JP7154675B1 - Medical Facility Referral System, Medical Facility Referral Method and Program - Google Patents

Abstract

The present invention determines the possibility of an oral disease and introduces a user to a medical facility suitable for its treatment. A medical facility introduction system that introduces a user to a medical facility suitable for treatment of an oral disease acquires an intraoral image of the user's oral cavity, analyzes the acquired intraoral image, The possibility of the oral disease is determined based on the analysis result, a medical facility suitable for treatment of the oral disease is specified based on the determination result, and the specified medical facility is introduced to the user. [Selection drawing] Fig. 1

Description

TECHNICAL FIELD The present invention relates to a technology effective in introducing medical facilities suitable for treatment of oral diseases.

In recent years, techniques related to intraoral diseases have attracted attention.
For example, Patent Literature 1 discloses a technique for classifying images of tooth surfaces for caries detection based on intraoral images.
In addition, Patent Literature 2 discloses a technique for diagnosing a disease in the user's oral cavity based on an intraoral image composed of a plurality of images representing a predetermined region in the oral cavity.

Japanese Patent Application Publication No. 2014-509908 JP 2019-155027 A

Some patients with oral diseases do not receive the necessary treatment.
Therefore, there is a demand for a technique for judging the possibility of oral disease and referring the patient to a medical facility suitable for the treatment.
However, with the techniques described in Patent Documents 1 and 2, it was not possible to determine the possibility of an oral disease and introduce the patient to a medical facility suitable for the treatment.

The inventor focused on the need for a medical facility referral system, a medical facility referral method, and a program that can determine the possibility of an oral disease and refer the user to a medical facility suitable for treatment.

Therefore, it is an object of the present invention to provide a medical facility referral system, a medical facility referral method, and a program that can determine the possibility of an oral disease and introduce the user to a medical facility suitable for the treatment. do.

The present invention is a medical facility introduction system that introduces a user to a medical facility suitable for treatment of oral diseases,
an intraoral image acquiring unit that acquires an intraoral image of the user's intraoral cavity;
an intraoral image analysis unit that analyzes the acquired intraoral image;
a determination unit that determines the possibility of the oral disease based on the analysis result;
an identification unit that identifies a medical facility suitable for treatment of the oral disease based on the determination result;
an introduction unit that introduces the specified medical facility to the user;
a medical facility community creation unit that creates the medical facility community;
a medical facility community invitation unit that invites the user to the introduced medical facility community;
To provide a medical facility referral system comprising:

According to the present invention, a medical facility introduction system that introduces a user to a medical facility suitable for treatment of an oral disease acquires an intraoral image of the user's oral cavity, and analyzes the acquired intraoral image. Then, based on the analysis results, the possibility of the oral disease is determined, based on the determination results, a medical facility suitable for treatment of the oral disease is identified, and the user is introduced to the identified medical facility. , creating a community of the medical facility and inviting the user to the introduced community of the medical facility .

Although the present invention is in the category of systems, the same actions and effects can be achieved with methods and programs.

ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to judge the possibility of an oral disease, and to introduce a user to the medical facility suitable for the treatment.

BRIEF DESCRIPTION OF THE DRAWINGS It is a figure explaining the outline|summary of the medical facility introduction system 1. FIG. 1 is a diagram showing a functional configuration of a medical facility introduction system 1; FIG. 2 is a diagram showing a flowchart of first determination processing executed by the medical facility introduction system 1. FIG. It is a figure which shows the example of an intraoral image. FIG. 10 is a diagram showing a flowchart of a second determination process executed by the medical facility introduction system 1; FIG. 4 is a diagram showing an example of an annotated intraoral image; FIG. 11 is a diagram showing a flowchart of a third determination process executed by the medical facility introduction system 1; FIG. 10 is a diagram showing a flowchart of a fourth determination process executed by the medical facility introduction system 1; 4 is a diagram showing a flowchart of medical facility referral processing executed by the medical facility referral system 1. FIG. FIG. 3 is a diagram showing a flowchart of a first identification process executed by the medical facility introduction system 1; FIG. 10 is a diagram showing a flowchart of a second identification process executed by the medical facility introduction system 1; FIG. 10 is a diagram showing a flowchart of a third specific process executed by the medical facility introduction system 1; FIG. 4 is a diagram showing a flowchart of community creation processing executed by the medical facility referral system 1. FIG. FIG. 4 is a diagram showing a flowchart of medical facility community invitation processing executed by the medical facility introduction system 1. FIG. It is a figure which shows the flowchart of the oral disease community invitation process which the medical facility introduction system 1 performs. 4 is a diagram showing a flowchart of participant detection processing executed by the medical facility introduction system 1. FIG. 4 is a diagram showing a flowchart of learning processing executed by the medical facility introduction system 1. FIG. FIG. 4 is a diagram showing a flowchart of treatment history provision processing executed by the medical facility referral system 1. FIG.

EMBODIMENT OF THE INVENTION Hereinafter, with reference to an accompanying drawing, the form (henceforth, embodiment) for implementing this invention is demonstrated in detail. In subsequent figures, the same numbers or symbols are attached to the same elements throughout the description of the embodiments.

[Basic Concept/Basic Configuration]
FIG. 1 is a diagram for explaining the outline of the medical facility referral system 1. As shown in FIG. The medical facility introduction system 1 includes at least a computer 10, and is a system that introduces users to medical facilities suitable for treatment of oral diseases. In this embodiment, in the medical facility referral system 1, a computer 10, a user terminal 20 owned by a user, and a medical facility terminal 21 managed by a medical facility that treats oral diseases are connected so as to be capable of data communication. .

Processing steps when the medical facility referral system 1 introduces a user to a medical facility suitable for an oral disease will be described with reference to FIG.

