Program supporting matching between patient and peer support community

Abstract

To provide a technique supporting further precise matching with a peer support community that a patient demands.SOLUTION: In an information processing system 1, a server device 2 has a control unit which functions as: input acceptance means for accepting input of user information including at least one of disease background information related to the background of a disease, therapy background information related to the background of therapy, mental background information related to a mental state, and attribute information showing attributes, and importance related to a matter regarded as important, from a user as the patient; calculation means for performing affinity calculation between the patient and peer support community based upon the user information, the importance, and a plurality of pieces of peer support communicate information to calculate the affinity between the patient and peer support community; and display control means for controlling a display corresponding to the affinity between the patient and peer support community based upon the calculation result of the affinity.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a program that assists in matching patients with peer support communities. [Background technology]

[0002] Cancer patients have a wide variety of worries, including cancer symptoms, pain from treatment, anxiety about the future, treatment costs, cosmetic concerns, etc., due to the stage of the cancer and the environment they find themselves in. These worries are unique and cause a sense of psychological isolation, so cancer patients can reduce their psychological burden by connecting with people called peer supporters who have experienced similar situations.

[0003] Patent Document 1 discloses a technology for matching multiple users by analyzing input data from multiple users and determining, for each user and life event, the life events that each user has experienced, is currently experiencing, or may experience in the future, and performing matching between multiple users. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] U.S. Patent Publication No. 2020 / 0351234 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the matching technology of Patent Document 1 does not reflect the factors that users consider important when matching, making it difficult to match patients with peer support communities that have people they need to talk to.

[0006] Therefore, one of the objectives of the present invention is to provide technology that supports more accurate matching with the peer support community that patients are looking for. [Means for solving the problem]

[0007] A program according to one embodiment of the present invention causes a computer to function as: an input accepting means for accepting input of user information about the user who is a patient and a level of importance of important matters from the user, the user information including at least one of disease background information about the background of the user's disease, treatment background information about the background of the user's treatment, psychological background information about the user's mental state, or attribute information indicating the attributes of the user; a calculation means for performing an affinity calculation between the patient and the peer support community based on the user information, the level of importance, and a plurality of peer support community information about a plurality of peer support communities, and calculating the affinity between the patient and the peer support community, the peer support community information including information about a plurality of topics of the peer support community, and the affinity calculation including calculating a similarity between the user information and the peer support community information; and a display control means for controlling a display according to the affinity between the patient and the peer support community based on a result of the affinity calculation.

[0008] An information processing device according to one embodiment of the present invention includes an input receiving unit that receives, from a user who is a patient, input of user information related to the user and a level of importance related to a matter that the user places importance on, wherein the user information includes at least one of disease background information related to the background of the user's disease, treatment background information related to the background of the user's treatment, psychological background information related to the user's mental state, or attribute information indicating the attributes of the user; a calculation unit that performs an affinity calculation between the patient and the peer support community based on the user information, the level of importance, and a plurality of community information related to a plurality of peer support communities, and calculates the affinity between the patient and the peer support community, wherein the peer support community information includes information related to a plurality of topics of the peer support community, and the affinity calculation includes calculating a similarity between the user information and the peer support community information; and a display control unit that controls a display according to the affinity between the patient and the peer support community based on a result of the affinity calculation.

[0009] An information processing method according to one aspect of the present invention includes a step of receiving, from a user who is a patient, input of user information about the user and a level of importance regarding a matter that the user places importance on, wherein the user information includes at least one of disease background information about the background of the user's disease, treatment background information about the background of the user's treatment, psychological background information about the user's mental state, and attribute information indicating the attributes of the user; a calculation unit that performs an affinity calculation between the patient and the peer support community based on the user information, the level of importance, and a plurality of community information about a plurality of peer support communities, and calculates an affinity between the patient and the peer support community, wherein the peer support community information includes information about a plurality of topics of the peer support community, and the affinity calculation includes calculating a similarity between the user information and the peer support community information; and a step of controlling a display according to the affinity between the patient and the peer support community based on a result of the affinity calculation. Execute the command. Effect of the Invention

[0010] According to the present invention, it is possible to provide a technology that supports more accurate matching with the peer support community that patients desire. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram illustrating a configuration of an information processing system. [Diagram 2] FIG. 11 is a flowchart illustrating the operation of the information processing system. [Diagram 3] 11 is a diagram illustrating an example of a display screen of a user terminal. FIG. [Figure 4] 11 is a diagram illustrating an example of a display screen of a user terminal. FIG. [Diagram 5] FIG. 13 is a diagram illustrating user information input by a patient. [Figure 6] FIG. 13 is a diagram illustrating peer support community information relating to a peer support community. [Figure 7] FIG. 2 is a hardware configuration diagram of the server device 2. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] A preferred embodiment of the present disclosure (hereinafter, referred to as the present embodiment) will be described with reference to the accompanying drawings. In each drawing, the same reference numerals denote the same or similar configurations.

