System and method for supporting examiners who conduct psychological tests

Abstract

To support an examiner so that the examiner can accurately and efficiently examine the psychology of a subject through a baum test.SOLUTION: A aum analysis model being a machine learning model for outputting an index related to a baum test with a baum image as an input is prepared. One or more indexes are acquired about a baum drawn by a subject by inputting an object image being a baum image drawn by the subject of a baum test to the baum analysis test. An examiner support system displays information on one or more selection indexes being one or more indexes among the acquired one or more indexes to an examiner of the baum test.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention generally relates to novel techniques for assisting testers in administering psychological tests. [Background technology]

[0002] In recent years, the number of patients suffering from mental illnesses has increased (for example, in Japan, the number exceeds 4 million). Depression, in particular, has become a social issue, but diagnosis and treatment are often not linked. Although a diagnostic standard known as the DMS-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th Edition) has been established, the causes of depression can vary widely, depending on the patient's personality, background, and environment, and may be constitutional or interpersonal. Therefore, even if a diagnosis is made, treatment is often difficult.

[0003] In order to provide truly appropriate treatment to patients, it is necessary to understand the patient from various perspectives, and for this purpose, psychological testing is usually carried out. The Baumtest is one such psychological testing method. Known techniques related to the Baumtest include the technique disclosed in Patent Document 1, for example. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 5629395 Summary of the Invention [Problem to be solved by the invention]

[0005] The technology disclosed in Patent Document 1 aims to create warm comments that are easily accepted by the subject (see paragraph 0008), and to achieve this aim, comments for the subject that correspond to the tree drawings drawn by the subject in the Baum test are mechanically created (paragraph 0056).

[0006] However, machine-generated comments may be invasive to the subject's mind depending on the degree of the subject's mental illness and the subject's mental state at the time, so it is not advisable to show machine-generated comments to the subject as they are.

[0007] Furthermore, for the comments to be appropriate, it is necessary to accurately interpret the Baum (which means "tree" in German) drawn by the subject. However, it is difficult to automatically interpret the Baum accurately enough to link it to treatment.

[0008] For the reasons mentioned above, it is difficult and undesirable to perform the Baumtest mechanically. The Baumtest should be performed by an examiner. Specifically, it is necessary for the examiner to face the subject during the Baumtest.

[0009] However, the time available for the Baumtest is limited, and the level of skill in the Baumtest varies depending on the examiner.

[0010] Furthermore, compared to the number of potential subjects for the Baumtest (typically those who suffer from or are at risk of suffering from a mental illness), there are few examiners who can administer the Baumtest. Psychologists are the main examiners, but with the recent rise in verbal approaches, primarily cognitive behavioral therapy, there are not necessarily many psychologists who are skilled in non-verbal approaches such as the Baumtest.

[0011] Therefore, an object of the present invention is to support examiners so that they can accurately and efficiently examine the psychology of subjects through the Baum test. [Means for solving the problem]

[0012] A Baum analysis model is prepared, which is a machine learning model that receives an image of a Baum test as input and outputs indicators related to the Baum test. The examiner support system acquires one or more indicators for the Baum test drawn by the examinee by inputting a target image, which is an image of a Baum test drawn by the examinee, into the Baum analysis model. The examiner support system displays information about one or more selected indicators, which are one or more indicators from the acquired one or more indicators, to the examiner of the Baum test. [Effects of the Invention]

[0013] According to the present invention, it is possible to support an examiner in accurately and efficiently diagnosing the psychology of a subject through a Baum test. [Brief explanation of the drawings]

[0014] [Figure 1] 1 shows an outline of a processing flow in an embodiment. [Figure 2] An example of an examiner support UI is shown below. [Figure 3] 1 illustrates an example of the physical configuration of the entire system according to an embodiment. [Figure 4] 1 shows an example of the logical configuration of an inspector support system. [Figure 5] 10 shows an example of the structure of an index table. [Figure 6] An example of the configuration of a reference table is shown below. [Figure 7] 10 shows a part of an example of the structure of a result table. [Figure 8] The rest of the example configuration of the result table is shown below. [Figure 9] 10 shows an example of a processing flow in an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0015] In the following description, an "interface apparatus" may refer to one or more interface devices, which may be at least one of the following: One or more I / O (Input / Output) interface devices. The I / O (Input / Output) interface devices are interface devices for at least one of the I / O device and a remote display computer. The I / O interface device for the display computer may be a communications interface device. The at least one I / O device may be a user interface device, for example, either an input device such as a keyboard and a pointing device, or an output device such as a display device. One or more communication interface devices. The one or more communication interface devices may be one or more homogeneous communication interface devices (e.g., one or more NICs (Network Interface Cards)) or two or more heterogeneous communication interface devices (e.g., an NIC and an HBA (Host Bus Adapter)).