The computer 10 acquires an intraoral image of the user's intraoral cavity (step S1).
The intraoral image is an image captured with visible light, and includes, for example, an integrated upper and lower jaw image, an upper jaw single image, a lower jaw single image, a tooth single image, and an oral mucosa image.
The computer 10 acquires an intraoral image of the user's oral cavity taken by the user terminal 20 from the user terminal 20 that took the image, and an intraoral image of the user's oral cavity taken by an imaging device provided in the medical facility. is acquired via the medical facility terminal 21 managed by the medical facility, an intraoral image of the user's oral cavity is acquired.

The computer 10 analyzes the acquired intraoral image (step S2).
The computer 10 performs image analysis using AI (Artificial Intelligence) on the acquired intraoral image.

The computer 10 determines the possibility of oral disease based on the analysis results (step S3).
Oral diseases are, for example, caries, periodontal disease, intraoral tumors, and orthodontics. Determining the possibility of oral disease is, for example, determining the presence or absence of oral disease, and determining the ratio of oral disease, such as 0 to 100%.
The computer 10 determines the oral disease suffered by this user based on the analysis result.

The computer 10 identifies medical facilities suitable for treatment of oral disease based on the determination result (step S4).
The method for the computer 10 to identify this medical facility is, for example, by referring to a database in which the medical facility and the oral disease that this medical facility specializes in treatment are associated and registered in advance, and the oral disease determined this time Identify the medical facility associated with the , conduct a bid for each medical facility and identify the medical facility based on the bidding results, identify the medical facility based on the user's evaluation of each medical facility It is.

The computer 10 introduces the specified medical facility to the user (step S5).
The computer 10 transmits medical facility information (for example, name, location, telephone number, email address, website, department, reception hours, consultation hours, attending physician, access method) regarding the specified medical facility to the user terminal 20. .
The user terminal 20 receives the medical facility information and displays it on its own display unit or the like.
By browsing the medical facility information displayed by the user terminal 20, the user grasps the medical facility suitable for treatment of his or her oral disease.
As a result, the computer 10 introduces the specified medical facility to the user.

According to such a medical facility referral system 1, it is possible to determine the possibility of an oral disease and introduce the user to a medical facility suitable for treatment thereof.

[Function configuration]
Based on FIG. 2, the functional configuration of the medical facility referral system 1 will be described.
The medical facility introduction system 1 includes at least a computer 10, and the computer 10 includes user terminals 20 such as mobile phones, smartphones, tablet terminals, and personal computers owned by users, mobile phones, smartphones, tablet terminals managed by medical facilities, It is a system in which a medical facility terminal 21 such as a personal computer is connected via a network 9 such as a public line network so as to be capable of data communication.

The computer 10 is a computer or a personal computer having a server function that introduces a user to medical facilities suitable for treatment of oral diseases.
The computer 10 may be realized by, for example, one computer, or may be realized by a plurality of computers like a cloud computer. A cloud computer in this specification is a computer that uses any computer in a scalable manner to perform a specific function, or includes multiple functional modules to realize a certain system, and uses the functions in a free combination. It can be anything.

The computer 10 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), etc. as a control unit, and a communication unit to communicate with other terminals, devices, etc. It includes a device for enabling communication, an intraoral image acquisition unit 11 for acquiring intraoral images, an introduction unit 12 for introducing medical facilities, and the like.
The computer 10 also includes a data storage unit such as a hard disk, a semiconductor memory, a storage medium, or a memory card as a storage unit.
In addition, the computer 10 includes, as a processing unit, various devices that perform various processes, an intraoral image analysis unit 13 that analyzes intraoral images, a determination unit 14 that determines the possibility of oral disease, A specifying unit 15 or the like for specifying a medical facility is provided.

In the computer 10, the control unit reads a predetermined program, and cooperates with the communication unit to obtain an intraoral image acquisition module, an X-ray image acquisition module, a registration information acquisition module, a bid module, an evaluation acquisition module, and an introduction module. , an advice module, a regular visit schedule provision module, a medical facility community invitation module, an oral disease community invitation module, a service provision module, a treatment history acquisition module, a consent acceptance module, and a treatment history provision module.
Further, in the computer 10, the control unit reads a predetermined program, and cooperates with the storage unit to realize a treatment content registration module, an evaluation registration module, a community registration module, a participant registration module, and a learning result registration module. .
Further, in the computer 10, the control unit reads a predetermined program to cooperate with the processing unit to perform an intraoral image analysis module, a learning module, a determination module, an intraoral image annotation module, an X-ray image analysis module, an X Line image annotation module, identification module, judgment module, tabulation module, regular visit schedule creation module, medical facility community creation module, oral disease community creation module, posted content acquisition module, posted content analysis module, harmful participant detection module, exclusion module , a beneficial participant detection module, and an awarding module.

[First Determination Process Executed by Computer 10]
A first determination process executed by the computer 10 will be described with reference to FIG. This figure is a diagram showing a flowchart of the first determination process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is the details of the intraoral image acquisition process (step S1), the intraoral image analysis process (step S2), and the oral disease possibility determination process (step S3).

The intraoral image acquisition module acquires an intraoral image of the user's intraoral cavity (step S10).
As described above, the intraoral image is an image captured with visible light, and includes an integrated upper and lower jaw image, an upper jaw single image, a lower jaw single image, a tooth single image, an oral mucosa image, and the like (see FIG. 4).
The intraoral image acquisition module acquires this intraoral image from the user terminal 20 or the medical facility terminal 21 .
A user causes the user terminal 20 to capture an intraoral image of the user and transmit the captured intraoral image to the computer 10 . In addition, a medical worker working at the medical facility (for example, a dentist, a dental hygienist, a part-time worker) shoots the user's oral cavity with an imaging device provided in the medical facility, and the taken intraoral image is sent to the medical facility terminal 21. Send to The medical facility terminal 21 transmits this intraoral image to the computer 10 .
The intraoral image acquisition module acquires an intraoral image of the user's oral cavity by receiving the intraoral image.

