Program, information processing device, and method

Abstract

To provide non-invasive and inexpensive digital biomarkers. [Solution] The server of the disease state estimation system stores a database containing data about the user, and as a function, it repeatedly executes the following steps at predetermined intervals for a predetermined number of times: acquiring user identification data (S101), presenting predetermined questions to the user to visualize the state of a predetermined disease (S102), receiving input of answers to the questions from the user (S103), and storing answer data indicating the content of the received answers in the database linked to the user identification data (S104). After a predetermined number of times, it executes the following steps: acquiring answer data stored in the database for a predetermined number of times or more, estimating a predetermined disease state based on the answer data for a predetermined number of times or more, and outputting the estimated result of the predetermined disease state.

Description

Technical Field

[0006] , , ,

[0005] , , , ,

[0001] The present disclosure relates to a program, an information processing apparatus, and a method.

Background Art

[0002] Conventionally, in order to diagnose diseases related to cognitive functions such as Alzheimer's disease (AD), the cognitive functions of patients have been diagnosed.

[0003] Patent Document 1 discloses a technique for displaying a prediction curve for predicting changes in cognitive function by having a person answer questions related to cognitive function such as the Mini-Mental State Examination (hereinafter referred to as "MMSE").

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] By the way, Alzheimer's disease is a neurodegenerative disease characterized by the accumulation of amyloid-β (Aβ) and tau protein from before the onset of symptoms, and the importance of intervention from before the onset of symptoms (preclinical stage) has been emphasized. Also, as a treatment method for Alzheimer's disease, it has been clarified that Aβ removal therapy is effective. However, for the evaluation of lesions (tau pathology) caused by abnormal accumulation of Aβ and tau protein in the brain, PET examinations, cerebrospinal fluid examinations, etc. are used, but they are expensive and require specialized procedures.

[0006] <Furthermore, predictive technologies using blood biomarkers are attracting attention, and their effectiveness is being verified, but they require visits to medical institutions. Therefore, there is a need for the development of digital biomarkers that can be measured non-invasively and inexpensively in the daily lives of subjects.

[0007] Therefore, this disclosure describes a technology that enables the provision of non-invasive and inexpensively measurable digital biomarkers. [Means for solving the problem]

[0008] According to one embodiment of the present disclosure, a program is provided for a computer having a processor and memory to run and estimate the state of a user with respect to a predetermined disease. The memory stores a database containing data about the user. The program causes the processor to repeatedly perform the following steps at predetermined intervals for a predetermined number of times: acquire user identification data to identify the user; present the user with predetermined questions to visualize the state of the user with respect to a predetermined disease; receive input from the user for answers to the questions; store answer data indicating the content of the received answers in the database, linked to the user identification data; acquire answer data stored in the database for a predetermined number of times or more, linked to the user identification data relating to the user; estimate the state of the user with respect to a predetermined disease based on the answer data for a predetermined number of times or more; and output the estimation result for the state of the predetermined disease. [Effects of the Invention]

[0009] According to this disclosure, the system repeatedly presents the user with predetermined questions and accepts their answers at predetermined intervals for a predetermined number of times. Based on the answer data from a predetermined number of times, the system outputs an estimated state of a predetermined disease. Therefore, it becomes possible to estimate the state of a predetermined disease from the changes in the test results over a predetermined number of times. This makes it possible to provide a non-invasive and inexpensively measurable digital biomarker for a predetermined disease, such as Alzheimer's disease. [Brief explanation of the drawing]

[0010] [Figure 1] This is a block diagram showing the overall configuration of the disease state estimation system 1 according to an embodiment of the present disclosure. [Figure 2] Figure 1 is a block diagram showing the functional configuration of the terminal device 10. [Figure 3] This block diagram shows the functional configuration of server 20 in Figure 1. [Figure 4] Figure 3 shows an example of the data structure of the user database 2021. [Figure 5] Figure 3 shows an example of the data structure of the 2022 response database. [Figure 6] This graph shows an example of the trend in response results, which forms the basis of the estimated model 2023 in Figure 3. [Figure 7] This flowchart shows an example of the process for processing questions using the disease state estimation system 1. [Figure 8] This flowchart shows an example of the flow of disease estimation processing performed by disease state estimation system 1. [Figure 9] This figure shows an example of a question screen displayed on terminal device 10. [Figure 10] This figure shows an example of a response reception screen displayed on terminal device 10. [Figure 11] This figure shows another example of a screen for receiving responses that can be displayed on terminal device 10. [Figure 12] This figure shows an example of the estimated result screen displayed on terminal device 10. [Figure 13] This is a block diagram showing the basic hardware configuration of computer 90.

Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In all the drawings for describing the embodiments, common components are denoted by the same reference numerals, and repeated descriptions are omitted. Note that the following embodiments do not unduly limit the content of the present disclosure described in the claims. Also, not all of the components shown in the embodiments are essential components of the present disclosure. Also, each drawing is a schematic diagram and is not necessarily drawn precisely.

[0012] Also, in the following description, a "processor" is one or more processors. At least one processor is typically a microprocessor such as a CPU (Central Processing Unit), but may also be another type of processor such as a GPU (Graphics Processing Unit). At least one processor may be single-core or multi-core.

[0013] Also, at least one processor may be a processor in a broad sense such as a hardware circuit (e.g., FPGA (Field-Programmable Gate Array) or ASIC (Application Specific Integrated Circuit)) that performs part or all of the processing.

[0014] Also, in the following description, expressions such as "xxx database" may be used to describe information from which an output can be obtained for an input, but this information may be data of any structure or a learning model such as a neural network that generates an output for an input. Therefore, "xxx database" can be referred to as "xxx information".

[0015] In the following description, the configuration of the tables constituting each database is an example. One table may be divided into two or more tables, or all or part of two or more tables may be combined into one table.

[0016] In the following description, the "program" may be used as the subject for explaining the processing. However, since the program is executed by a processor to perform the defined processing while appropriately using a storage unit and / or an interface unit, etc., the subject of the processing may be the processor (or a device such as a controller having that processor).

[0017] The program may be installed in a device such as a computer, or may be, for example, on a program distribution server or a computer-readable (e.g., non-transitory) recording medium. Also, in the following description, two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0018] In the following description, an identification number is used as the identification information for various objects, but identification information of other types (e.g., an identifier including letters or symbols) may be adopted.

[0019] In the following description, when explaining without distinguishing between elements of the same type, reference signs (or common signs among the reference signs) are used, and when explaining while distinguishing between elements of the same type, the identification numbers (or reference signs) of the elements may be used.

[0020] In the following description, the control lines and information lines indicate those considered necessary for the explanation, and not necessarily all control lines and information lines on the product are shown. All components may be interconnected.

[0021] <Summary> The disease state estimation system described herein is described below. The disease state estimation system described herein is a system used to estimate the state of a user for a predetermined disease, such as dementia, and especially Alzheimer's disease. This disease state estimation system presents the user with predetermined questions, accepts the input of answers, and repeats this process at a predetermined number of times (e.g., 7 times) or more at predetermined intervals (e.g., 1 day). Based on the predetermined number of answer data received from the user, the system outputs an estimated result of the state of the predetermined disease. The disease state estimation system described herein is a system provided as a web service, such as SaaS (Software as a Service), via a cloud server, and is configured to allow users to access it through predetermined authentication.