[0013] [Information processing system configuration] Fig. 1 is a diagram showing an example of the configuration of an information processing system 1 according to the present invention. As shown in Fig. 1, the information processing system 1 includes a patient terminal device 3, a server device 2, and a communication network 5. In this embodiment, the patient terminal device 3 may be referred to as a "user terminal device 3." The user terminal device 3 and the server device 2 are configured to be able to communicate with each other via the communication network 5.

[0014] The communication network 5 is a wired or wireless network, and may be the Internet, a LAN (Local Area Network), a dedicated line, a telephone line, an in-house network, a mobile communication network, Bluetooth (registered trademark), WiFi (Wireless Fidelity), other communication lines, or a combination thereof. The user terminal device 3 and the server device 2 may be located in the same facility or in remote locations.

[0015] The server device 2 is a server device that uses the user terminal device 3 as a client device, and is typically a web server device. The server device 2 includes a control unit 10, a storage unit 11, a communication interface unit 12, and a bus 13. The control unit 10, the storage unit 11, and the communication interface unit 12 are electrically connected to each other via the bus 13. The server device 2 may be composed of one computer, or may be composed of multiple computers distributed over the communication network 5. The server device 2 realizes various functions described in this embodiment by the control unit 10 executing various programs stored in the storage unit 11.

[0016] The user terminal device 3 is a device used by a user. The user is, for example, a patient. In this embodiment, the patient may be referred to as a "user". The user terminal device 3 is, for example, an electronic device such as a smartphone, a smart watch, a tablet terminal, or a personal computer. In this embodiment, the user terminal device 3 is described as being a smartphone. The user can operate the user terminal device 3 by touching a touch panel display provided on the user terminal device 3. The user terminal device 3 can function a web browser, application software, or the like.

[0017] A peer support application (hereinafter referred to as "peer support app") AP1 may be stored in the memory of the user terminal device 3. The peer support app is an application program that enables patients to search peer support communities, browse various information, and perform matching. The peer support app AP1 may be configured to be installed in the user terminal device 3, or may be configured such that some or all of the functions of the peer support app AP1 are provided from the server device 2 via the communication network 5 (such as so-called SaaS (Software as a Service)).

[0018] The following describes various functions that are realized by the control unit 10 of the server device 2 executing a program according to an embodiment of the present invention. The server device 2 functions as an input receiving unit, a calculation unit, and a display control unit by the control unit 10 executing a program according to an embodiment of the present invention.

[0019] (Input reception means) The input receiving means has a function of receiving input of user information about the patient and the importance of the priority items input by the patient.

[0020] The input user information includes one or more of the disease background information, treatment background information, psychological background information, and attribute information of the patient, as shown in FIG. 5, for example. The disease background information is information about the background of the patient's disease, and includes items such as disease name, cancer type, cancer stage, diagnosis status, and physical condition. The treatment background information is information about the background of the patient's treatment, and includes items such as current medical history, medical history, family history, treatment history, treatment schedule, and treatment values. The psychological background information is information about the mental state of the patient, and includes items such as self-perception and other's perception of the mental state. The attribute information is information indicating the attributes of the patient, and includes items such as age, employment status, occupation, family composition, budget, personality of the patient, lifestyle, living area, life events (such as a child's graduation ceremony), interests and worries in life (treatment, finances, lifestyle, and employment), desired consultation content, available consultation content, and topics to avoid. In this embodiment, the input user information includes at least text information indicating the value of the user for each item.

[0021] In this embodiment, a "patient" refers to a person suffering from a disease, and may be a person suffering from a chronic disease such as cancer, leukemia, sarcoma, myeloma, stroke, myocardial infarction, hypertensive disease, diabetes, cirrhosis of the liver, chronic renal failure, and mental illness (including depression, schizophrenia, and dementia).

[0022] In this embodiment, the "cancer" will be described as typically breast cancer, but the scope of application of this embodiment is not limited to this and may include other types of cancer, such as lung cancer, stomach cancer, colon cancer, pancreatic cancer, prostate cancer, liver cancer, esophageal cancer, and cervical cancer.

[0023] In this embodiment, a "cancer patient" refers to an individual who has been diagnosed with cancer, and includes both individuals who are at a stage where they require treatment and individuals under observation who are undergoing follow-up observation of their condition.