[0016] In the following description, "memory" refers to one or more memory devices, typically a primary storage device. At least one of the memory devices may be a volatile memory device or a non-volatile memory device.

[0017] In the following description, a "persistent storage device" refers to one or more persistent storage devices. A persistent storage device is typically a non-volatile storage device (e.g., an auxiliary storage device), and specifically, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive).

[0018] In the following description, the term "storage device" may refer to at least one of memory and persistent storage device.

[0019] In the following description, a "processor" refers to one or more processor devices. The at least one processor device is typically a microprocessor device such as a CPU (Central Processing Unit), but may also be other types of processor devices such as a GPU (Graphics Processing Unit). The at least one processor device may be a single-core or multi-core. The at least one processor device may also be a processor core. The at least one processor device may also be a processor device in a broader sense, such as a hardware circuit (e.g., an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit)) that performs part or all of the processing.

[0020] Furthermore, in the following description, functions may be described using the expression "kkk unit." However, the functions may be realized by one or more computer programs being executed by a processor, or by one or more hardware circuits (e.g., FPGA or ASIC). When a function is realized by a program being executed by a processor, the specified processing is performed using a storage device and / or an interface device, etc., as appropriate, and therefore the function may be considered to be at least a part of the processor. Processing described using a function as the subject may be processing performed by a processor or a device having the processor. A program may be installed from a program source. The program source may be, for example, a computer from which the program is distributed or a computer-readable recording medium (e.g., a non-transitory recording medium). The description of each function is an example, and multiple functions may be combined into one function, or one function may be divided into multiple functions.

[0021] In the following description, information that provides an output for an input may be described using expressions such as "xxx table." However, this information may be data of any structure (for example, structured data or unstructured data), or may be a neural network that generates an output for an input, or a learning model such as a genetic algorithm or random forest. Therefore, the "xxx table" may be referred to as "xxx information." In the following description, the structure of each table is an example, and one table may be divided into two or more tables, or all or part of two or more tables may be one table.

[0022] An embodiment of the present invention will be described below with reference to the drawings. In the following embodiment, the psychological test using the Baumtest is conducted by an examiner in person with a subject, but it may also be conducted online. In the following, the definitions of terms are as follows: ·Subject: The person taking the Baumtest. Examiner: A person who administers a psychological test using the Baum test and makes an assessment based on the results of the test, such as a psychologist. Diagnosator: A person who makes a diagnosis that leads to treatment of the subject based on the assessment obtained from the examiner, such as a doctor (typically a psychiatrist). A doctor may be both an examiner and a diagnostician.

[0023] FIG. 1 shows an outline of the processing flow in this embodiment.

[0024] A subject 10 visits a hospital (S51), and a diagnostician 15 interviews the subject 10 (S61). Based on the results of the interview, an examiner 20 starts examining the subject 10 (S71).

[0025] Subject 10 draws a Baumkuchen (S52) in response to instructions from examiner 20. The Baumkuchen may be drawn on paper or on a display device of an information processing terminal (for example, a touch panel of a tablet-type information processing terminal).

[0026] The target image, which is an image of the drawn Baum, is input to the examiner support system 13, which is a computer system that supports the examiner. The target image may be a photographed image of the Baum drawn on paper, or an image of the Baum drawn on a display device of an information processing terminal.

[0027] The examiner support system 13 analyzes the input target image (S81). Specifically, a Baum analysis model 251 is prepared in advance, and the examiner support system 13 inputs the target image into the Baum analysis model 251 to acquire one or more indicators for the Baum drawn by the subject. The Baum analysis model 251 is a machine learning model that receives an image of a Baum as input and outputs indicators related to the Baum test. The Baum analysis model 251 is typically a deep learning model such as a neural network, and is a model trained using training data. The training data includes, for example, for each Baum, an image of the Baum (input data) and an indicator to be noted for that Baum (correct answer data as output).