The intraoral image analysis module analyzes the acquired intraoral image (step S11).
The intraoral image analysis module analyzes intraoral images by image analysis using AI.
A learning model used by AI will be described.
The learning module learns in advance by associating the intraoral image with the oral disease in the intraoral image, and generates a learning model. Oral diseases include caries, periodontal disease, intraoral tumors, orthodontics, etc., as described above. Learning performed by the learning module includes, for example, supervised learning, unsupervised learning, machine learning such as reinforcement learning, convolutional neural network, recurrent neural network, and deep learning using long/short-term memory.
The intraoral image analysis module applies this learning model to the acquired intraoral image to perform image analysis. As image analysis, the intraoral image analysis module analyzes the location where an oral disease is suspected and the content of the oral disease in the acquired intraoral image.

The determination module determines the possibility of oral disease based on the analysis results (step S12).
The determination of the possibility of oral disease is, as described above, determination of the presence or absence of oral disease and determination of the ratio of oral disease, such as 0 to 100%.
The determination module determines the possibility of an oral disease at each location based on the location suspected of having an oral disease and the content of the oral disease obtained by analyzing the intraoral image. A determination module determines one or more oral diseases at each location. The judgment module judges the single oral disease as a possible oral disease if only one oral disease exists as a possibility at each location. In addition, the judgment module, when there is a possibility of multiple oral diseases at each location, judges these multiple oral diseases as possible oral diseases, and combines the proportions of the possibilities of each oral disease to judge.

The above is the first determination process.

[Second Determination Processing Executed by Computer 10]
A second determination process executed by the computer 10 will be described with reference to FIG. This figure is a diagram showing a flowchart of the second determination process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is a modification of the first determination process described above.
Note that detailed descriptions of the same processes as those described above will be omitted.

The intraoral image acquisition module acquires an intraoral image of the user's intraoral cavity (step S20).
The processing of step S20 is the same as the processing of step S10 described above.

The intraoral image annotation module annotates the acquired intraoral image (step S21).
Annotations are, for example, marking, tagging, and labeling.
The intraoral image annotation module accepts an annotation input for a location where a medical worker or the like feels the possibility of an oral disease, and annotates the accepted location.
Alternatively, the intraoral image annotation module uses AI to annotate.
A learning model used by AI will be described.
The learning module learns in advance by associating intraoral images with locations to be annotated where there is a possibility of an oral disease, and generates a learning model.
The intraoral image annotation module uses this learning model to annotate. The intraoral image annotation module applies a learning model to the acquired intraoral image to annotate the possible oral disease locations in the intraoral image.
Note that the intraoral image annotation module can also be configured to annotate the acquired intraoral image by a method other than the method described above.

An example of an intraoral image annotated by the intraoral image annotation module will be described with reference to FIG. FIG. 6 is a diagram schematically showing an example of a state in which the intraoral image annotation module annotates each acquired intraoral image.
In FIG. 6, the intraoral image annotation module has added marks 30 to possible oral disease locations in the intraoral image. The intraoral image annotation module annotates the acquired intraoral image by applying annotations such as marks 30 to the intraoral image.

Returning to FIG. 5, the continuation of the second determination process will be described.
The intraoral image analysis module analyzes the annotated intraoral image (step S22).
The intraoral image analysis module analyzes the annotated intraoral image by image analysis using AI. The learning model used by AI in this process is the same as the learning model in the process of step S11 described above.
The intraoral image analysis module applies this learning model to the annotated intraoral image to perform image analysis. The intraoral image analysis module analyzes the content of the oral disease at the annotated location in the intraoral image as image analysis.

The determination module determines the possibility of oral disease based on the analysis results (step S23).
The judgment module judges the possibility of an oral disease at each annotated location based on the content of the oral disease obtained by analyzing the intraoral image. A determination module determines one or more oral diseases at each location. The judgment module judges the single oral disease as a possible oral disease if only one oral disease exists as a possibility at each location. In addition, the judgment module, when there is a possibility of multiple oral diseases at each location, judges these multiple oral diseases as possible oral diseases, and combines the proportions of the possibilities of each oral disease to judge.

The above is the second determination process.

[Third Determination Processing Executed by Computer 10]
A third determination process executed by the computer 10 will be described with reference to FIG. This figure is a diagram showing a flowchart of the third determination process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is a modification of the first determination process described above.
Note that detailed descriptions of the same processes as those described above will be omitted.

The intraoral image acquisition module acquires an intraoral image of the user's mouth (step S30), and the intraoral image analysis module analyzes the acquired intraoral image (step S31).
The process of step S30 is the same as the process of step S10 described above, and the process of step S31 is the same as the process of step S11 described above.

The X-ray image acquisition module acquires an X-ray image of the user's intraoral cavity (step S32).
An X-ray image is an image captured by X-rays, such as an upper and lower jaw integrated X-ray image, an upper jaw single X-ray image, a lower jaw single X-ray image, a tooth single X-ray image, an oral mucosa X-ray image, and the like.
An imaging device provided in the medical facility images the intraoral area of the user by a medical worker working at the medical facility, and transmits the captured X-ray image to the medical facility terminal 21 . The medical facility terminal 21 transmits this X-ray image to the computer 10 .
The X-ray image acquisition module acquires an X-ray image of the intraoral cavity of the user by receiving this X-ray image.