[0024] In this embodiment, the "peer support community" refers to a community formed by individuals who have overcome a disease, individuals who have the same or similar experiences or situations related to the disease as the individual, or people related to the individual, such as their relatives or acquaintances. In this embodiment, the "individual who has overcome a disease" includes both individuals who have successfully undergone treatment and are in complete remission, and individuals whose disease condition has temporarily subsided as a result of treatment.

[0025] In this embodiment, the term "current medical history" refers to a record of a disease currently being suffered from, and includes the onset history, onset time, and symptom progression of the disease currently being suffered from. In this embodiment, the term "past medical history" refers to a record of a disease suffered from in the past, and includes the onset history, onset time, and symptom progression of the disease suffered from in the past. In this embodiment, the term "family history" refers to the current medical history and past medical history of the user's close relatives. In this embodiment, the term "treatment history" refers to a record of current and past treatments, such as surgical treatment, chemotherapy, hormone therapy, and radiation therapy. In addition, in this embodiment, the term "treatment history" refers to a record of supplementary treatments, such as breast reconstruction, exercise therapy, diet therapy, and counseling. In this embodiment, the term "treatment schedule" refers to a schedule of actions related to treatment, such as consultation, hospitalization, discharge, surgery, examination, and drug treatment. In this embodiment, the term "genetic information" refers to information indicating an individual's biological characteristics, and includes blood type, genetic test data, and the like. In this embodiment, "treatment values" refer to the values ​​that the user holds regarding treatment, and may include wanting a quick recovery, wanting to avoid chemotherapy, preferring natural therapies, wanting to keep costs as low as possible, wanting to minimize pain, wanting to use the latest treatments, etc.

[0026] User information may be input in chatbot format, voice input format, free-form text box format, or checkbox selection format. When free-form text box format is used, keywords may be extracted and accepted as user information input. When checkbox selection format is used, checkboxes for topics and subtopics that are more detailed and linked to the topics may be provided for each item of user information, and the user may check the checkbox to accept the user information as input.

[0027] The input receiving means receives input of the importance of the various user information described above as considered by the patient. The importance is information related to matters that the patient considers important. For example, the input of keywords that the patient desires to emphasize when inputting the user information may be received as the importance. The score given by the user to each presented item or keyword may be received as the importance. The selection of items that the user considers important for each type of user information may be received as the importance. The selection of items that the user considers important may be received as the importance.

[0028] Importance input can be performed by providing check boxes corresponding to topics for each item and subtopics that provide more detailed content for the topic, and determining that items for which a predetermined number or more check boxes corresponding to subtopics have been selected are items that the user places importance on and accepting these as the importance input.

[0029] The input receiving means may also receive input of topics that the patient wants to avoid when receiving input of user information and importance by the patient. This can reduce the occurrence of a situation in which the patient unintentionally comes into contact with information that may increase the psychological burden. The input of topics that the patient wants to avoid may be received in the same manner as the input of user information and importance.

[0030] The input receiving means may score the user information input by the patient and receive it as a numerical value. For example, the input contents of the psychological background information may be classified and scored as 1: stable, 2: decreased motivation, 3: unstable, 4: depressed, 5: irritable, etc., or the user information may be scored by having the user select from options that have been classified and scored in advance.

[0031] The input user information may be automatically linked to medical data such as electronic medical records.

[0032] (Calculation method) The calculation means has a function of performing an affinity calculation between the patient and the peer support community based on user information and importance input by the patient and multiple peer support community information related to multiple peer support communities, and calculating the affinity between the patient and the peer support community.

[0033] In this embodiment, "peer support community information" is information related to the activities and management of the peer support community, and includes, for example, information related to multiple topics of the peer support community, text information related to the profiles and posts of multiple participating members of the peer support community, etc. In this embodiment, information related to topics of the peer support community is information related to topics held by the peer support community, and includes at least text information such as the titles of the topics and the content posted on the topics.

[0034] The affinity calculation may involve calculating a feature score or feature vector corresponding to a user and a feature score or feature vector corresponding to a peer support community, and calculating the similarity between the user information of the user and the peer support community information of the peer support community based on the calculated feature score or vector.

[0035] In this embodiment, "affinity" represents the degree to which a user is familiar with a peer support community and the topics of the peer support community. In this embodiment, affinity is calculated based on the similarity between user information and peer support community information, but is not limited to this.

[0036] The calculation of the feature score and feature vector corresponding to the user or the peer support community may be performed by performing a morphological analysis on the text information included in the user information or the peer support community information, and calculating the feature score and feature vector of the keyword corresponding to a predetermined item for the user or the peer support community, and using these as the feature score and feature vector corresponding to the user or the peer support community. The correspondence between various items and the keywords used to calculate the feature vector of the item may be stored in a referable manner in the storage unit 11 of the server device 2, for example.