[0028] The examiner support system 13 selects information about one or more indices from the one or more indices obtained by the analysis in S81 (S82). For convenience, each of these "one or more indices" is referred to as a "selected indices." All or some of the one or more indices obtained by the analysis in S81 are selected indices. Below, we will take one selected indices as an example.

[0029] The inspector support system 13 identifies information representing statistics on the appearance trends of the selection indicators (S83). Also, for example, the inspector support system 13 identifies, as a recommendation, an indicator interpretation sentence, which is a text sentence representing an interpretation of the selection indicator (S84). Also, for example, the inspector support system 13 identifies references related to the selection indicators (S85). The inspector support system 13 displays information representing the indicators selected in S82, the statistics identified in S83, the recommendation identified in S84, and the references identified in S85 (S86). At least one of S83 to S85 may not be performed.

[0030] The examiner 20 performs a psychological test on the subject 10 based on the information (information representing at least one of the selection index, statistics, recommendations, and references) displayed by the examiner support system 13. The psychological test includes the following: · The examiner 20 interprets the Baum (S72). The examiner 20 asks the subject 10 a question (S73). The subject 10 answers the question (S53). The question in S73 and the answer in S53 are typically repeated.

[0031] The examiner 20 performs a psychological assessment of the subject 10 based on the results of the psychological test (S74). In S74, for example, findings as assessment are input by the examiner 20 to the examiner's terminal.

[0032] Based on the assessment, the diagnostician 15 diagnoses the subject 10 (S62). Based on the diagnosis in S62, the subject 10 takes action for treatment, if necessary (S54).

[0033] The examiner 20 may input information regarding the Baum test (for example, information representing at least part of the image of the drawn Baum, the displayed indicator names, the examiner's 20 interpretation of the Baum, questions for the subject 10, answers from the subject 10, and the diagnosis made by the examiner 20) into the examiner support system 13, and the input information may be stored by the examiner support system 13.

[0034] The information representing the elements selected or identified in S82 to S85 may be displayed in different UIs (User Interfaces) at different times, but in this embodiment, it is displayed in one UI at the same time, as shown in Fig. 2. Hereinafter, this one UI will be referred to as the "examiner support UI."

[0035] FIG. 2 shows an example of an examiner support UI 300.

[0036] The examiner support UI 300 is typically a GUI (Graphical User Interface), and displays a Baum image 301 , an index image set 302 , an index name list 303 , a statistics list 304 , and a recommendation / reference table 663 .

[0037] The Baum image 301 is an image of a Baum drawn by the subject 10.

[0038] The index image set 302 indicates the names of one or more Baum sites to which one or more selection indices correspond, for one or more selection indices among one or more indices obtained by inputting the Baum image 301 into the Baum analysis model 251. The index image set 302 also includes, for each of the one or more Baum sites, one or more sample images as the basis for the selection indices belonging to the Baum site. The sample image is an image of a sample Baum site.

[0039] The index name list 303 is a list of index names of the selected indexes. The statistics list 304 is a list of statistics of the appearance tendency of the selected indexes.

[0040] The recommendation / reference table 663 indicates, for each selection index, the index name, index interpretation, and reference. The reference indicates reference literature related to the selection index.

[0041] There are many indices related to the Baumtest (for example, there are approximately 80 indices). In addition, the time available for psychological testing using the Baumtest is limited (for example, about 20 minutes). It is not easy for an examiner 20 to visually find noteworthy indices from the many indices within a limited time.

[0042] In this embodiment, the above-described Baum analysis model 251 is prepared, and one or more indices are acquired by inputting a target image (a Baum image drawn by the subject 10) into the Baum analysis model 251. Then, information regarding one or more selected indices from the acquired one or more indices is displayed to the examiner 20. This allows the examiner 20 to accurately and efficiently examine the psychology of the subject 10 through the Baum test. Furthermore, according to this embodiment, the information input regarding the subject 10 may be only the Baum image drawn by the subject 10, and personal information of the subject 10 is not required.

[0043] The displayed "information about one or more selected indices" may include the name of each of the one or more selected indices, which allows the examiner 20 to quickly identify the indices as a point of view for Baum's interpretation.

[0044] Furthermore, the displayed "information regarding one or more selection indices" may include, for each of the one or more selection indices, a sample image of the Baum region that served as the basis for the selection indices. This allows the examiner 20 to visually determine whether the indices obtained by image analysis using the Baum analysis model 251 are correct by comparing the Baum region in the target image with the sample image for each Baum region. For example, if the Baum region in the target image is significantly different from the sample image, it can be determined that there is a high possibility that the indices obtained using the Baum analysis model 251 are incorrect.