[0022] As mentioned above, certain diseases, such as Alzheimer's disease, are neurodegenerative diseases characterized by the accumulation of amyloid-beta (Aβ) and tau protein even before the onset of symptoms, and the importance of intervention from the preclinical stage is emphasized. Furthermore, it has become clear that Aβ depletion therapy is effective as a treatment for Alzheimer's disease. However, PET scans, cerebrospinal fluid tests, and other tests used to evaluate lesions caused by the abnormal accumulation of Aβ and tau protein in the brain (tau pathology) are expensive and require specialized procedures. In addition, predictive technologies using blood biomarkers are attracting attention and their effectiveness is being verified, but a visit to a medical institution is required to use these technologies.

[0023] Therefore, the disease state estimation system described in this disclosure is configured to present a predetermined question to the user, accept the input of answers, repeat this process a predetermined number of times (e.g., 7 times) or more at predetermined intervals (e.g., 1 day), and output an estimation result for the state of a predetermined disease (e.g., Alzheimer's disease) based on the answer data received for a predetermined number of times or more.

[0024] Furthermore, the disease state estimation system described herein estimates the state of a given disease based on changes in response data received from a user a predetermined number of times or more, in accordance with the progression of the response count.

[0025] Furthermore, the disease state estimation system described herein estimates whether a person is in a state of a specific disease, specifically Alzheimer's disease, specifically in a normal state, a preclinical state, or a state of mild cognitive impairment.

[0026] With this configuration, the disease state estimation system described in this disclosure makes it possible to estimate the state of a given disease from changes in the results of a predetermined test over time. In particular, for Alzheimer's disease, it becomes possible to visualize and estimate subtle changes in cognitive function during the preclinical phase, when patients often do not seek medical attention. This makes it possible to provide a non-invasive and inexpensive digital biomarker for a given disease, such as Alzheimer's disease.

[0027] <First Embodiment> The disease state estimation system 1 according to an embodiment of this disclosure will be described below. In the following description, for example, when terminal device 10 accesses server 20, server 20 responds with information for terminal device 10 to generate a screen. Terminal device 10 generates and displays a screen based on the information received from server 20.

[0028] <1 Overall configuration of disease state estimation system 1> Figure 1 is a block diagram showing the overall configuration of the disease state estimation system 1 according to Embodiment 1 of this disclosure. As shown in Figure 1, the disease state estimation system 1 includes a plurality of terminal devices (in Figure 1, terminal devices 10A and 10B are shown; hereinafter, they may be collectively referred to as "terminal devices 10") and a server 20. The terminal devices 10 and the server 20 are connected to each other so as to be able to communicate with each other via a network 80. The network 80 is composed of a wired or wireless network. The network 80 includes, for example, 4G, 5G mobile communication systems, LTE (Long Term Evolution), and wireless networks that can connect to the internet via a predetermined access point (e.g., Wi-Fi®). When the network 80 is connected wirelessly, communication protocols include, for example, Z-Wave®, ZigBee®, and Bluetooth®. When the network is connected via a wired connection, the network also includes connections made directly by USB (Universal Serial Bus) cables, etc.

[0029] In this embodiment, server 20 is a web server (including a cloud server) and exchanges information with terminal device 10 via web pages. While terminal device 10 has a web browser installed for viewing web pages, a dedicated application for providing services from server 20 may also be installed and configured to allow viewing via this application. In this embodiment, the disease state estimation system 1 is described as a configuration where terminal device 10 and server 20 are connected via a network 80, but it may also be configured on-premise using various standalone computer devices.

[0030] Terminal device 10 is a device operated by each user. Here, a user is a person who uses terminal device 10 to receive an estimation of their condition for a disease such as Alzheimer's disease, which is a function of the disease state estimation system 1. This could be, for example, the person receiving the estimation (not limited to patients in medical institutions or residents of nursing care facilities), family members, or staff at medical institutions or nursing care facilities. Terminal device 10 can be implemented as a stationary PC (Personal Computer), a laptop PC (Note PC), etc. Alternatively, terminal device 10 may be a mobile device such as a tablet compatible with a mobile communication system or a smartphone.

[0031] The terminal device 10 is connected to the server 20 via the network 80 in a communicative manner. The terminal device 10 is connected to the network 80 by communicating with communication equipment such as a wireless base station 81 that supports communication standards such as 4G, 5G, and LTE (Long Term Evolution), and a wireless LAN router 82 that supports wireless LAN (Local Area Network) standards such as IEEE (Institute of Electrical and Electronics Engineers) 802.11. As shown as terminal device 10B in Figure 1, the terminal device 10 includes a communication interface 12, an input device 13, an output device 14, a memory 15, a storage unit 16, and a processor 19.

[0032] The communication interface 12 is an interface for inputting and outputting signals so that the terminal device 10 can communicate with external devices. The input device 13 is an input device (for example, a keyboard, touch panel, touchpad, mouse, or other pointing device) for receiving input operations from the user. The output device 14 is an output device (display, speaker, etc.) for presenting information to the user. The memory 15 is for temporarily storing programs and data processed by programs, etc., and is a volatile memory such as DRAM (Dynamic Random Access Memory). The storage unit 16 is a storage device for saving data, such as flash memory or an HDD (Hard Disk Drive). The processor 19 is hardware for executing the instruction set written in the program, and is composed of an arithmetic unit, registers, peripheral circuits, etc.

[0033] Server 20 is a device that estimates the state of a disease such as Alzheimer's disease and outputs the result. Server 20 acquires user identification data to identify the user, presents the user with predetermined questions and accepts input answers, and repeats this process at a predetermined time interval (e.g., 1 day) for a predetermined number of times (e.g., 7 times or more). Based on the answer data representing the answers for a predetermined number of times or more, Server 20 estimates the state of the predetermined disease. Furthermore, Server 20 outputs the estimation result.

[0034] Server 20 is a computer connected to network 80. Server 20 includes a communication interface 22, an input / output interface 23, memory 25, storage 26, and a processor 29.

[0035] Communication IF22 is an interface for inputting and outputting signals so that the server 20 can communicate with external devices. Input / Output IF23 functions as an interface to an input device for receiving input operations from the user and an output device for presenting information to the user. Memory 25 is for temporarily storing programs and data processed by programs, etc., and is a volatile memory such as DRAM (Dynamic Random Access Memory). Storage 26 is a storage device for saving data, such as flash memory or HDD (Hard Disk Drive). Processor 29 is hardware for executing the instruction set written in the program, and is composed of an arithmetic unit, registers, peripheral circuits, etc.

[0036] <1.1 Configuration of terminal device 10> Figure 2 is a block diagram showing the functional configuration of the terminal device 10 that constitutes the disease state estimation system 1 of Embodiment 1. As shown in Figure 2, the terminal device 10 includes a plurality of antennas (antenna 111, antenna 112), wireless communication units corresponding to each antenna (first wireless communication unit 121, second wireless communication unit 122), an operation reception unit 130 (including a keyboard 131 and a mouse 132), a display 140, a storage unit 150, and a control unit 160. The terminal device 10 also has functions and configurations not specifically shown in Figure 2 (for example, a battery for maintaining power, a power supply circuit for controlling the supply of power from the battery to each circuit, etc.). As shown in Figure 2, each block included in the terminal device 10 is electrically connected by a bus or the like.