[0037] For example, the affinity between user A and peer support community B may be calculated by calculating a feature score for item I of user A and a feature score for item I of peer support community B, and performing a similarity analysis of the calculated feature scores. Furthermore, the affinity between user A and peer support community B may be calculated by performing natural language processing such as morphological analysis on the user information of user A and the peer support community information of peer support community B, calculating a feature vector for item I of user A and a feature vector for item I of peer support community B, and performing a similarity analysis of the calculated feature vectors.

[0038] The morphological analysis can be performed by using a morphological analyzer corresponding to the language contained in the text information to be analyzed. Based on the results of the morphological analysis, a feature score or a feature vector can be calculated from the frequency of occurrence or commonality of a predetermined keyword. For example, a Bag-of-Words (BoW) value or a Term Frequency-Inverse Document Frequency (TF-IDF) value may be used to calculate a feature vector based on the frequency of occurrence or commonality of a predetermined keyword. The BoW value can calculate a feature vector based on the frequency of occurrence of a predetermined keyword in a topic. The TF-IDF value can calculate a feature vector based on the commonality derived from the frequency of occurrence of a predetermined word in a predetermined topic and the frequency of occurrence of the keyword in topics other than the topic. Note that TF is a value indicating the frequency at which a predetermined keyword appears in a predetermined text, and the larger this value, the more frequently the keyword appears in the predetermined text. Also, DF is a value indicating the frequency at which a predetermined keyword appears in a plurality of predetermined texts, and the larger this value, the more frequently the keyword appears in the plurality of texts.

[0039] The TF-IDF is calculated by multiplying the TF by the IDF, which is the inverse of the DF. For example, the following formula may be used to calculate the TF-IDF.

[0040]

number

[0041] In this embodiment, for example, in the above formula, "tf i.j " indicates the frequency with which a given keyword i appears in multiple sentences constituting topic j of a given peer support community, "N" indicates the total number of multiple sentences constituting multiple topics of multiple peer support communities to be searched, and "df i " indicates the number of sentences containing keyword i among all sentences that make up the multiple topics of the multiple peer support communities being searched.

[0042] In this embodiment, the "feature vector corresponding to a user" may be the inner product of the feature vectors of keywords corresponding to a predetermined item in the user information of the user. That is, the feature vector corresponding to a user may be the feature vector of a predetermined item on a per-user basis. For example, when the user information of user A includes "I am feeling depressed because my mental health has been worsening," "I am worried about returning to society, but I am worried because I have not found anyone to help me," and "I am mentally overwhelmed because I have no idea how much I can pay for treatment," a morphological analysis is performed on the text information, and the feature vectors of each of the items "mental counseling," "body counseling," "money counseling," and "family counseling" of user A are calculated. The feature vectors of each of the items such as "mental counseling," "body counseling," "money counseling," and "family counseling" may be calculated by the inner product of the feature vectors of the keywords used to calculate the feature vectors of each item.

[0043] When user information input by a user is accepted as a score, a feature vector may be calculated based on the score for each type or item of user information.

[0044] In the affinity calculation, when calculating the feature score or feature vector of a user, a weighting process may be performed on the user information based on the importance input by the user. For example, the feature score of the item may be calculated by multiplying the basic score of each item, such as the consultation content input by the user, by the importance score as a weighting coefficient.

[0045] For example, if the items of consultation content entered by the user are "mental consultation" (importance score: 5), "physical consultation" (importance score: 2), and "money consultation" (importance score: 3), the feature score for the "mental consultation" item may be the basic score 1 of the "mental consultation" item multiplied by the importance score 5, the feature score for the "physical consultation" item may be the basic score 1 of the "physical consultation" item multiplied by the importance score 2, and the feature score for the "money consultation" item may be the basic score 1 of the "money consultation" item multiplied by the importance score 3.

[0046] The weighting process may be to multiply the basic score of each item by the [importance score / total importance score] of each item to obtain the feature score of the item. The weighting process may be to adjust the importance score given to a specific item among multiple items based on the relationship with the importance scores given to other items. For example, the importance score given to the specific item may be adjusted based on the ranking, deviation value, difference, etc. with respect to the importance scores given to other items.

[0047] In this embodiment, the "feature vector corresponding to a topic of a community" may be an inner product of feature vectors of keywords corresponding to a predetermined item in the topic. In other words, the feature vector corresponding to a topic of a community may be a feature vector of an item on a topic-by-topic basis.