[0045] Furthermore, the displayed "information about one or more selection indicators" may include an indicator interpretation for each of the one or more selection indicators, allowing the examiner 20 to quickly determine questions based on the selection indicators based on the indicator interpretation.

[0046] Note that the indicator interpretation sentence does not include the question sentence itself to the subject 10. The question sentence is determined by the examiner 20 based on the indicator interpretation sentence. Specifically, even if the same indicator (same indicator interpretation sentence) is provided to multiple different examiners, the examiners will interpret the indicator interpretation sentence differently, and therefore, the questions they ask the subject will also differ. For example, it is impossible to determine from an analysis using the Baum analysis model 251 whether a description of a certain Baum site is an expression due to an association with cutting one's body or a description of something seen that day. The examiner 20 needs to correctly understand the background of the Baum site (the background of the indicator) for accurate assessment (typically meaning findings, evaluation, etc.), and to do so, it is necessary to ask the subject 10 appropriate questions. Indicators and questions do not correspond one-to-one. The examiner 20 can also determine questions based on a combination of indicator interpretation sentences for multiple selected indicators.

[0047] Furthermore, the displayed "information regarding one or more selection indicators" may include, for each of the one or more selection indicators, information representing statistics on the appearance tendency of the selection indicator (e.g., appearance rate by age group). This allows the examiner 20 to more accurately interpret the Baum drawn by the subject 10 based on the statistics of the selection indicators. For example, analysis using the Baum analysis model 251 is an analysis of an image, and the background behind the drawing of the Baum represented by the image (e.g., the age of the subject 10) is not taken into account in the analysis using the Baum analysis model 251. Because it is not necessary to input personal information of the subject 10, the examiner 20 can interpret the Baum based on statistics linked to the selection indicators in addition to the selection indicators themselves.

[0048] Furthermore, the displayed "information about one or more selection indices" may include, for each of the one or more selection indices, information indicating references to the selection indices. This allows the examiner 20 to more accurately examine the psychology of the subject 10 based on the references to the selection indices.

[0049] This embodiment will be described in detail below.

[0050] FIG. 3 shows an example of the physical configuration of the entire system according to the embodiment.

[0051] The examiner support system 13 and the examiner terminal 11 communicate with each other via a communication network (for example, the Internet) 160.

[0052] The examiner terminal 11 is an information processing terminal (for example, a desktop, mobile, or tablet personal computer) and includes, for example, an input device 113 (for example, a keyboard or a mouse), a display device 114 (for example, a display device), an interface device 111, a storage device 112, and a processor 115. The input device 113 and the display device 114 may be an integrated device such as a touch panel. The input device 113 and the display device 114 are connected to the interface device 111, and communication with the examiner support system 13 is performed through the interface device 111. The processor 115 is connected to the interface device 111 and the storage device 112. The examiner terminal 11 may be a virtual information processing terminal (for example, a virtual machine on a server) instead of such a physical information processing terminal.

[0053] The examiner support system 13 has a front-end server 23 connected to a communication network 160, and a back-end server 33 connected to the front-end server 23 via a communication network 170. A dedicated line may be used instead of the communication network 170, or the communication network 170 may be the same communication network as the communication network 160.

[0054] The front-end server 23 includes an interface device 131, a storage device 132, and a processor 133 connected to them. Communication with the examiner terminal 11 and the back-end server 33 is performed via the interface device 131. The storage device 132 stores computer programs executed by the processor 133 and data referenced or updated by the processor 133. The processor 133 executes the computer programs stored in the storage device 132.

[0055] The back-end server 33 includes an interface device 141, a storage device 142, and a processor 143 connected to these. Communication with the front-end server 23 is performed via the interface device 141. The storage device 142 stores computer programs executed by the processor 143 and data referenced or updated by the processor 143. The processor 143 executes the computer programs stored in the storage device 142.

[0056] In this embodiment, the examiner support system 13 is a physical computer system configured with a front-end server 23 and a back-end server 33 as examples of one or more physical computers, but instead of a physical computer system, a virtual computer system (e.g., a cloud computing service or an application service) based on a physical computer system (e.g., a cloud platform) may be used. The examiner support system 13 may be configured with a single server instead of being configured with multiple different servers such as the front-end server 23 and the back-end server 33.