[0037] Antenna 111 radiates signals emitted by terminal device 10 as radio waves. Antenna 111 also receives radio waves from space and provides the received signals to first wireless communication unit 121.

[0038] Antenna 112 radiates signals emitted by terminal device 10 as radio waves. Antenna 112 also receives radio waves from space and provides the received signals to second wireless communication unit 122.

[0039] The first wireless communication unit 121 performs modulation and demodulation processing, etc., for the terminal device 10 to transmit and receive signals via the antenna 111 in order to communicate with other wireless devices. The second wireless communication unit 122 performs modulation and demodulation processing, etc., for the terminal device 10 to transmit and receive signals via the antenna 112 in order to communicate with other wireless devices. The first wireless communication unit 121 and the second wireless communication unit 122 are a communication module that includes a tuner, an RSSI (Received Signal Strength Indicator) calculation circuit, a CRC (Cyclic Redundancy Check) calculation circuit, a high-frequency circuit, etc. The first wireless communication unit 121 and the second wireless communication unit 122 perform modulation, demodulation, and frequency conversion of the wireless signals transmitted and received by the terminal device 10, and provide the received signal to the control unit 160.

[0040] The operation reception unit 130 has a mechanism for receiving user input operations. Specifically, the operation reception unit 130 includes a keyboard 131 and a mouse 132. The operation reception unit 130 may also be configured as a touchscreen that detects the user's contact position with the touch panel, for example, by using a capacitive touch panel.

[0041] The keyboard 131 accepts user input operations from the terminal device 10. The keyboard 131 is a device for character input and outputs the input character information as an input signal to the control unit 160.

[0042] The mouse 132 accepts user input operations from the terminal device 10. The mouse 132 is a pointing device for selecting objects displayed on the display 140, and outputs the selected position information on the screen and information indicating that a button is pressed as input signals to the control unit 160.

[0043] The display 140 displays data such as images, videos, and text in accordance with the control of the control unit 160. The display 140 is implemented, for example, by an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display.

[0044] The storage unit 150 is composed of a memory 15, such as flash memory, and a storage unit 16, and stores data and programs used by the terminal device 10. In certain situations, the storage unit 150 stores user information 151.

[0045] User information 151 is information about a user who uses terminal device 10 to receive a disease state estimation for a disease such as Alzheimer's disease, which is a function of disease state estimation system 1. User information may include user identification data (user ID, etc.) to identify the user, the user's name, gender, date of birth, etc.

[0046] The control unit 160 is composed of, for example, a processor 19, and controls the operation of the terminal device 10 by reading a program stored in the memory unit 150 and executing the instructions contained in the program. The control unit 160 is, for example, an application that is pre-installed on the terminal device 10. By operating according to the program, the control unit 160 performs the functions of an input operation receiving unit 161, a transmitting / receiving unit 162, a notification control unit 163, and a data processing unit 164.

[0047] The input operation reception unit 161 processes input operations from the user to an input device such as a keyboard 131.

[0048] The transmitting / receiving unit 162 performs processing to enable the terminal device 10 to send and receive data with an external device such as a server 20 in accordance with a communication protocol.

[0049] The notification control unit 163 performs processing to present information to the user. The notification control unit 163 also performs processing such as displaying the display image on the display 140.

[0050] The data processing unit 164 performs calculations on the data received as input by the terminal device 10 according to the program and outputs the calculation results to memory or the like.

[0051] <1.2 Functional Configuration of Server 20> Figure 3 shows the functional configuration of the server 20 that constitutes the disease state estimation system 1 of Embodiment 1. As shown in Figure 3, the server 20 functions as a communication unit 201, a storage unit 202, and a control unit 203.

[0052] The communications unit 201 performs processing to enable the server 20 to communicate with external devices.

[0053] The memory unit 202 stores data and programs used by the server 20. The memory unit 202 stores the user database 2021, the response database 2022, the estimation model 2023, etc.

[0054] User Database 2021 is a database for storing and maintaining various data about users who receive disease status estimations, such as Alzheimer's disease, using the Disease Status Estimation System 1. User Database 2021 stores, for example, user identification data (such as user ID), the user's name, gender, and date of birth. Further details will be described later.

[0055] The Response Database 2022 is a database for storing and maintaining data on the responses received from users when they use the Disease State Estimation System 1, in response to predetermined questions. The Response Database 2022 stores response data that indicates the answers to questions, for example, linked to user identification data (such as a user ID) that identifies the user. Further details will be described later.

[0056] Estimation Model 2023 is a model that provides criteria for estimation, used when estimating the state of a disease such as Alzheimer's disease using the Disease State Estimation System 1. Estimation Model 2023 is a model based on past user response data and data showing the state of a given disease (Alzheimer's disease) for past users, and shows the trend of response data for each number of times the question and answer were repeated for past users. Further details will be described later.

[0057] The control unit 203 performs the functions shown in the following modules as the server 20's processor 29 processes according to the program: the receive control module 2031, the transmit control module 2032, the user identification data acquisition module 2033, the question presentation module 2034, the answer input reception module 2035, the answer data storage module 2036, the question execution control module 2037, the disease state estimation module 2038, and the estimation result output module 2039.

[0058] The receive control module 2031 controls the process by which the server 20 receives signals from external devices according to a communication protocol.

[0059] The transmission control module 2032 controls the process by which the server 20 transmits signals to external devices according to a communication protocol.

[0060] The user identification data acquisition module 2033 controls the process of acquiring user identification data that identifies a user, which is used to estimate the state of a disease such as Alzheimer's disease. The user, for example, operates the terminal device 10 to input user identification data (such as a user ID) and sends it to the server 20. The user identification data acquisition module 2033 receives the user identification data sent from the terminal device 10 via the communication unit 201.

[0061] The user identification data acquisition module 2033 may, for example, identify a user using biometric authentication such as facial recognition or fingerprint recognition, and acquire user identification data that recognizes the identified user and has been registered. Specifically, the terminal device 10 may be equipped with a camera function (not shown in the diagram), and the user may transmit a facial photograph of the user taken with the camera function to the server 20, and the user identification data acquisition module 2033 may identify the user by analyzing the received facial photograph data. Alternatively, the terminal device 10 may be equipped with a fingerprint reading function (not shown in the diagram), and the user may transmit a fingerprint of the user read with the fingerprint reading function to the server 20, and the user identification data acquisition module 2033 may identify the user by analyzing the received fingerprint data.

[0062] Furthermore, the user identification data acquisition module 2033 identifies the user based on the acquired user identification data and reads the user database 2021 to obtain various data about the user.

[0063] The question presentation module 2034 controls the process of presenting predetermined questions to a user identified by the user identification data acquisition module 2033, in order to visualize the state of a predetermined disease, such as Alzheimer's disease. For example, the question presentation module 2034 transmits data indicating the predetermined questions, specifically text data of the question sentences and image data related to the question sentences, to the terminal device 10 used by the user via the communication unit 201, and displays them on the display 140 of the terminal device 10.