The X-ray image analysis module analyzes the acquired X-ray image (step S33).
The X-ray image analysis module analyzes the X-ray image by image analysis using AI.
A learning model used by AI will be described.
The learning module learns in advance by associating the X-ray image with the oral disease in the X-ray image, and generates a learning model.
The X-ray image analysis module applies this learning model to the acquired X-ray image to perform image analysis. As image analysis, the X-ray image analysis module analyzes the location suspected of having an oral disease and the content of the oral disease in the acquired X-ray image.

The judgment module judges the possibility of an oral disease based on the analysis result of the intraoral image and the analysis result of the X-ray image (step S34).
The determination module is based on the location where oral disease is suspected and the content of oral disease analyzed by intraoral image, and the location where oral disease is suspected and content of oral disease by analyzing X-ray image, Oral disease at each location determine the possibility of A determination module determines one or more oral diseases at each location. The judgment module judges the single oral disease as a possible oral disease if only one oral disease exists as a possibility at each location. In addition, the judgment module, when there is a possibility of multiple oral diseases at each location, judges these multiple oral diseases as possible oral diseases, and combines the proportions of the possibilities of each oral disease to judge.
At this time, the determination module, if the location where the oral disease is suspected is different or the content of the oral disease is different between the intraoral image and the X-ray image, based on one of the images, The probability of oral disease may be determined, the probability of oral disease may be determined based on both, respectively, and the percentage of the probability of oral disease in either image may be determined. Based on what is high, the likelihood of oral disease may be determined.

The above is the third determination process.

[Fourth determination process executed by computer 10]
A fourth determination process executed by the computer 10 will be described with reference to FIG. This figure is a diagram showing a flowchart of the fourth determination process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is a modification of the first determination process described above.
Note that detailed descriptions of the same processes as those described above will be omitted.

The intraoral image acquisition module acquires an intraoral image of the user's intraoral cavity (step S40), the intraoral image annotation module annotates the acquired intraoral image (step S41), and the intraoral image analysis module analyzes the annotated intraoral image (step S42), and the X-ray image acquisition module acquires an X-ray image of the user's intraoral cavity (step S43).
The process of step S40 is the same as the process of step S10 described above, the process of step S41 is the same as the process of step S21 described above, and the process of step S42 is the same as the process of step S22 described above. , the processing of step S43 is the same as the processing of step S32 described above.

The X-ray image annotation module annotates the acquired X-ray image (step S44).
The X-ray image annotation module accepts an annotation input for a location where a medical worker or the like suspects the possibility of an oral disease, and annotates the accepted location.
Alternatively, the X-ray image annotation module uses AI to annotate.
A learning model used by AI will be described.
The learning module learns in advance by associating X-ray images with locations to be annotated where there is a possibility of oral disease, and generates a learning model.
The X-ray image annotation module uses this learning model to annotate. The X-ray image annotation module applies a learning model to the acquired X-ray image to annotate the X-ray image where possible oral disease exists.
The X-ray image annotation module can also be configured to annotate the acquired X-ray image by a method other than the method described above.

The X-ray image analysis module analyzes the annotated X-ray image (step S45).
The X-ray image analysis module analyzes the annotated X-ray image by image analysis using AI. The learning model used by AI in this process is the same as the learning model in the process of step S33 described above.
The X-ray image analysis module applies this learning model to the annotated X-ray image to perform image analysis. The X-ray image analysis module analyzes the contents of the oral disease at the annotated location in this X-ray image as image analysis.

The judgment module judges the possibility of an oral disease based on the analysis result of the intraoral image and the analysis result of the X-ray image (step S46).
The judgment module determines the possibility of an oral disease at each location based on the content of the oral disease at each annotated location obtained by analyzing the intraoral image and the content of the oral disease at each annotated location obtained by analyzing the X-ray image. to decide. A determination module determines one or more oral diseases at each location. The judgment module judges the single oral disease as a possible oral disease if only one oral disease exists as a possibility at each location. In addition, the judgment module, when there is a possibility of multiple oral diseases at each location, judges these multiple oral diseases as possible oral diseases, and combines the proportions of the possibilities of each oral disease to judge.
At this time, if the annotated location is different between the intraoral image and the X-ray image, or if the content of the oral disease is different, the determination module determines whether the oral disease is based on one of the images. The probability may be determined, and the probability of oral disease may be determined based on both, respectively, and which of the images has a high percentage of the probability of oral disease. You may judge the possibility of an oral disease based on.

The above is the fourth determination process.

The medical facility referral system 1 executes the processes described later based on the possibility of oral disease determined by the first to fourth determination processes described above.

[Medical Facility Referral Processing Executed by Computer 10]
The medical facility referral process executed by the computer 10 will be described with reference to FIG. This figure is a diagram showing a flowchart of the medical facility referral process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is performed after the above-described first to fourth determination processes, and is the details of the above-described medical facility identification process (step S4) and medical facility introduction process (step S5).

The computer 10 executes medical facility identification processing (step S50).
The medical facility specifying process is a process executed by any one of first to third specifying processes described below or a combination of a plurality of them.
A medical facility identification process executed by the computer 10 will be described.

<First Specific Processing Executed by Computer 10>
A first specific process executed by the computer 10 will be described with reference to FIG. This figure is a diagram showing a flowchart of the first specific processing executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This processing is the details of the above-described medical facility identification processing (step S50).

The registration information acquisition module acquires the treatment details and medical facility information that the medical facility specializes in (step S500).
As described above, the medical facility information includes the name, location, telephone number, e-mail address, website, department, reception hours, consultation hours, doctor in charge, access method, and the like.
The registration information acquisition module acquires treatment details and medical facility information that the medical facility specializes in, from the medical facility terminal 21 or a database stored in an external server or the like.
The medical facility terminal 21 receives an input of information on oral disease treatment that the medical facility managing itself specializes in and medical facility information as information for registration. The medical facility terminal 21 transmits the received registration information to the computer 10 .
By receiving this registration information, the registration information acquisition module acquires the treatment details and medical facility information that the medical facility specializes in.
In addition, the registration information acquisition module accesses an external server or the like and acquires treatment details and medical facility information that the medical facility specializes in, which are stored in the external server or the like.