[0057] FIG. 4 shows an example of the logical configuration of the examiner support system 13.

[0058] A result table 201, a statistics table 202, and a reference table 203 are stored in the storage device 132 of the front-end server 23. The result table 201 stores information as a processing result as appropriate. The statistics table 202 stores, for each index, information representing statistics on the appearance tendency of the index. The result table 201 and the reference table 203 will be described later. Although not shown, a feedback table may be stored in the examiner support system 13 (or an external storage system). The feedback table may store, for each Baum test, information fed back from the examiner 20 regarding the Baum test (for example, information representing at least part of the image of the drawn Baum, the displayed index name, the examiner 20's interpretation of the Baum, questions for the subject 10, answers from the subject 10, and the assessment made by the examiner 20). At least part of the information in the feedback table may be used, for example, as training data, for training the Baum analysis model 251.

[0059] The processor 133 of the front-end server 23 executes a computer program to realize functions such as a UI unit 211 and an index optimization unit 212. The UI unit 211 provides a UI to the examiner 20 (provides display information to the examiner terminal 11). The index optimization unit 212 optimizes one or more indexes obtained as a result of analysis using the Baum analysis model 251 into one or more indexes (selected indexes).

[0060] An index table 252 and a Baum analysis model 251 are stored in the storage device 142 of the back-end server 33. The index table 252 will be described later.

[0061] The processor 143 of the backend server 33 executes a computer program to realize functions such as a Baum analysis unit 261 and an index acquisition unit 262. The Baum analysis unit 261 performs analysis using a Baum analysis model 251. The index acquisition unit 262 acquires, for each index obtained by the analysis, information associated with the index from the index table 252.

[0062] 4 (the arrangement of functions and tables in the examiner support system 13) is one example. Any function and any table in the examiner support system 13 may be arranged in any server. As described above, the examiner support system 13 may be configured with one server, and the functions and tables illustrated in FIG. 4 may be provided in that server.

[0063] FIG. 5 shows an example of the structure of the index table 252.

[0064] The index table 252 has a record for each index related to the Baum test. Each record has information such as a Baum location 501, a classification 502, an index ID 503, an early type 504, a level of importance 505, an index name 506, an index status 507, and an index interpretation 508. Take one index as an example.

[0065] Baum site 501 represents the Baum site to which the index belongs. Classification 502 represents the classification to which the index belongs. Baum site 501 corresponds to information representing a first classification, and classification 502 corresponds to information representing a second classification that is lower than the first classification.

[0066] The index ID 503 indicates the ID of the index. The early type 504 indicates whether the index is an early type (whether the index appears early in development and disappears as the child grows). "0" means that the index is not an early type, and "1" means that the index is an early type.

[0067] The importance 505 indicates the importance of the index. The higher the value, the higher the importance of the index.

[0068] The index name 506 indicates the name of the index. In this embodiment, the index name 506 corresponds to the primary key in the index table 252. The index status 507 indicates the status of the index, for example, details of the expression of the Baum site to which the index belongs.

[0069] The index interpretation 508 is an index interpretation sentence of the index. The index interpretation sentence is displayed on the examiner terminal 11 as shown in FIG.

[0070] The index table 252 may include a sample image (or a link to a sample image) for each index. That is, the sample images illustrated in FIG. 2 (sample images for each Baum region) may be obtained by referring to the index table 252.

[0071] FIG. 6 shows an example of the configuration of the reference table 203.

[0072] The reference table 203 has a record for each index related to the Baum test. Each record has an index name 601 and reference information for identifying the location of the corresponding reference (e.g., author name 602, title 603, publication name 604, publication year 605, volume number 606, start page 607, end page 608, and URL 609). Let's take one index as an example.

[0073] The index name 601 indicates the name of the index. The author name 602 indicates the name of the author of the reference in which information about the index is published. The title 603 indicates the title of the reference. The publication name 604 indicates the name of the academic journal etc. (academic journal or other book) in which the reference is published. The publication year 605 indicates the year in which the academic journal etc. was published. The volume number 606 indicates the corresponding volume number of the academic journal etc. The start page 607 indicates the first page of the reference in the academic journal etc. The end page 608 indicates the last page of the reference in the academic journal etc. The URL 609 indicates the URL as a link to the reference.

[0074] 7 and 8 show examples of the structure of the result table 201. FIG.