[0048] For example, if the topics of community A are "topic 1: relapse," "topic 2: family history," "topic 3: medical expenses," "topic 4: mental illness," and "topic 5: relationships with family," the feature vector corresponding to topic 1 can be calculated by performing morphological analysis on the text information contained in topic 1 and calculating the feature vectors of each of the items of "mental health advice," "health advice," "money advice," and "family advice" in topic 1 of community A. The feature vector of each item can be calculated by calculating the inner product of the feature vectors of each keyword used to calculate the feature vector of each item, similar to the calculation of the feature vector corresponding to a user.

[0049] In this embodiment, the "feature vector corresponding to a community" may be, for example, an inner product of feature vectors of predetermined items of the community, calculated by the inner product of feature vectors of keywords corresponding to predetermined items in the community. In other words, the feature vector of a community may be a feature vector of a predetermined item on a community-by-community basis. For example, if the topics in community A are "Topic 1: Recurrence," "Topic 2: Family history," "Topic 3: Medical costs," "Topic 4: Mental disorders," and "Topic 5: Relationships with family," a morphological analysis can be performed on the text information contained in topics 1 to 5 to calculate feature vectors for each of the items "mental counseling," "physical counseling," and "money counseling" in topics 1 to 5 of community A. The inner product of each feature vector for the "mental counseling" item in topics 1 to 5 can be used as the feature vector for the "mental counseling" item in community A, the inner product of each feature vector for the "physical counseling" item in topics 1 to 5 can be used as the feature vector for the "physical counseling" item in community A, and the inner product of each feature vector for the "money counseling" item in topics 1 to 5 can be used as the feature vector for the "money counseling" item in community A. The feature vector for each item may be calculated by calculating the inner product of the feature vectors of each keyword used to calculate the feature vector for each item, similar to the calculation of the feature vector corresponding to a user or the feature vector corresponding to a topic in a community.

[0050] The calculation means calculates a similarity between user information and peer support community information based on a feature score or a feature vector corresponding to a user and a feature score or a feature vector corresponding to a peer support community, and calculates an affinity between the user and the peer support community.

[0051] For example, the affinity between user A and each of the multiple peer support communities may be calculated by searching and extracting peer support communities having a feature score for the "mental consultation" item within a predetermined range using the feature score for the "mental consultation" item of user A as a reference. Also, for example, a cosine similarity analysis may be performed between the feature vector for the "physical consultation" item of user A and the feature vector for the "physical consultation" item of the multiple peer support communities to calculate the affinity between user A and each of the multiple peer support communities. Also, for example, a cosine similarity analysis may be performed between the feature vector for the "money consultation" item of user A and the feature vector for the "money consultation" item of the multiple topics of peer support community A to calculate the affinity between user A and each of the multiple topics of peer support community A.

[0052] As a calculation formula for performing the cosine similarity analysis, for example, the following formula may be used.

[0053]

number

[0054] In the formula, A and B indicate the feature vectors of each sample to be compared. In this embodiment, for example, in the above formula, A indicates the feature vector of the "mental health consultation" item of the user, and B indicates the feature vector of the "mental health consultation" item of the peer support community A. In the formula, Ai and Bi indicate the i-th components of A and B, respectively. The result of the cosine similarity analysis is calculated as a value between 0 and 1, and the closer the value is to 0, the lower the similarity and affinity of the items to be compared, and the closer the value is to 1, the higher the similarity and affinity of the items to be compared.

[0055] The calculation means may also calculate feature scores and feature vectors for the profiles and posts of members participating in the community, and use them to calculate the affinity. The calculation of the feature scores and feature vectors may be performed in the same manner as the calculation of the feature scores and feature vectors for users, peer support communities, and topics of the peer support communities.

[0056] (Display control means) The display control means has a function of controlling display according to the affinity between the user and the peer support community, or between the user and the topic of the peer support community, based on the calculation result of the affinity. In this embodiment, controlling the display includes transmitting information required for various display controls according to this embodiment from the server device 2 to the user terminal device 3.

[0057] The display control means may visually display the affinity between the patient and the peer support community, or between the user and the topic of the peer support community, which makes it easier for the patient to find the peer support community that he or she desires.

[0058] For example, the affinity of each peer support community may be displayed in the list of searched peer support communities. The peer support communities may be ranked in order of affinity with the patient. The list of peer support communities may display topics with high affinity with the patient and the affinity of the topics with high affinity. The list of searched peer support communities may display topics with high affinity with the patient in an identifiable manner.

[0059] In this embodiment, "affinity" is not necessarily limited to being displayed as affinity, but may be displayed using expressions such as relevance, compatibility, degree of agreement, affinity, match, etc., or may be displayed using a numerical value.