The treatment content registration module registers the treatment content of oral disease, which the medical facility specializes in, for each medical facility (step S501).
The treatment content registration module associates and registers the specialty treatment content for each medical facility based on the acquired treatment content that the medical facility is good at and the medical facility information.

It should be noted that the computer 10 can also be configured to previously perform the processes of steps S500 and S501 described above. In this case, the computer 10 executes only the process of step S502, which will be described later, during the first specifying process.

The identification module identifies the medical facility based on the registered treatment details and the judgment result (step S502).
The identification module identifies a medical facility based on the treatment content that the registered medical facility specializes in and the possibility of an oral disease determined by the first to fourth determination processes described above.
The identification module identifies medical facilities that specialize in this oral disease when only one oral disease has been determined as a possibility. At this time, if there is only one applicable medical facility, the identification module identifies this one medical facility, and if there are a plurality of applicable medical facilities, identifies these multiple medical facilities.
In addition, when the possibility of multiple oral diseases is determined, the identification module identifies a medical facility specializing in each oral disease. At this time, the identification module identifies this one medical facility when there is only one applicable medical facility for each oral disease, and identifies the plurality of medical facilities when there are multiple applicable medical facilities. do.

The above is the first identification process.

<Second Specific Processing Executed by Computer 10>
A second specific process executed by the computer 10 will be described with reference to FIG. 11 . This figure is a diagram showing a flowchart of the second specific processing executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This processing is the details of the above-described medical facility identification processing (step S50), which is different from the above-described first identification processing.

The bidding module submits a bid to a medical facility to treat an oral disease (step S510).
The bidding module transmits intraoral images and X-ray images from which oral diseases are determined to the medical facility terminal 21 .
The medical facility terminal 21 receives the intraoral image and the X-ray image, and displays them on its own display unit or the like. A person in charge of bidding (for example, a manager, a medical worker, an employee) can view this intraoral image or X-ray image, and if he or she wishes to receive treatment at his/her own medical facility, the user who has been determined to have this oral disease Bid against. When bidding, the medical facility terminal 21 transmits medical facility information and predetermined conditions (scheduled medical examination date and time, doctor in charge, etc.) to the computer 10 .
The bidding module receives the medical facility information and predetermined conditions to bid for the medical facility to treat the oral disease.

The judging module judges the result of the bid (step S511).
The judging module judges the result of the bidding based on the medical facility information of each bidding medical facility and predetermined conditions. A determination module determines the bidding medical facility for each oral disease.

The identification module identifies a medical facility based on the bidding result and the determination result (step S512).
The identification module identifies the medical facility based on the medical facility for each oral disease that determined the bidding result and the possibility of the oral disease determined by the first to fourth determination processes described above.
The identification module, if only one oral disease was determined as a possibility, identifies the medical facility that bid for this oral disease. At this time, if there is only one applicable medical facility, the identification module identifies this one medical facility, and if there are a plurality of applicable medical facilities, identifies these multiple medical facilities.
The identification module also identifies medical facilities that have bid for each oral disease, if the possibility of multiple oral diseases has been determined. At this time, the identification module identifies this one medical facility when there is only one applicable medical facility for each oral disease, and identifies the plurality of medical facilities when there are multiple applicable medical facilities. do.

The above is the second identification process.

<Third Specific Processing Executed by Computer 10>
A third specific process executed by the computer 10 will be described with reference to FIG. 12 . This figure is a diagram showing a flowchart of the third specific processing executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This processing is the details of the above-described medical facility identification processing (step S50), which is different from the above-described first and second identification processing.

The evaluation acquisition module acquires the evaluation of the medical facility and medical facility information from the user treated at the medical facility (step S520).
The evaluation is represented by numbers, symbols, characters, and the like. The evaluation of the medical facility is for the medical facility, the content of the treatment, the medical staff, and the like, which the user consulted.
The evaluation acquisition module acquires the evaluation of the medical facility introduced by the computer 10 through the medical facility introduction process (step S51), which will be described later.
The user terminal 20 accepts an input of evaluation for the medical facility visited. The user terminal 20 accepts, for example, a number from 1 to 5 as an evaluation of the medical facility. At this time, as the number increases, it means that the user gave a good evaluation. The user terminal 20 transmits the received evaluation and medical facility information of the medical facility to the computer 10 .
The evaluation obtaining module obtains the evaluation of the medical facility and the medical facility information from the user treated at the medical facility by receiving the evaluation and the medical facility information.

The aggregation module aggregates the acquired evaluations of medical facilities (step S521).
The tabulation module tabulates the acquired evaluations of medical facilities for each medical facility based on the medical facility information. If there are evaluations of medical facilities that have been aggregated in the past, the aggregation module aggregates the medical facilities acquired this time and aggregates the evaluations of each medical facility. At this time, the aggregation module may aggregate the evaluations of the medical facility as a whole, or may aggregate the evaluations of individual medical facilities, treatment details, medical staff, etc., as individual evaluations.
As an aggregation method, if the evaluation is the above-mentioned number, the aggregation module calculates the average value of the acquired evaluation of the medical facility, and performs a predetermined calculation such as aggregating the evaluation of the medical facility, or adds up the evaluation as it is. etc.

The evaluation registration module registers the aggregated evaluation of the medical facility (step S522).
The evaluation registration module registers aggregated evaluations for each medical facility.

It should be noted that the computer 10 can also be configured to perform the processes of steps S520 to S522 described above in advance. In this case, the computer 10 executes only the process of step S523, which will be described later, during the third specifying process.