[0075] The result table 201 is prepared for each Baum test (each Baum image), for example. The result table 201 has a record for each index. This "each index" may be for each predefined index, or may be for each index obtained by analyzing the Baum image (output from the Baum analysis model 251).

[0076] Each record contains information such as a classification result 701, accuracy 702, number of classifications 703, Baum region 704, classification 705, index ID 706, early type 707, importance 708, index name 709, index status 710, index interpretation 711, importance 712, statistics 713, author name 714, title 715, publication nomination 716, publication year 717, volume number 718, start page 719, end page 720, and URL 721. Take one index as an example.

[0077] The discrimination result 701 indicates whether the indicator is identified. The accuracy 702 indicates the probability that the indicator is correct. This probability is determined in the analysis using the Baum analysis model 251.

[0078] The number of discriminations 703 indicates the cumulative total of the indices obtained from the Baum image.

[0079] The Baum portion 704, classification 705, index ID 706, early type 707, importance 708, index name 709, index status 710, and index interpretation 711 are the Baum portion 501, classification 502, index ID 503, early type 504, importance 505, index name 506, index status 507, and index interpretation 508 obtained from the index table 252 using the index name as a key.

[0080] The importance 712 indicates whether the indicator is an important indicator or a general indicator. "1" means an important indicator, and "0" means a general indicator. For example, for each indicator, information indicating whether the indicator is an important indicator or a general indicator may be registered in the indicator table 252, and this information may be registered in the result table 201 as importance 712.

[0081] Statistics 713 represent statistics for the index obtained from the statistics table 202. Author name 714, title 715, publication designation 716, publication year 717, volume number 718, start page 719, end page 720, and URL 721 are the author name 602, title 603, publication name 604, publication year 605, volume number 606, start page 607, end page 608, and URL 609 obtained from the reference table 203 using the index name as a key.

[0082] FIG. 9 shows an example of the flow of processing in the embodiment.

[0083] In the front-end server 23, the UI unit 211 receives input of a Baum image from the examiner terminal 11 and transmits the Baum image to the back-end server 33 (S901). For example, in S901, an analysis request associated with the Baum image is transmitted.

[0084] In the back-end server 33, the Baum analysis unit 261 performs image processing such as digitization of the Baum image from the front-end server 23, for example, in response to an analysis request (S902). The Baum analysis unit 261 inputs the processed image into the Baum analysis model 251, thereby analyzing the Baum image (S903). For each index obtained by the analysis of S903, the index acquisition unit 262 acquires information 501 to 508 corresponding to the index from the index table 252 using the index name of the index as a key (S904). The index acquisition unit 262 transmits result information (for example, information including, for each index, information 501 to 508 (information 704 to 711 exemplified in FIG. 7) and information 701 to 703 and 712 exemplified in FIG. 7) to the front-end server 23 (S905). For example, the result information is transmitted as a response to the analysis request. The result information may include a sample image (or a link thereto) for each index.

[0085] In the front-end server 23, the index optimization unit 212 optimizes one or more indexes represented by the result information into one or more indexes (selected indexes) based on the result information (S906). For example, the index optimization unit 212 registers information (information 701 to 712) of each of the one or more indexes represented by the result information in the result table 201. The index optimization unit 212 optimizes (narrows down) the one or more indexes into one or more selected indexes based on at least one of the importance 708, the number of discriminations 703, and the accuracy 702 for each index. As a result, even if many indexes are identified, the indexes displayed on the examiner terminal 11 are narrowed down to appropriate indexes.

[0086] 2 on the examiner terminal 11. In this case, the examiner support UI 300 displays the Baum image 301, the index image set 302, the index name list 303, and the index names and index analyses in the recommendation / reference table 203, but does not display the statistics list 304 or references.

[0087] If necessary (for example, when a statistics request specifying an index is received via the examiner support UI 300), the UI unit 211 acquires statistics corresponding to the index name of the specified index from the statistics table 202 (S907). The UI unit 211 registers the acquired statistics in the result table 201 as statistics 713.

[0088] Furthermore, the UI unit 211, if necessary (for example, when a reference request in which an index is specified is received via the examiner support UI 300), acquires reference information (information 602 to 609) corresponding to the index name of the specified index from the reference table 203 (S908). The UI unit 211 registers the acquired reference information (information 602 to 609) in the result table 201 as information 714 to 721.

[0089] The UI unit 211 displays the examiner support UI 300, which displays information about the selection index narrowed down in S906, on the examiner terminal 11 (S909).