[0060] The following describes various screens displayed on the user terminal device 3 based on the various functions described above. If a peer support application AP1 is installed in the user terminal device 3, the peer support application AP1 may display various screens.

[0061] (1) Recommended peer support community list screen (see Figure 3) The control unit 10 of the server device 2 performs affinity calculation between the patient and the peer support community based on the user information and importance input by the patient and multiple peer support community information related to multiple peer support communities, calculates the affinity between the patient and the peer support community, and controls display according to the affinity between the patient and the peer support community based on the affinity calculation result. Here, the control unit 10 of the server device 2 may display the peer support community together with the topic of the peer support community according to the affinity between the patient and multiple topics of the peer support community. Also, topics with high affinity with the patient may be displayed in a identifiable manner. For example, a recommended peer support community list screen d10 shown in FIG. 3 is displayed on the user terminal device 3.

[0062] The recommended peer support community list screen d10 exemplarily displays a peer support community list d210 showing the searched peer support communities, an affinity d110 showing the affinity with the patient, and a topic d211 that identifiably displays topics with high affinity with the patient. In the case of FIG. 3, the searched peer support communities A to D are displayed in order of affinity with the patient. In addition, for the peer support community A, the affinity d110 is displayed with the notation "Affinity No. 1," and a topic d211 is displayed with the notation "Topic 1: Recurrence" and "Topic 2: Family History" that identifiably displays topics with high affinity with the patient. This allows the patient to easily recognize the peer support community with higher affinity to the patient, and to easily recognize which topic in the community has higher affinity to the patient.

[0063] (2) Peer support community details screen (see Figure 4) When the control unit 10 of the server device 2 detects a patient's selection (click, tap, etc.) of the peer support community list, it causes a peer support community detail screen displaying details of the target peer support community to be displayed on the user terminal device 3. For example, it causes the peer support community detail screen d30 shown in FIG.

[0064] The peer support community details screen d30 exemplarily displays topics d410 that identifiably display topics that have a high affinity with the patient. In the case of Fig. 4, the details screen of the peer support community A is displayed, and topics d410 that identifiably display topics that have a high affinity with the patient, such as "Topic 1: Recurrence" and "Topic 2: Family History", are displayed. By identifiably displaying topics that have a high affinity with the patient, the patient can instantly see the community that contains the topic that interests him or her.

[0065] The peer support community detail screen d30 may display a number of topics in the community ranked in order of affinity with the patient, as shown in Fig. 4. The peer support community detail screen d30 exemplarily displays a topic list d413 that displays a number of topics in the community ranked in order of affinity with the patient.

[0066] The peer support community detail screen d30 may display recommendation levels of multiple topics in the community based on the affinity between users and topics, as shown in Fig. 4. The peer support community detail screen d30 exemplarily displays recommendation levels d312 of multiple topics in the community.

[0067] The peer support community detail screen d30 may display a list of participating members of the community, as shown in Fig. 4. For example, the peer support community detail screen d30 displays a participating member list d313.

[0068] The peer support community details screen d30 may be provided with a save button d411 for saving a link to transition to the target peer support community details screen, a join button d412 for applying to join the target peer support community, and a button for transitioning to a screen for viewing the profiles and posts of the participating members of the target peer support community.

[0069] [Operation of information processing system] The operation of the information processing system 1 according to one embodiment of the present invention will be described with reference to FIG.

[0070] The input receiving means receives input of user information and importance by a patient (step S101).

[0071] The calculation means performs affinity calculation between the patient and the peer support community based on the input user information, importance, and a plurality of peer support community information related to the plurality of peer support communities, and calculates the affinity between the patient and the peer support community (step S102). For example, the calculation means searches for peer support communities by referring to a plurality of peer support community information related to the plurality of peer support communities based on the user information input by the patient, extracts the peer support communities searched based on the importance of the patient, and selects a peer support community with a high affinity. Here, the plurality of peer support community information related to the plurality of peer support communities is exemplified in FIG. 6, and may be stored in the storage unit 11 of the server device 2, for example.

[0072] The display control means controls the display according to the affinity between the patient and the peer support community based on the calculation result of the affinity (step S103). For example, the display control means causes the user terminal device 3 to display a recommended peer support community list screen that displays the peer support communities in order of the affinity.

[0073] 7, an example of a hardware configuration in which the above-mentioned server device 2 and terminal device 3 are realized by a computer 70 will be described. Note that the functions of each device can also be realized by dividing them into multiple devices.

[0074] As shown in FIG. 7, a computer 70 includes a processor 700 , a storage device 702 , an input I / F 704 , a data I / F 706 , a communication I / F 708 , and a display device 710 .