The identifying module identifies the medical facility based on the aggregated evaluation of the medical facility and the judgment result (step S523).
The identification module identifies a medical facility based on the aggregated evaluation of the medical facility and the possibility of oral disease determined by the first to fourth determination processes described above.
If only one oral disease is determined as a possibility, the identification module identifies a medical facility whose aggregated evaluation satisfies predetermined conditions (highest evaluation, evaluation within a predetermined rank, etc.). At this time, if there is only one applicable medical facility, the identification module identifies this one medical facility, and if there are a plurality of applicable medical facilities, identifies these multiple medical facilities.
In addition, when the possibility of multiple oral diseases is determined, the specific module selects a medical facility that satisfies predetermined conditions (highest evaluation, evaluation within a predetermined order, etc.) aggregated for each oral disease. Identify. At this time, the identification module identifies this one medical facility when there is only one applicable medical facility for each oral disease, and identifies the plurality of medical facilities when there are multiple applicable medical facilities. do.

The above is the third identification process.

The computer 10 may execute any one of the above-described first to third identifying processes in the above-described medical facility identifying process (step S50) to be executed, or may perform any of the first to third identifying processes. You may perform the process which combined the plurality of.
The computer 10 may specify a medical facility based on the registered treatment details (first specifying process), the bidding result (second specifying process), and the judgment result, or may specify the registered treatment details. Based on the (first identification process), the aggregated medical facility evaluation (third identification process), and the judgment result, the medical facility may be identified, or the result of the bidding (second identification process ), the aggregate evaluation of the medical facility (third specifying process), and the judgment result, the medical facility may be specified, and the registered treatment content (first specifying process) and the bidding A medical facility may be specified based on the result (second specifying process), the aggregated medical facility evaluation (third specifying process), and the judgment result.

A case will be described where the computer 10 identifies medical facilities based on a plurality of combinations of the first to third identification processes.
For the first and second identification processes, the computer 10 identifies the bidding medical facility among the registered medical facilities that specialize in the determined oral disease. Alternatively, the computer 10 identifies a registered medical facility that specializes in this oral disease among the medical facilities that have bid on the determined oral disease.
In the case of the first and third identification processes, the computer 10 identifies medical facilities whose aggregated evaluation satisfies a predetermined condition among registered medical facilities that specialize in the determined oral disease. Alternatively, the computer 10 identifies a registered medical facility that specializes in the determined oral disease among the medical facilities whose aggregated evaluation satisfies a predetermined condition.
In the case of the second and third identification processes, the computer 10 identifies medical facilities whose evaluation satisfies predetermined conditions among the medical facilities that bid for the determined oral disease. Alternatively, the computer 10 identifies the medical facilities that bid, among the medical facilities whose aggregated evaluations satisfy predetermined conditions.
In the case of the first to third identification processes, the computer 10 identifies the medical facility that submitted the bid among the registered medical facilities that specialize in the determined oral disease, Identify medical facilities that meet the criteria for Alternatively, the computer 10 identifies those registered medical facilities that specialize in the determined oral disease, those whose evaluation satisfies a predetermined condition, and further identifies those medical facilities that have made bids. . Alternatively, the computer 10 identifies a registered medical facility that specializes in the determined oral disease among the medical facilities that have bid for the determined oral disease, and further among the registered medical facilities, the evaluation is Identify medical facilities that meet predetermined criteria. Alternatively, the computer 10 identifies, among the medical facilities that have bid for the determined oral disease, those medical facilities whose evaluation satisfies a predetermined condition, and among these medical facilities, registered that specializes in the determined oral disease. Identify medical facilities. Alternatively, the computer 10 identifies a medical facility whose evaluation satisfies a predetermined condition, identifies a registered medical facility that specializes in the determined oral disease from among these medical facilities, and identifies this oral cavity from among these medical facilities. Identify medical facilities that have bid on the disease. Alternatively, the computer 10 identifies a medical facility whose evaluation satisfies a predetermined condition, identifies a medical facility that has bid on the determined oral disease from among these medical facilities, and identifies a medical facility that is good at the determined oral disease from among these medical facilities. Identify the registered medical facility that

Returning to FIG. 9, the continuation of the medical facility referral process will be described.
The introduction module introduces the specified medical facility (step S51).
The referral module transmits medical facility information of the specified medical facility to the user terminal 20 . At this time, if there is only one specified medical facility, the referral module transmits the medical facility information of this one medical facility to the user terminal, and if there are multiple specified medical facilities, the plurality of medical facilities The medical facility information of the facilities is transmitted to the user terminal 20 in a list or in order.
The user terminal 20 receives this medical facility information and displays it on its own display unit or the like.
By browsing this medical facility information, the user grasps the medical facility suitable for him/herself.
The introduction module introduces the specified medical facility to the user by causing the user terminal 20 to display the medical facility information of the specified medical facility.
Note that the introduction module may introduce not only the medical facility but also the determined possibility of oral disease. Further, the content of the introduction module to introduce the medical facility to the user is not limited to the above example.

The advice module advises the user on home treatment based on the determination result (step S52).
Home treatments include, for example, use of toothpaste containing fluoride, use of dental floss, interdental brushes, liquid toothpaste, and mouthwash, use of gum containing xylitol, cleaning by brushing, and improvement of lifestyle habits.
The advice module refers to a database in which oral diseases and details of home treatment are associated and registered in advance, and specifies the details of home treatment associated with the oral disease determined this time. The advice module transmits the content of the identified home treatment to the user terminal 20 .
The user terminal 20 receives the content of this home treatment and displays it on its own display unit or the like.
By browsing the contents of this home treatment, the user can grasp the treatment method that can be performed before the user himself/herself consults a medical facility.
The advice module displays the content of the identified home treatment on the user terminal 20, and gives advice on the home treatment to the user based on the determination result.