[0064] In the Question Presentation Module 2034, for example, the following questions are presented to the user as predetermined questions (structured issues): • Face and name memory task: Participants are presented with a photograph (or illustration, etc.) of a person's face and name for a set period of time (approximately 10 seconds or so) and asked to memorize the person's face and name. • Furniture memory task: Participants are shown a photograph (or illustration, etc.) of a room with furniture arranged in it for a set period of time (about 10 seconds) and asked to remember what furniture is in that room. • Landscape Memory Task: A photograph (or illustration, etc.) of a landscape is presented for a set period of time (about 10 seconds) and the participant is asked to remember the season in which the landscape was depicted. • Processing speed test: This test involves presenting a table that associates multiple images (symbols, etc.) with numbers, and having the test-taker select the number corresponding to each image (symbol, etc.) from a set of options. It is used to estimate processing speed. • Delayed Recall Task: In this task, after a certain period of time (approximately 4-5 minutes) has elapsed since the face and name recall task, the furniture recall task, and the landscape recall task, the participant is presented with the same person's photograph, the room's photograph, and the landscape's photograph again. The participant is then asked to select the person's name, the furniture in the room, and the season of the landscape from the given options. This task is used to estimate memory ability.

[0065] The above examples of questions presented by Question Presentation Module 2034 are designed to estimate a state of Alzheimer's disease, but are not limited to this.

[0066] The response input receiving module 2035 controls the process of receiving input of answers to questions presented by the question presentation module 2034. For example, when a user operates the terminal device 10 to input an answer to a question presented by the question presentation module 2034, and the transmitting / receiving unit 162 of the terminal device 10 sends answer data indicating the answer to the server 20, the response input receiving module 2035 receives the user identification data sent from the terminal device 10 via the communication unit 201.

[0067] The response data storage module 2036 controls the process of storing response data, which indicates the content of the response received by the response input reception module 2035, in the response database 2022, linked to user identification data (user ID, etc.). For example, the response data storage module 2036 stores response data (such as the number selected by the user from the options) indicating the answer to a question presented by the question presentation module 2034 in the response database 2022, linked to the user ID for each question.

[0068] The question execution control module 2037 controls the processing performed by the user identification data acquisition module 2033, the question presentation module 2034, the answer input reception module 2035, and the answer data storage module 2036 to be executed repeatedly a predetermined number of times (e.g., 7 times) or more at predetermined intervals (e.g., 1 day). In the disease state estimation system 1 according to the embodiment of this disclosure, as described later, the state of a predetermined disease (Alzheimer's disease) is estimated based on answer data for a predetermined number of times or more, so the system controls the execution to be repeated in order to acquire the answer data for this purpose.

[0069] The question execution control module 2037 may, for example, prompt the user to accept input of an answer to a question again after a predetermined period (e.g., 1 day) has elapsed since the answer input reception module 2035 accepted input of an answer to a question. Specifically, when the question execution control module 2037 detects that a predetermined period (e.g., 1 day) has elapsed using a timer function, it may send notification data to the terminal device 10 used by the user via the communication unit 201 indicating that it will accept input of an answer to a question again, and display it as a push notification on the display 140 of the terminal device 10.

[0070] The disease state estimation module 2038 is associated with user identification data (such as a user ID) and controls the process of retrieving response data stored in the response database 2022 for a predetermined number of times (for example, 7 times) or more. For users who have answered questions a predetermined number of times (for example, 7 times) or more, the disease state estimation module 2038 reads the response database 2022 and retrieves the response data. The disease state estimation module 2038 may also retrieve the response data when the user operates the terminal device 10 and inputs a user ID, etc., or this process may be performed separately, for example, as a batch process.

[0071] Furthermore, the disease state estimation module 2038 controls the process of estimating the user's state for a given disease (e.g., Alzheimer's disease) based on a predetermined number of response data points (e.g., 7 times or more). The disease state estimation module 2038 estimates, for example, whether the user has a dementia state for a given disease, specifically Alzheimer's disease, specifically a normal state, a preclinical state, or a mild cognitive impairment state.

[0072] The disease state estimation module 2038 estimates the state of a given disease for a given user based on changes in response data over time, for example, in response data obtained a predetermined number of times or more. In the question presentation module 2034, the above-mentioned questions are asked in the same way (but not exactly the same) for repeated questions, so for a typical user, the results generally improve as they become accustomed to answering the questions. However, for users in the preclinical stage before the onset of symptoms for diseases such as Alzheimer's disease, or for users with mild cognitive impairment, the degree of improvement tends to be different, so the disease state estimation module 2038 estimates the state of a given disease for a given user based on changes in response data over time.

[0073] In this case, the disease state estimation module 2038 may estimate the user's state for a given disease using estimation model 2023, which is based on past user response data and data indicating the user's past state for a given disease (Alzheimer's disease). Since estimation model 2023 has criteria for the degree of improvement in results for repeatedly asked questions, set for normal state, preclinical state, and mild cognitive impairment state, the disease state estimation module 2038 estimates based on the criteria of estimation model 2023.

[0074] Furthermore, the disease state estimation module 2038 may estimate the state of a predetermined disease based on a predetermined score calculated from the response data. In this case, the response data storage module 2036 calculates a predetermined score based on the response data indicating the content of the response received by the response input reception module 2035, and stores the calculated predetermined score in the response database 2022, linked to user identification data (user ID, etc.). The predetermined score is a score (point) calculated by performing a predetermined operation on the user's response data, and is the sum of scores set according to the content of the responses to the above tasks and tests. This score may be weighted according to the above tasks and tests, or according to the user's attributes (age, gender, etc.).

[0075] The estimation result output module 2039 controls the process of outputting the estimated state results for a predetermined disease (e.g., Alzheimer's disease) by the disease state estimation module 2038. The estimation result output module 2039 transmits data indicating the estimated state results for the predetermined disease, specifically various data such as text data and numerical values ​​of the estimation results, to the terminal device 10 used by the user via the communication unit 201, and displays them on the display 140 of the terminal device 10. This allows the user to understand the estimated results for the predetermined disease by the disease state estimation system 1.

[0076] The estimation result output module 2039 may output a predetermined score for a given disease (e.g., Alzheimer's disease) calculated by the disease state estimation module 2038. The estimation result output module 2039 may also output the criteria set in the estimation model 2023 along with the score. This allows the user to objectively understand the estimation results for a given disease from the disease state estimation system 1.

[0077] <2 Data Structure> Figure 4 shows an example of the data structure of the user database 2021 in Figure 3.

[0078] As shown in Figure 4, each record in user database 2021 includes fields such as "User ID", "Username", "Gender", and "Date of Birth".

[0079] The item "User ID" is information (user identification data) that identifies each user whose condition for a given disease is estimated by the disease state estimation system 1.

[0080] The item "User Name" is the name of the user whose condition for a given disease is estimated by the disease state estimation system 1.

[0081] The item "Gender" is the gender of the user whose condition for a given disease is estimated by the disease state estimation system 1.

[0082] The item "Date of Birth" is the date of birth of the user whose condition for a given disease is estimated by the disease state estimation system 1.

[0083] The user identification data acquisition module 2033 of server 20 adds a record to the user database 2021 when a new user is registered in the disease state estimation system 1.

[0084] Figure 5 shows an example of the data structure of the response database 2022 in Figure 3.

[0085] As shown in Figure 5, each record in the response database 2022 includes the fields "User ID" and "Response Data Details," etc.

