatment.

[1922] "Inquiries from users" refer to the act of an individual using the system to seek questions and information regarding infertility treatment.

[1923] "Generative AI model" refers to an algorithm or program that uses artificial intelligence to generate appropriate responses to users' questions.

[1924] "Appropriate response" refers to an answer that provides accurate and useful information in response to a user's question.

[1925] The system for implementing this invention is configured as follows. The server includes means for referring to a database containing past treatment records, statistical information, and information disclosures by research institutions, means for providing information regarding infertility treatment based on the information obtained from the database, means for responding to inquiries from users based on the information obtained from the database, and means for generating appropriate responses to users' questions using a generative AI model.

[1926] Hardware and Software Used

[1927] Hardware: Server, Smartphone

[1928] Software: Python, SQLite, OpenAI API

[1929] Data Processing and Data Calculation

[1930] The server first connects to a database containing past treatment records, statistical information, and information disclosures by research institutions using SQLite. When a user accesses the system using a smartphone and makes an inquiry in chat format, the server analyzes the content of the inquiry.

[1931] Information Acquisition from the Database

[1932] When the user's inquiry is about a specific infertility treatment method, the server retrieves the corresponding information from the database and provides it to the user. For example, when the user asks, "What are the advantages and disadvantages of two-stage transplantation?", the server retrieves information about two-stage transplantation from the database and generates a response based on it.

[1933] Use of the generation AI model

[1934] When the user's inquiry is not directly related to the database, the server uses the generation AI model to generate an appropriate response. Specifically, the OpenAI API is used to generate a prompt sentence for the user's question, and based on that prompt sentence, the AI generates a response.

[1935] Specific example

[1936] For example, when the user asks, "Tell me the specifications of the iPhone 13", the server retrieves the specification information of the iPhone 13 from the database and returns that information to the user. Also, when the user asks, "What are the advantages and disadvantages of two-stage transplantation?", the server sends the following prompt sentence to the generation AI model:

[1937] User's question: What are the advantages and disadvantages of two-stage transplantation?

[1938] Answer:

[1939] Based on this prompt sentence, the generation AI model generates an appropriate response and provides it to the user. As a result, the user can obtain quick and accurate information.

[1940] The flow of the specific process in Application Example 3 will be described with reference to FIG. 16.

[1941] Step 1:

[1942] The user accesses the system using a smartphone and makes an inquiry in chat format.

[1943] Input: User's question (e.g., "What are the advantages and disadvantages of two-stage transplantation?")

[1944] Output: The content of the user's question is sent to the server.

[1945] Specific operation: The user opens the chat application on the smartphone, enters the question, and presses the send button.

[1946] Step 2:

[1947] The server receives the user's question and analyzes the content.

[1948] Input: The content of the user's question

[1949] Output: Analysis result of the question content (e.g., "Question about two-stage transplantation")

[1950] Specific operation: The server analyzes the received text data with a natural language processing algorithm to identify the intention of the question.

[1951] Step 3:

[1952] The server connects to the database and searches for relevant information.

[1953] Input: Analysis result of the question content

[1954] Output: Information retrieved from the database (e.g., "Information about the advantages and disadvantages of two-stage transplantation")

[1955] Specific operation: The server sends a query to the SQLite database and retrieves the relevant information.

[1956] Step 4:

[1957] The server generates a response based on the information retrieved from the database.

[1958] Input: Information retrieved from the database

[1959] Output: Response content to the user (e.g., "The advantages of two-stage transplantation are..., and the disadvantages are...")

[1960] Specific operation: The server formats the retrieved information into text format and generates a response for sending to the user.

[1961] Step 5:

[1962] The server uses the generated AI model to generate an appropriate response to the user's question.

[1963] Input: Content of the user's question

[1964] Output: Response content by the generated AI model (e.g., "The advantages and disadvantages of two-stage transplantation are as follows...")

[1965] Specific operation: The server sends the prompt text to the OpenAI API and receives the generated response.

[1966] Step 6:

[1967] The server sends the generated response to the user.

[1968] Input: Generated response content

[1969] Output: Response message displayed on the user's smartphone

[1970] Specific operation: The server sends the generated response to the user through the chat application and is displayed on the user's smartphone.

[1971] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion specific model 59 and perform specific processing using the user's emotion.

[1972] "Form Example 1"

[1973] As an embodiment of the present invention, there is a infertility treatment information providing system combined with an emotion engine for recognizing the user's emotion. When the user makes an inquiry to the system, this system has the emotion engine recognize the user's emotion. The emotion engine analyzes the emotion from the user's text input or voice input, and the system uses the result. For example, when the user shows an anxious emotion, the system recognizes the emotion and provides information to soothe the anxiety.

[1974] "Form Example 2"

[1975] Also, as another embodiment of the present invention, there is a system in which the emotion engine provides information regardi...

Claims

1. A system for providing infertility treatment information, comprising: means for referring to a database including past treatment records, statistical information, and information disclosure at research institutions; means for obtaining information from the database in response to an inquiry regarding infertility treatment information from a user; means for recognizing the user's emotion using an emotion engine that analyzes emotion from the user's text input or voice input; means for creating a prompt sentence instructing to provide information on infertility treatment based on the obtained information using the inquiry regarding infertility treatment information from the user, and transmitting the prompt sentence to a generation AI model; means for receiving a response from the generation AI model; means for generating a response suitable for the user based on the recognized emotion and the response from the generation AI model; means for providing the generated response suitable for the user to the user in a chat format; comprising a system.

2. The inquiry regarding infertility treatment information from the user is an inquiry regarding a specific infertility treatment method, and the transmitting means creates a prompt sentence instructing to provide information on the infertility treatment including the advantages and disadvantages of the specific infertility treatment method, and transmits the prompt sentence to the generation AI model. The system according to claim 1.

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