The regular visit schedule creation module creates a regular visit schedule to the specified medical facility (step S53).
The regular visit schedule is a schedule of dates and times for the user to visit a medical facility.
The regular medical examination schedule creation module creates a regular medical examination schedule based on the specified medical facility's medical treatment date and time, reservation status, and the like. The regular visit schedule creation module may create a regular visit schedule for all specified medical facilities, and meet predetermined conditions (eg, the degree of oral disease determined, the appointment status of the medical facility at the most recent date and time). A regular visit schedule at a medical facility may be created.

The regular medical examination schedule providing module provides the created regular medical examination schedule to the user (step S54).
The regular medical examination schedule providing module transmits the created regular medical examination schedule to the user terminal 20 .
The user terminal 20 receives this regular medical examination schedule and displays it on its own display unit or the like.
The user grasps the regular medical examination schedule by browsing the regular medical examination schedule.
The regular visit schedule providing module provides the created regular visit schedule to the user by displaying the created regular visit schedule on the user terminal 20 .

The above is the medical facility referral processing.

[Community Creation Processing Executed by Computer 10]
Based on FIG. 13, the community creation process executed by the computer 10 will be described. This figure is a diagram showing a flow chart of the community creation process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process may be performed before each process described above is performed, and is at least a process performed before the community invitation process described later.

The medical facility community creating module creates a medical facility community (step S60).
A community is intended to be a predetermined website for participants, etc., to interact on specific purposes and topics, and allows participants to post comments, images, and the like.
The medical facility community creating module creates a community according to a predetermined format for each medical facility.

The oral disease community creation module creates an oral disease community (step S61).
The oral disease community creation module creates a community for each oral disease according to a predetermined format.

The community registration module registers the created community (step S62).
The community registration module registers the community by storing the created community in the storage unit.
The community registration module associates and registers the created medical facility community and the identifier (name, ID, management number, etc.) of the medical facility, and registers the created oral disease community and the oral disease identifier. Associate and register.

The above is the community creation process.

[Medical Facility Community Invitation Processing Executed by Computer 10]
Based on FIG. 14, the medical facility community invitation process executed by the computer 10 will be described. This figure is a diagram showing a flowchart of medical facility community invitation processing executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is a process performed after the community creation process described above.

The medical facility community invitation module invites the user to the community of the introduced medical facility (step S70).
The medical facility community invitation module invites the user, for whom the possibility of oral disease is determined by the first to fourth determination processes described above, to the community of the medical facility introduced by the medical facility introduction process described above. The invitation method performed by the medical facility community invitation module is, for example, a predetermined message and a community invitation URL (Uniform Resource Locator ), etc.
The medical facility community invitation module transmits this predetermined message and the community invitation URL to the user terminal 20 as an invitation message. At this time, the medical facility community invitation module transmits this invitation message to one or more user terminals 20 .
The user terminal 20 receives the invitation message and displays it on its own display unit or the like.
The user views the invitation message and enters the invitation URL to participate in the medical facility community.
The medical facility community invitation module invites the user to the introduced medical facility community by displaying this invitation message on the user terminal 20 .

The medical facility community invitation module invites the medical staff of the introduced medical facility to the community of the introduced medical facility (step S71).
The medical facility community invitation module invites medical personnel of the medical facility referred by the medical facility referral process described above to the community of the medical facility. The invitation method performed by the medical facility community invitation module is, for example, to send a predetermined message and community invitation URL etc. to the pre-registered email address, SNS, message application, chat application, etc. of the medical facility or medical worker. Such as.
The medical facility community invitation module transmits this predetermined message and community invitation URL as an invitation message to the medical facility terminal 21 and the medical worker terminal owned by the medical worker.
The medical facility terminal 21 and the medical staff terminal receive the invitation message and display it on their display unit or the like. The medical staff browses this invitation message and enters the invitation URL to participate in the community of the medical facility.
The medical facility community invitation module displays this invitation message on the medical facility terminal 21 or the medical staff terminal, thereby inviting the medical staff to the introduced medical facility community.

The participant registration module registers the participant with the community (step S72).
The participant registration module registers users and medical professionals who have responded to the invitation among the invited users and medical professionals in each community as participants.

The computer 10 accepts remarks, image submissions, etc. between users who have been introduced to the same medical facility, or between users and medical workers who work at the introduced medical facility. It promotes exchanges between users and exchanges between users and medical staff who work at medical facilities introduced to them.

The above is the medical facility community invitation processing.

[Oral Disease Community Invitation Processing Executed by Computer 10]
Based on FIG. 15, the oral disease community invitation process which the computer 10 performs is demonstrated. The same figure is a figure which shows the flowchart of the oral disease community invitation process which the computer 10 performs. Processing executed by each module described above will be described together with this processing. This process is a process performed after the community creation process described above.

The oral disease community invitation module invites the user to the determined oral disease community (step S80).
The oral disease community invitation module invites the user, who has determined the possibility of oral disease through the above-described first to fourth determination processes, to the community of the determined oral disease. The invitation method performed by the oral disease community invitation module is the same as for the user in the medical facility community invitation process described above.
The user views the invitation message and enters the invitation URL to participate in the oral disease community.
The oral disease community invitation module invites the user to the judged oral disease community by displaying this invitation message on the user terminal 20 .

The oral disease community invitation module invites the medical staff of the identified medical facility to the determined oral disease community (step S81).
The oral disease community invitation module invites the medical staff of the medical facility identified by the medical facility identification process (step S50) described above to the oral disease community determined by the first to fourth determination processes described above. . The invitation method performed by the oral disease community invitation module is the same as for the medical staff in the medical facility community invitation process described above.
A healthcare professional joins the oral disease community by viewing the invitation message and entering the invitation URL.
The oral disease community invitation module displays this invitation message on the medical facility terminal 21 or the medical worker terminal, thereby inviting the medical staff of the identified medical facility to the determined oral disease community.