[0086] The "User ID" field is information (user identification data) that identifies each user whose condition for a given disease is estimated by the disease state estimation system 1, and corresponds to the "User ID" field in user database 2021.

[0087] The item "Detailed Response Data" is the response data stored in the response data storage module 2036 after the user has answered questions using the disease state estimation system 1. Specifically, it includes the item "Date of Implementation," the items "Question 1," "Question 2," "Question 3," etc., and the item "Score," etc.

[0088] The item "Implementation Date" is data for the date the user answered the questions using the disease status estimation system 1.

[0089] The items "Question 1," "Question 2," "Question 3," etc., contain the content of the response data provided by the user using the disease state estimation system 1 to answer the questions. The question presentation module 2034 presents multiple questions, and the response input reception module 2035 accepts the answers to each question. Therefore, the items "Question 1," "Question 2," "Question 3," etc., store the corresponding values ​​(numbers) for each of the multiple questions as response data.

[0090] The item "Score" is a predetermined score calculated by the disease state estimation module 2038 based on the response data obtained by the user using the disease state estimation system 1 to answer questions. As an example of a predetermined score, the item "Score" shown in Figure 5 stores the score when converted to a maximum of 100 points.

[0091] The user identification data acquisition module 2033 of server 20 adds a record to the response database 2022 when a new user is registered in the disease state estimation system 1. Additionally, the response data storage module 2036 of server 20 adds a record to the "Response Data Details" field in the response database 2022 for each date the response was taken, as the response input reception module 2035 receives the response data, and stores the response data linked to the "User ID" field (user identification data).

[0092] Figure 6 is a graph showing an example of the progression of response results, which forms the basis of the estimated model 2023 in Figure 3. The example graph in Figure 6 shows the relationship between the score calculated based on past user response data for questions and answers administered in the past, and the number of times the questions and answers (tests) were repeatedly administered. The vertical axis represents the score, and the horizontal axis represents the number of times the test was administered. Curve L1 in the graph in Figure 6 shows the progression of the user's normal state for Alzheimer's disease, curve L2 shows the progression of the user's state before the onset of symptoms (preclinical stage 1), and curve L3 shows the progression of the user's state before the onset of symptoms (preclinical stage 2).

[0093] As shown by curve L3 in Figure 6, when the user is in the preclinical stage 2 state, a significant difference in the score is observed from the first test compared to curves L1 and L2. In contrast, as shown by curve L2, when the user is in the preclinical stage 1 state, no significant difference in the score is observed from the first test compared to curve L1. Therefore, it is difficult to distinguish between a normal state and a pre-symptomatic state (preclinical stage 1) for Alzheimer's disease by performing such a test only once. However, as shown by curve L2, when the user is in a pre-symptomatic state (preclinical stage 1), a significant difference in the score is observed from the test results as the number of tests progresses compared to curve L1, making it possible to detect subtle changes in cognitive function and distinguish between a normal state and a pre-symptomatic state (preclinical stage 1). For this reason, the disease state estimation system 1 repeats the same test a predetermined number of times (e.g., 7 times) or more at predetermined intervals (e.g., 1 day). It has also been found that significant differences can be observed in cases where the user has mild cognitive impairment, as shown by curve L3 in Figure 6, but this will not be discussed in detail here.

[0094] The estimation model 2023 shown in Figure 6 may be composed of an estimation model that has been trained based on past user response data and data indicating the past user's status regarding a given disease (Alzheimer's disease). Estimation model 2023 may be composed of a machine learning model that has been trained using any machine learning algorithm (supervised machine learning, etc.), deep learning algorithm, neural network (e.g., Deep Neural Network (DNN)) model, etc. Furthermore, estimation model 2023 does not need to be a single training model, and may be implemented by switching between multiple independent training models for each task or test.

[0095] <3 operations> The following describes the question answering process and disease estimation process (method) by the disease state estimation system 1 according to the embodiment of this disclosure, with reference to Figures 7 and 8.

[0096] Figure 7 is a flowchart showing an example of the flow of question answer processing by the disease state estimation system 1. This process is controlled by the question execution control module 2037 of the server 20 and is executed repeatedly a predetermined number of times (e.g., 7 times) or more at predetermined intervals (e.g., 1 day).

[0097] In step S101, the user identification data acquisition module 2033 of the server 20 acquires user identification data that identifies a user, which is used to estimate the state of a predetermined disease. In step S101, the user identification data (user ID, etc.) may be acquired by user operation from the terminal device 10, by identifying the user through biometric authentication, or by reading the user database 2021.

[0098] In step S102, the question presentation module 2034 of the server 20 presents the user identified in step S101 with a set of questions to visualize the state of a predetermined disease, such as Alzheimer's disease. In step S102, for example, data indicating the predetermined questions, specifically text data of the questions and image data related to the questions, is transmitted via the communication unit 201 to the terminal device 10 used by the user and displayed on the display 140 of the terminal device 10.

[0099] In step S103, the response input receiving module 2035 of the server 20 receives the input of the response to the question presented in step S102. In step S103, for example, the user operates the terminal device 10 to input the response to the question presented in step S102, and the transmitting / receiving unit 162 of the terminal device 10 sends the response data to the server 20. The server 20 receives the user identification data sent from the terminal device 10 via the communication unit 201.

[0100] In step S104, the response data storage module 2036 of the server 20 stores the response data, which indicates the content of the response received in step S103, in the response database 2022, linked to user identification data (user ID, etc.). In step S104, for example, the response data (number selected by the user from the options, etc.) indicating the answer to the question presented in step S102 is stored in the response database 2022 for each question, linked to the user ID.

[0101] As described above, the disease state estimation system 1 acquires user identification data to identify a user, presents the identified user with predetermined questions to visualize their condition, for example, regarding Alzheimer's disease, accepts their answers, and stores the answer data in the answer database 2022, linked to the user ID. This process is repeated at least seven times at predetermined intervals (e.g., one day).

[0102] Figure 8 is a flowchart showing an example of the flow of disease estimation processing performed by the disease state estimation system 1.

[0103] In step S201, the user identification data acquisition module 2033 of the server 20 acquires user identification data that identifies the user, which is then used to estimate the state of a predetermined disease. This is the same process as in step S101. Note that the disease estimation process may be performed at a different time than the user's response, in which case the process in step S201 may not be performed.

[0104] In step S202, the disease state estimation module 2038 of server 20 is associated with user identification data (user ID, etc.) related to the user and retrieves response data stored in the response database 2022 for a predetermined number of times (for example, 7 times) or more. In step S202, for example, for users who have answered questions a predetermined number of times (for example, 7 times) or more, the response database 2022 is read and response data is retrieved.

[0105] In step S203, the disease state estimation module 2038 of the server 20 estimates the user's state for a given disease (e.g., Alzheimer's disease) based on a predetermined number of response data (e.g., 7 times) obtained in step S202. In step S203, for example, it estimates whether the user has a dementia state for the given disease, specifically Alzheimer's disease, specifically a normal state, a preclinical state, or a state of mild cognitive impairment.

[0106] In step S204, the estimation result output module 2039 of the server 20 outputs the estimated state result for the predetermined disease (e.g., Alzheimer's disease) estimated in step S203. In step S204, for example, data showing the estimated state result for the predetermined disease, specifically various data such as text data and numerical values ​​of the estimation result, is transmitted via the communication unit 201 to the terminal device 10 used by the user and displayed on the display 140 of the terminal device 10.