[0090] Although one embodiment of the present invention has been described above, this is merely an example for explaining the present invention, and the scope of the present invention is not limited to this embodiment. The present invention can be implemented in various other forms.

[0091] For example, trees vary depending on the region (e.g., country or state), and therefore, for example, the Baum analysis model 251 and the index table 252 may be prepared for each region.

[0092] Also, for example, the appearance rate of some indicators may differ depending on age group, so for example, the Baum analysis model 251 may be prepared for each age group.

[0093] Furthermore, for example, the displayed examiner support UI300 may accept information input (e.g., manual input or voice input) during a psychological test, and may be updated according to the input information (e.g., information representing the answer of the subject 10).

[0094] Furthermore, for example, the examiner support system 13 may have an assessment support function. For example, this function may be a function to display a UI that displays a template including input items for assessment. This reduces the amount of information that the examiner 20 must input, thereby reducing the input burden on the examiner. [Explanation of symbols]

[0095] 13...Examiner support system

Claims

1. a Baum analysis unit that inputs a target image, which is an image of a Baum drawn by a subject of a Baum test, into a Baum analysis model that is a machine learning model that inputs an image of a Baum and outputs an index specific to the Baum test, such as a single-line root, a double-line root, or a stem-lower edge stand, and thereby acquires one or more indexes for the Baum drawn by the subject from among the indexes that are predetermined for each of multiple Baum parts as indexes specific to the Baum test, such as a single-line root, a double-line root, or a stem-lower edge stand; a user interface unit that displays, to an examiner of the Baum test, information about the target image and one or more selected indices, which are one or more indices for one or more Baum sites in the target image among the one or more acquired indices; An inspector support system comprising:

2. The information about the one or more selection indices includes, for each of the one or more selection indices, an index name of the selection indices; The inspector support system according to claim 1 .

3. The information about the one or more selection indices includes, for each of the one or more selection indices, one or more sample images of the Baum region to which the selection indices belong; 3. The inspector support system according to claim 1.

4. The information about the one or more selection indicators includes, for each of the one or more selection indicators, an indicator interpretation sentence, which is a text sentence representing a pre-prepared interpretation of the selection indicator. The inspector support system according to any one of claims 1 to 3.

5. an index optimization unit that optimizes the one or more acquired indexes into the one or more selected indexes based on at least one of the importance, the number of discriminations, and the accuracy of each of the one or more acquired indexes; Further provided with For each of the one or more indicators, the importance is a value identified from index information including information indicating the importance of each index related to the Baum test, the number of discriminations is a cumulative total of the indices obtained from the target image, The accuracy is the accuracy determined for the indicator from the Baum analysis model.

5. The inspector support system according to claim 1.

6. The target image is an image input from an information processing terminal, the user interface unit displays the target image and information relating to the one or more selection indicators on a display of the information processing terminal; 6. The inspector support system according to claim 1.

7. An information processing terminal; The inspector support system according to any one of claims 1 to 6, Equipped with the target image is an image input from an information processing terminal, the user interface unit displays the target image and information relating to the one or more selection indicators on a display of the information processing terminal; system.

8. A computer inputs a target image, which is an image of a Baum drawn by a subject in a Baum test, into a Baum analysis model, which is a machine learning model that inputs an image of a Baum and outputs an index specific to the Baum test, such as a single-line root, a double-line root, or a stem-lower edge stand, and obtains one or more indexes for the Baum drawn by the subject from among the indexes predetermined for each of multiple Baum parts as indexes specific to the Baum test, such as a single-line root, a double-line root, or a stem-lower edge stand, The computer displays, for an examiner of the Baum test, information on the target image and one or more selected indices, which are one or more indices for one or more Baum sites in the target image from among the one or more acquired indices. Examiner assistance methods.

9. By inputting a target image, which is an image of a Baum drawn by a subject taking a Baum test, into a Baum analysis model, which is a machine learning model that inputs an image of a Baum and outputs an index specific to the Baum test, such as a single-line root, a double-line root, or a stem-lower edge standing, one or more indexes are obtained for the Baum drawn by the subject from among the indexes predetermined for multiple Baum parts as indexes specific to the Baum test, such as a single-line root, a double-line root, or a stem-lower edge standing, and displaying information about the target image and one or more selected indices, which are one or more indices for one or more Baum sites in the target image among the one or more acquired indices, for an examiner of the Baum test. A computer program that causes a computer to do something.

Images