[0075] The processor 700 controls various processes in the computer 70 by executing programs stored in the storage device 702. For example, each functional unit included in the control unit of the server device 2 and the user terminal device 3 can be realized by the processor 700 executing the programs stored in the storage device 702.

[0076] The storage device 702 is a storage medium such as a random access memory (RAM), etc. The RAM temporarily stores the program code of the program executed by the processor 700 and data required when the program is executed.

[0077] The storage device 702 may also be a non-volatile storage medium such as a hard disk drive (HDD) or a flash memory. The storage device 702 stores an operating system and various programs for implementing the above-mentioned configurations. The storage medium storing the various programs may be a non-transitory computer readable medium. In addition, the storage device 702 may store a table for registering various information and a DB for managing the table. Such programs and data are loaded into the storage device 702 as necessary and referred to by the processor 700.

[0078] The input I / F 704 is a device for receiving input from a user. Specific examples of the input I / F 704 include a camera, a button, a microphone, a keyboard, a mouse, a touch panel, various sensors, and a wearable device. The input I / F 704 may be connected to the computer 70 via an interface such as a Universal Serial Bus (USB).

[0079] The data I / F 706 is a device for inputting data from outside the computer 70. A specific example of the data I / F 706 is a drive device for reading data stored in various storage media. The data I / F 706 may be provided outside the computer 70. In that case, the data I / F 706 is connected to the computer 70 via an interface such as a USB.

[0080] The communication I / F 708 is a device for performing data communication with an external device of the computer 70 via the communication network 5 in a wired or wireless manner. The communication I / F 708 may be provided outside the computer 70. In that case, the communication I / F 708 is connected to the computer 70 via an interface such as a USB.

[0081] The display device 710 is a device for displaying various types of information. Specific examples of the display device 710 include a liquid crystal display, an organic EL (Electro-Luminescence) display, and a display of a wearable device. The display device 710 may be provided outside the computer 70. In that case, the display device 710 is connected to the computer 70 via, for example, a display cable. In addition, when a touch panel is adopted as the input I / F 704, the display device 710 can be configured integrally with the input I / F 704.

[0082] The components of the server device 2 and the user terminal device 3 described in the above embodiment are assumed to realize a predetermined process in cooperation with other hardware by the processor 700 executing a program stored in the storage device 702. In other words, these components are assumed to be software or firmware, and also corresponding hardware, and in both concepts, they are also described as "functions," "means," "parts," "processing circuits," "units," or "modules," and can be interpreted as each of these.

[0083] [Effects of the embodiment] As described above, according to this embodiment, it is possible to provide a technology that supports more accurate matching with the peer support community that a patient desires.

[0084] For example, in one aspect, the computer includes an input receiving means for receiving input of user information about the user and a degree of importance of a matter to be emphasized from a user who is a patient, the user information including at least one of disease background information about the background of the user's disease, treatment background information about the background of the user's treatment, psychological background information about the mental state of the user, and attribute information indicating an attribute of the user, and a calculation means for calculating an affinity between the patient and the peer support community based on the user information, the degree of importance, and a plurality of peer support community information about a plurality of peer support communities, the calculation means comprising: The peer support community information includes information regarding multiple topics of the peer support community, and the affinity calculation includes calculating the similarity between the user information and the peer support community information. The system functions as a calculation means and a display control means that controls the display according to the affinity between the patient and the peer support community based on the affinity calculation result. Therefore, even if a patient has highly specific concerns such as the symptoms of a disease, treatment costs, or cosmetic concerns, the patient can easily find the peer support community he or she is looking for or a peer support community where he or she can talk to someone who can sympathize with the patient's situation and concerns, and can share his or her situation and concerns to reduce the psychological burden.

[0085] In one embodiment, the peer support communities are ranked in order of their affinity with the patient, so that the patient can efficiently identify the peer support community he or she desires from the list of searched peer support communities.

[0086] In one embodiment, the affinity calculation includes calculating the affinity between the patient and multiple topics of the peer support community, and the peer support community is displayed together with the topics of the peer support community according to the affinity between the patient and multiple topics of the peer support community, and topics that have a high affinity with the patient are displayed in an identifiable manner, so that the patient can instantly identify the topic he or she is looking for from the list of searched peer support communities.

[0087] In one embodiment, the affinity calculation includes performing a weighting process on the user information based on the importance, so that patients can increase the priority of the items that they consider important when finding a community, thereby achieving more accurate matching.