[0107] As described above, the disease state estimation system 1 estimates and outputs the user's state for a predetermined disease (e.g., Alzheimer's disease) based on a predetermined number of response data (e.g., 7 times or more). This allows the user to understand the estimation results for a predetermined disease provided by the disease state estimation system 1 by using the disease state estimation system described herein.

[0108] <4. Screen Example> The following describes examples of the question screen, the answer reception screen, and the estimation result screen displayed on the terminal device 10 by the disease state estimation system 1, with reference to Figures 9 to 12.

[0109] Figure 9 shows an example of a question screen displayed on the terminal device 10. The example screen in Figure 9 shows a screen displaying a face and name memory task, which is an example of a question (instruction) presented by the question presentation module 2034 of the server 20. This corresponds to step S102 in Figure 7.

[0110] As shown in Figure 9, the display 140 of the terminal device 10 shows a question display screen 1411. This question display screen 1411 shows a username display field 1412 that displays the name of the user receiving the question (instruction), and a question display field 1413 that displays a face and name memory task as an example of a question (instruction). Following the contents of this question display screen 1411, the user performs a test to visualize the state of a predetermined disease, such as Alzheimer's disease.

[0111] Figure 10 shows an example of a response reception screen displayed on terminal device 10. The example screen in Figure 10 shows a screen displaying a delayed recall task for a face and name memory task, which is an example of a question (answer) presented by the question presentation module 2034 of server 20. This corresponds to step S103 in Figure 7.

[0112] As shown in Figure 10, the display 140 of the terminal device 10 shows a question display screen 1421. This question display screen 1421 shows a username display field 1422 that displays the name of the user who will receive the question (answer), a question display field 1423 that displays a delayed recall task for a face and name memory task as an example of a question, and an answer input field 1424 for entering the answer to the question.

[0113] The question display screen 1421 shown in Figure 10 is displayed after a certain period of time (approximately 4-5 minutes) has elapsed since the display of the question display screen 1411 shown in Figure 9. This question display screen 1421 tests whether the user can correctly answer the question in the question display field 1423 shown in Figure 10, using the name displayed in the question display field 1413 shown in Figure 9. The user enters the correct (or what they believe to be correct) name by selecting it from the list of hiragana characters displayed in the answer input field 1424. Note that this question display screen 1421 may be displayed after several questions or tests have been conducted in between.

[0114] Figure 11 shows another example of a screen for receiving responses displayed on the terminal device 10. The example screen in Figure 11 shows a screen displaying a delayed recall task for a face and name memory task, which is an example of a question (answer) presented by the question presentation module 2034 of the server 20. This corresponds to step S103 in Figure 7.

[0115] As shown in Figure 11, the display 140 of the terminal device 10 shows a question display screen 1431. This question display screen 1431 shows a username display field 1432 that displays the username of the user receiving the question (answer), a question display field 1433 that displays a delayed recall task for a face and name memory task as an example of a question, and an option input field 1434 for selecting an answer to the question.

[0116] The question display screen 1431 shown in Figure 11 is displayed after a certain period of time (approximately 4-5 minutes) has elapsed since the display of the question display screen 1411 shown in Figure 9. This question display screen 1431 tests whether the user can correctly answer the question in the question display field 1433 shown in Figure 11, using the name displayed in the question display field 1413 shown in Figure 9. The user selects and enters the correct (or what they believe to be the correct) option from the option input field 1434. Note that this question display screen 1431 may be displayed after several questions or tests have been conducted in between. Here, the display and input of the question display screen 1421 shown in Figure 10 takes place before the display and input of the question display screen 1431 shown in Figure 11 takes place. However, while the question display screen 1421 shown in Figure 10 and the question display screen 1431 shown in Figure 11 represent different ways of answering the same question (instruction), and the question display screen 1421 shown in Figure 10 is more difficult, users may choose to use them depending on the user's response status, test results, etc.

[0117] Figure 12 shows an example of a screen displaying the estimation results on the terminal device 10. The example screen in Figure 12 shows a screen displaying the estimated state of a predetermined disease (e.g., Alzheimer's disease) output by the estimation result output module 2039 of the server 20. This corresponds to step S204 in Figure 8.

[0118] As shown in Figure 12, the display 140 of the terminal device 10 shows an estimated result display screen 1441. This estimated result display screen 1441 shows a user name display field 1442 that displays the user name of the user for whom the estimated result is based, and a result display field 1443 that displays the estimated result. The result display field 1443 displays a predetermined score for Alzheimer's disease for each date the test was conducted. Through this estimated result display screen 1441, the user can understand the estimated result for a predetermined disease (Alzheimer's disease) by the disease state estimation system 1.

[0119] <Summary> As described above, according to this embodiment, user identification data is acquired to identify a user, and a predetermined question is presented to the identified user to visualize their condition, for example, regarding Alzheimer's disease. The user is asked to input their answers, and the answer data is linked to the user ID and stored in a database. This process is repeated a predetermined number of times (e.g., 7 times) or more at predetermined intervals (e.g., 1 day). Based on the changes in the answer data corresponding to the number of repetitions in the answer data for the predetermined number of repetitions (e.g., 7 times), the system estimates and outputs the user's condition regarding a predetermined disease (e.g., Alzheimer's disease). Therefore, by using the disease state estimation system according to this disclosure, it becomes possible to estimate the condition regarding a predetermined disease from the changes in predetermined test results over time. In particular, for Alzheimer's disease, it becomes possible to visualize and estimate subtle changes in cognitive function in the preclinical stage, when patients often have not yet visited a medical institution. At this time, even within the same preclinical stage, it is possible to visualize and estimate subtle changes in cognitive function due to differences in stages. This makes it possible to provide non-invasive and inexpensively measurable digital biomarkers for specific diseases, such as Alzheimer's disease.

[0120] Furthermore, according to this embodiment, it is possible to estimate the state of Alzheimer's disease, specifically whether it is a normal state, a preclinical state, or a state of mild cognitive impairment. This makes it possible to provide an inexpensive, measurable digital biomarker for Alzheimer's disease, particularly a digital biomarker that can visualize the preclinical state.

[0121] <Basic Computer Hardware Configuration> Figure 13 is a block diagram showing the basic hardware configuration of computer 90. Computer 90 comprises at least a processor 901, main memory 902, auxiliary memory 903, and a communication interface IF991. These are electrically connected to each other by a communication bus 921.

[0122] The processor 901 is hardware for executing the instruction set written in a program. The processor 901 consists of an arithmetic unit, registers, peripheral circuits, etc.

[0123] Main memory 902 is used to temporarily store programs and data processed by programs, etc. For example, it is a volatile memory such as DRAM (Dynamic Random Access Memory).

[0124] Auxiliary storage device 903 refers to a storage device for saving data and programs. Examples include flash memory, HDD (Hard Disc Drive), magneto-optical disk, CD-ROM, DVD-ROM, and semiconductor memory.

[0125] The IF991 communication interface is an interface for inputting and outputting signals for communication with other computers via a network using wired or wireless communication standards. A network consists of various mobile communication systems, such as the internet, LANs, and wireless base stations. For example, a network includes 3G, 4G, and 5G mobile communication systems, LTE (Long Term Evolution), and wireless networks that can connect to the internet via designated access points (e.g., Wi-Fi®). When connecting wirelessly, communication protocols include, for example, Z-Wave®, ZigBee®, and Bluetooth®. When connecting via a wired connection, the network also includes connections made directly via USB (Universal Serial Bus) cables, etc.

[0126] Furthermore, by distributing all or part of each hardware configuration across multiple computers 90 and connecting them to each other via a network, a computer 90 can be virtually realized. Thus, the concept of computer 90 includes not only a computer 90 housed in a single enclosure or case, but also a virtualized computer system.

[0127] <Basic Functional Configuration of Computer 90> The functional configuration of the computer realized by the basic hardware configuration of computer 90 (Figure 13) is described below. The computer comprises at least one functional unit: a control unit, a memory unit, and a communication unit.

[0128] Furthermore, the functional units of computer 90 can also be realized by distributing all or part of each functional unit across multiple computers 90 interconnected via a network. The concept of computer 90 includes not only a single computer 90 but also a virtualized computer system.

[0129] The control unit is realized when the processor 901 reads various programs stored in the auxiliary storage device 903, loads them into the main memory device 902, and executes processing according to those programs. The control unit can realize various functional units that perform information processing depending on the type of program. In this way, the computer is realized as an information processing device that performs information processing.

[0130] The memory unit is implemented by the main memory 902 and the auxiliary memory 903. The memory unit stores data, various programs, and various databases. The processor 901 can also reserve memory areas corresponding to the memory unit in the main memory 902 or the auxiliary memory 903 according to the program. The control unit can also cause the processor 901 to perform operations such as adding, updating, and deleting data stored in the memory unit according to the various programs.

[0131] A database, specifically a relational database, is used to manage and link together tabular data sets called masters, which are structurally defined by rows and columns. In a database, tables are called tables, masters are called masters, the columns of tables are called columns, and the rows of tables are called records. In a relational database, relationships can be established and linked between tables and masters. Typically, each table and master has a primary key column to uniquely identify records, but setting a primary key column is not mandatory. The control unit can instruct the processor 901 to add, delete, or update records in specific tables and masters stored in the memory unit, according to various programs. Furthermore, by storing data, various programs, and various databases in the memory unit, the information processing device and information processing system related to this disclosure can be considered to have been manufactured.

[0132] Furthermore, the databases and masters in this disclosure may include any data structures (lists, dictionaries, associative arrays, objects, etc.) in which information is structurally defined. Data structures also include data that can be considered as data structures by combining data with functions, classes, methods, etc., written in any programming language.

[0133] The communication unit is implemented by the communication IF991. The communication unit provides the functionality to communicate with other computers 90 via the network. The communication unit can receive information transmitted from other computers 90 and input it to the control unit. The control unit can cause the processor 901 to perform information processing on the received information according to various programs. The communication unit can also transmit information output from the control unit to other computers 90.

[0134] Furthermore, each of the above-mentioned configurations, functions, processing units, processing means, etc., may be implemented in hardware, either partially or entirely, by designing them as integrated circuits, for example. The present invention can also be implemented by software program code that realizes the functions of the embodiment. In this case, a storage medium on which the program code is recorded is provided to a computer, and the processor of that computer reads the program code stored in the storage medium. In this case, the program code read from the storage medium itself realizes the functions of the embodiment described above, and the program code itself and the storage medium on which it is stored constitute the present invention. Examples of storage media used to supply such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, SSDs, optical disks, magneto-optical disks, CD-Rs, magnetic tapes, non-volatile memory cards, ROMs, and the like.

[0135] Furthermore, the program code that implements the functions described in this embodiment can be implemented in a wide range of programming or scripting languages, such as assembler, C / C++, Perl, Shell, PHP, and Java (registered trademark).

[0136] Furthermore, the program code for the software that implements the functions of the embodiment may be distributed via a network and stored in a storage means such as a computer's hard disk or memory, or in a storage medium such as a CD-RW or CD-R, and the computer's processor may read and execute the program code stored in the storage means or storage medium.

[0137] The functions realized by the components described herein may be implemented in a circuit or processing circuitry, including general-purpose processors, application-specific processors, integrated circuits, ASICs (Application Specific Integrated Circuits), CPUs (A Central Processing Units), conventional circuits, and / or combinations thereof, programmed to realize the functions described herein. A processor is considered to be a circuit or processing circuitry, including transistors and other circuits. A processor may be a programmed processor that executes a program stored in memory. In this specification, circuitry, unit, and means are hardware programmed to perform or execute the functions described herein. Such hardware may be any hardware disclosed herein, or any hardware known to be programmed to perform or execute the functions described herein. If the hardware is a processor that is considered to be a type of circuitry, then the circuitry, means, or unit is a combination of hardware and software used to constitute the hardware and / or processor.

[0138] While embodiments relating to this disclosure have been described above, these can be implemented in various other forms and can be carried out with various omissions, substitutions, and modifications. These embodiments and variations, as well as those with omissions, substitutions, and modifications, are included within the technical scope of the claims and their equivalents.

[0139] <Note> The details described in each of the above embodiments are noted below.

[0140] (Note 1) A program to be executed on a computer equipped with a processor 29 and memory 25 to estimate the state of a predetermined disease relating to a user, wherein the memory 25 stores a database containing data relating to the user (2021), and the program causes the processor 29 to repeatedly perform the following steps at predetermined intervals for a predetermined number of times or more: acquiring user identification data to identify the user (S101); presenting the user with predetermined questions to visualize the state relating to the predetermined disease (S102); receiving input from the user for answers to the questions (S103); storing answer data indicating the content of the received answers in the database linked to the user identification data (S104); acquiring answer data stored in the database for a predetermined number of times or more linked to the user identification data relating to the user (S202); estimating the state relating to the predetermined disease for the user based on the answer data for a predetermined number of times or more (S203); and outputting the estimation result for the state relating to the predetermined disease (S204).

[0141] (Note 2) The program described in (Note 1), which, in the step of estimating the state of a user for a predetermined disease, estimates the state of the user for a predetermined disease based on the changes in the response data over time in response data for a predetermined number of times or more.

[0142] (Note 3) The program described in (Note 2), which, in the step of estimating the user's condition for a given disease, uses an estimation model based on past user response data and data indicating the user's condition for a given disease in the past to estimate the user's condition for a given disease.

[0143] (Note 4) The program further includes the steps of: calculating a predetermined score based on response data showing the content of the received responses; storing the response data in a database; storing the calculated predetermined score in the database linked to user identification data; and estimating the user's condition for a predetermined disease; and estimating the user's condition for a predetermined disease based on the predetermined score calculated a predetermined number of times or more, as described in any of (Note 1) to (Note 3).

[0144] (Note 5) The program described in (Note 4) that, in the step of outputting the estimation results, outputs the calculated predetermined score and the estimated result of the state of the predetermined disease.

[0145] (Appendix 6) The program described in (Appendix 5) which, in the step of outputting the estimation result, outputs criteria for estimating the state of a given disease.

[0146] (Note 7) The program further includes the step of prompting the user to input an answer to a question again after a predetermined period has elapsed since the input of an answer to a question was received, as described in (Note 1).