[0088] In one aspect, the affinity calculation includes performing a morphological analysis on the user information and the multiple peer support community information, calculating a feature vector corresponding to the user information and at least a portion of the multiple peer support community information based on the importance and the results of the morphological analysis, and calculating the similarity based on the calculated feature vector.Therefore, even if a patient has highly specific concerns such as symptoms of a disease, treatment costs, or cosmetic concerns, the patient can find peer support communities or topics that are highly relevant to the issues or keywords that the patient values.

[0089] In one aspect, the peer support community information further includes information regarding the profiles or content of messages from multiple participating members of the peer support community, so that patients can easily find peer support communities that have participating members who have experienced situations similar to their own, even if they have highly specific concerns such as symptoms of an illness, treatment costs, or cosmetic concerns.

[0090] The present invention is not limited to the above-described embodiment, and can be implemented in various other forms without departing from the scope of the present invention. Therefore, the above-described embodiment is merely an example in every respect, and should not be interpreted as being restrictive. For example, the order of each of the above-described processing steps can be arbitrarily changed or executed in parallel as long as no contradiction occurs in the processing content. [Explanation of symbols]

[0091] 1...information processing system, 2...server device, 3...user terminal device, 5...communication network, 10...control unit, 11...storage unit, 12...communication interface unit, 13...bus, 100...input receiving means, 101...calculation means, 102...output means, 102a...display control means,

Claims

1. Computer, an input receiving means for receiving input of user information about the user and a degree of importance of a matter to be emphasized from a user who is a patient, the user information including at least one of disease background information about a background of the user's disease, treatment background information about a background of the user's treatment, psychological background information about the user's mental state, and attribute information indicating an attribute of the user; A calculation means for calculating an affinity between the patient and the peer support community based on the user information, the importance, and a plurality of peer support community information related to a plurality of peer support communities, and calculating an affinity between the patient and the peer support community, the peer support community information including information on a plurality of topics of the peer support community, and the affinity calculation includes calculating a similarity between the user information and the peer support community information; A display control means for controlling a display according to the affinity between the patient and the peer support community based on the calculation result of the affinity; A program that functions as a

2. The patient is suffering from a chronic disease including at least one of cancer, leukemia, sarcoma, myeloma, stroke, myocardial infarction, hypertensive disease, diabetes, cirrhosis, chronic renal failure, depression, schizophrenia, and dementia; The program according to claim 1.

3. The patient is a cancer patient. The program according to claim 2.

4. the display control means displays the peer support communities in order of affinity with the patient. The program according to claim 1.

5. The affinity calculation includes calculating an affinity between a plurality of topics of the patient and the peer support community; the display control means displays the peer support community together with the topics of the peer support community according to the affinity between the patient and a plurality of topics of the peer support community, and displays topics having a high affinity with the patient in an identifiable manner; The program according to claim 1.

6. The affinity calculation includes performing a weighting process on the user information based on the importance. The program according to claim 1.

7. The affinity calculation includes: performing a morphological analysis on the user information and the plurality of pieces of peer support community information; calculating a feature vector corresponding to the user information and at least a part of the plurality of pieces of peer support community information based on the importance and a result of the morphological analysis; and calculating the similarity based on the calculated feature vector. The program according to claim 1.

8. The peer support community information further includes information regarding profiles or messages of a plurality of participating members of the peer support community. The program according to claim 1.

9. an input receiving unit that receives input of user information about the user and a level of importance of a matter to be emphasized from a user who is a patient, the user information including at least one of disease background information about a background of the user's disease, treatment background information about a background of the user's treatment, and attribute information indicating an attribute of the user; a calculation unit that performs an affinity calculation between the patient and the peer support community based on the user information, the importance, and a plurality of community information related to a plurality of peer support communities, and calculates an affinity between the patient and the peer support community, the peer support community information including information related to a plurality of topics of the peer support community, and the affinity calculation includes calculating a similarity between the user information and the peer support community information; A display control unit that controls a display according to the affinity between the patient and the peer support community based on a result of the affinity calculation; An information processing device comprising:

10. On the computer, A step of receiving input of user information about the user and a level of importance of a matter to be emphasized from a user who is a patient, the user information including at least one of disease background information about a background of the disease of the user, treatment background information about a background of the treatment of the user, and attribute information indicating an attribute of the user; a calculation unit for calculating an affinity between the patient and the peer support community based on the user information, the importance, and a plurality of community information related to a plurality of peer support communities, and calculating an affinity between the patient and the peer support community, the peer support community information including information on a plurality of topics of the peer support community, and the affinity calculation includes calculating a similarity between the user information and the peer support community information; A step of controlling a display according to the affinity between the patient and the peer support community based on the calculation result of the affinity; An information processing method.

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