[0147] (Note 8) The program described in (Note 1) for estimating the state of dementia in the user in the step of estimating the state of a specified disease in the user.

[0148] (Note 9) The program described in (Note 8) that, in the step of estimating the user's condition for a given disease, estimates whether the user is in a normal state, a pre-symptomatic state, or a state of mild cognitive impairment.

[0149] (Note 10) An information processing device comprising a control unit 203 and a memory 25 (storage unit 202), which estimates the state of a predetermined disease relating to a user, wherein the memory 25 stores a database storing data relating to the user (2021), and the control unit 203 repeatedly performs the following steps at predetermined intervals for a predetermined number of times or more: acquiring user identification data to identify the user (S101); presenting the user with predetermined questions to visualize the state relating to the predetermined disease (S102); receiving input of answers to the questions from the user (S103); storing answer data indicating the content of the received answers in the database linked to the user identification data (S104); acquiring answer data linked to the user identification data relating to the user for a predetermined number of times or more (S202); estimating the state relating to the predetermined disease for the user based on the answer data for a predetermined number of times or more (S203); and outputting the estimation result for the state relating to the predetermined disease (S204).

[0150] (Note 11) A method for estimating the state of a predetermined disease relating to a user, which is executed by a computer comprising a processor 29 and a memory 25, wherein the memory 25 stores a database containing data relating to the user (2021), and the method is to have the processor 29 repeatedly perform the following steps at predetermined intervals for a predetermined number of times: acquiring user identification data to identify the user (S101); presenting the user with predetermined questions to visualize the state relating to the predetermined disease (S102); receiving input of answers to the questions from the user (S103); storing answer data indicating the content of the received answers in the database linked to the user identification data (S104); acquiring answer data stored in the database linked to the user identification data relating to the user for a predetermined number of times or more (S202); estimating the state relating to the predetermined disease for the user based on the answer data for a predetermined number of times or more (S203); and outputting the estimation result for the state relating to the predetermined disease (S204). [Explanation of Symbols]

[0151] 1: Disease status estimation system 10: Terminal device 10A: Terminal device 10B: Terminal device 13: Input device 14: Output device 15: Memory 16: Storage section 19: Processor 20: Server 25: Memory 26: Storage 29: Processor 80: Network 81: Wireless base station 82: Wireless LAN router 90: Computer 111: Antenna 112: Antenna 121: First Radio Communication Unit 122: Second Wireless Communication Section 130: Operation Reception Section 131: Keyboard 132: Mouse 140: Display 150: Storage section 151: User Information 160: Control Unit 161: Input operation reception unit 162: Transceiver Unit 163: Notification Control Unit 164: Data Processing Unit 201: Communications Department 202: Storage section 203: Control Unit 901: Processor 902: Main memory 903 :Auxiliary storage device 921: Communications bus 2021: User Database 2022: Answer Database 2023: Estimated model 2031: Receiver control module 2032: Transmit control module 2033: User Identification Data Acquisition Module 2034: Question Presentation Module 2035: Response Input Reception Module 2036: Answer data storage module 2037: Question Execution Control Module 2038: Disease State Estimation Module 2039: Estimation Result Output Module

Claims

1. A program to be executed on a computer equipped with a processor and memory, for estimating the state of a user with respect to a predetermined disease relating to cognitive function, The memory stores a database containing data about the user, The program is provided to the processor: The steps include: obtaining user identification data to identify the user; The steps include presenting the user with predetermined questions to visualize the state of a predetermined disease related to cognitive function, The steps include receiving input from the user regarding the answer to the question, The steps of storing the response data, which shows the content of the received response, in the database linked to the user identification data, are repeated a predetermined number of times or more each day. The steps include: acquiring the response data stored in the database for a predetermined number of times or more, which is linked to the user identification data relating to the user; A step of estimating which of several states indicating the state of a predetermined cognitive function disorder the user falls into, based on the changes in the response data over time for a predetermined number of times or more; A program that performs the step of outputting an estimated result of the state of the aforementioned predetermined disease.

2. The program according to claim 1, which of the following states applies to the user's state regarding the predetermined disease: a normal state or a preclinical state, based on changes in response to the number of responses of the predetermined number of times or more of the response data.

3. The program according to claim 2, wherein in the step of estimating the state of a user regarding the predetermined disease, the program estimates the state of a user regarding the predetermined disease using an estimation model based on the user's past response data and data indicating the user's past state regarding the predetermined disease.

4. The aforementioned program, further, Based on the response data showing the content of the received response, the system executes a step to calculate a predetermined score. In the step of storing the response data in the database, the calculated predetermined score is stored in the database linked to the user identification data. The program according to any one of claims 1 to 3, wherein in the step of estimating the state of the user with respect to the predetermined disease, the program estimates the state of the user with respect to the predetermined disease based on the predetermined score calculated for a predetermined number of times or more.

5. The program according to claim 4, wherein in the step of outputting the estimation result, the calculated predetermined score and the estimated result of the state of the predetermined disease are output.

6. The program according to claim 5, wherein in the step of outputting the estimation result, a criterion for estimating the state of the predetermined disease is output.

7. The aforementioned program, further, The program according to claim 1, which causes the user to perform a step of prompting the user to input an answer to the question again after a predetermined period has elapsed since the user provided an answer to the question.

8. The program according to claim 1, wherein, in the step of estimating the state of the user with respect to the predetermined disease, the program estimates the state of dementia for the user.

9. The program according to claim 8, wherein, in the step of estimating the state of the user with respect to the predetermined disease, the program estimates whether the user is in a normal state, a state before the onset of symptoms, or a state of mild cognitive impairment.

10. An information processing device comprising a control unit and a memory, which estimates the state of a user regarding a predetermined disease relating to cognitive function, The memory stores a database containing data about the user, The control unit, The steps include: obtaining user identification data to identify the user; The steps include presenting the user with predetermined questions to visualize the state of a predetermined disease related to cognitive function, The steps include receiving input from the user regarding the answer to the question, The steps of storing the response data, which shows the content of the received response, in the database linked to the user identification data, are repeated a predetermined number of times or more each day. The steps include: acquiring the response data stored in the database for a predetermined number of times or more, which is linked to the user identification data relating to the user; A step of estimating which of several states indicating the state of a predetermined cognitive function disorder the user falls into, based on the changes in the response data over time for a predetermined number of times or more; An information processing device that performs the step of outputting an estimated result of the state of the aforementioned predetermined disease.

11. A method for estimating the state of a user with respect to a predetermined disease relating to cognitive function, which is executed by a computer comprising a processor and memory, The memory stores a database containing data about the user, The above method involves the processor, The steps include: obtaining user identification data to identify the user; The steps include presenting the user with predetermined questions to visualize the state of a predetermined disease related to cognitive function, The steps include receiving input from the user regarding the answer to the question, The steps of storing the response data, which shows the content of the received response, in the database linked to the user identification data, are repeated a predetermined number of times or more each day. The steps include: acquiring the response data stored in the database for a predetermined number of times or more, which is linked to the user identification data relating to the user; A step of estimating which of several states indicating the state of a predetermined cognitive function disorder the user falls into, based on the changes in the response data over time for a predetermined number of times or more; A method for performing the step of outputting an estimated result of the state of the aforementioned predetermined disease.

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