The participant registration module registers the participant with the community (step S82).
The participant registration module registers users and medical professionals who have responded to the invitation among the invited users and medical professionals in each community as participants.

The computer 10 accepts remarks, image submissions, etc. between users determined to have the same oral disease or between users and medical professionals working at medical facilities that treat oral diseases determined to be the same oral disease. We aim to promote exchanges between users with diseases and exchanges between users and medical professionals who work at medical facilities that treat oral diseases.

The above is the oral disease community invitation processing.

[Participant Detection Processing Executed by Computer 10]
Participant detection processing executed by the computer 10 will be described with reference to FIG. 16 . FIG. 1 is a diagram showing a flowchart of participant detection processing executed by the computer 10. As shown in FIG. Processing executed by each module described above will be described together with this processing. This process is a process performed after the above-described medical facility community invitation process and oral disease community invitation process.

The posted content acquisition module acquires the posted content of the participant (step S90).
The content of the post is, for example, a statement or image posted in the above-described community.
The posted content acquisition module acquires the content posted to the community by each participant.

The posted content analysis module analyzes the acquired posted content (step S91).
The post content analysis module, for example, analyzes the frequency of each participant's remarks, pre-registered predetermined keywords in the remark content (e.g., slander, obscene, inappropriate content), effective treatment content, Analyze false content and personal information of participants.

The toxic participant detection module determines whether or not a toxic community participant is detected (step S92).
The harmful participant detection module detects participants who have a significantly low frequency of speaking (for example, participants who have never spoken after participating in the community, who have not spoken more than a predetermined number of times within a predetermined period of time, etc.) participants), participants who posted predetermined keywords, participants who posted their personal information, participants who posted false content, etc. are detected as harmful community participants.

If the harmful participant detection module detects a harmful community participant (step S92 YES), the exclusion module excludes the harmful community participant from the community (step S93).
The exclusion module removes the harmful community participant from the community by unregistering him from all communities in which he is currently participating. That is, if a community participant is detected to be a harmful community participant in a certain community, the exclusion module will Exclude this participant. In addition, the exclusion module removes anything this participant has previously posted in the community.
A participant excluded from a community cannot post comments, images, etc., view, etc. in the excluded community.
In addition, the computer 10 registers the detected harmful community participants, and in the subsequent medical facility community invitation processing and oral disease community invitation processing, the registered participants may not be invited to the community. It is possible.
After excluding the participant from the community, the computer 10 terminates this process.

On the other hand, if the harmful participant detection module has not detected a harmful community participant (step S92 NO), the beneficial participant detection module determines whether or not a beneficial community participant has been detected ( step S94).
Based on the analysis result of the content posted, the beneficial participant detection module detects participants whose utterance frequency is equal to or greater than a predetermined number of times (for example, participants whose utterances are equal to or greater than a predetermined number of times within a predetermined period of time), effective treatment content Detect participants, etc., who have posted, etc., as useful community participants.

If the beneficial participant detection module has not detected a beneficial participant (step S94 NO), the computer 10 terminates this process.

On the other hand, if the beneficial participant detection module detects a beneficial participant (step S94 YES), the granting module grants points to the beneficial community participant (step S95).
A method of giving points is, for example, linking points to each participant.
The granting module grants useful community participants points according to the content of comments based on the analysis results of the posted content. The granting module refers to a database or the like that associates content that is determined to be beneficial in advance with points to be granted, specifies points to be granted to a beneficial participant, and grants the specified points to this participant. .

The service providing module provides the participant with a service corresponding to the given points (step S96).
The services are, for example, oral care goods gifts and coupon issuance.
The service providing module refers to a database or the like that associates services with required points in advance, and identifies services corresponding to the given points. The service providing module may specify the service based only on the points granted this time, or may specify the service based on the sum of the points granted in the past that have not been consumed and the points granted this time. You may specify, and you may receive the input etc. from a participant, and may specify a service.
The service providing module provides the specified service to the participants. At this time, the service providing module consumes the points associated with this service from the points given to the participants. The service providing module executes processing necessary to provide the participants with services such as arranging gifts of oral care goods, issuing coupons, and arranging the issued coupons.

The above is the participant detection processing.

[Learning processing executed by computer 10]
Learning processing executed by the computer 10 will be described based on FIG. 17 . This figure is a diagram showing a flowchart of the learning process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is a process performed after the medical facility referral process described above. Using the result of this process, the computer 10 can perform the determination process of the possibility of an oral disease in the first to fourth determination processes after the next time.

The treatment history acquisition module acquires the user's treatment history at the introduced medical facility (step S100).
The medical facility terminal 21 at the introduced medical facility transmits the user's treatment history and identifier to the computer 10 .
The treatment history acquisition module acquires the user's treatment history at the introduced medical facility by receiving the user's treatment history and the identifier.

The learning module learns the treatment history (step S101).
The learning module associates this user's oral disease with the treatment history for this oral disease and learns to generate a learning model.

The learning result registration module registers the learning result (step S102).
The learning result registration module registers the learning result by storing the generated learning model.

The above is the learning process.

When the computer 10 executes the first to fourth determination processes from the next time onward, the computer 10 determines the possibility of an oral disease, taking into account the learning results.
In the first determination process, the determination module determines the possibility of an oral disease at each location based on the location suspected of having an oral disease and the details of the oral disease obtained by analyzing the intraoral image, and the learning result.
In the second determination process, the determination module determines the possibility of an oral disease at each annotated location based on the content of the oral disease obtained by analyzing the intraoral image and the learning result.
In the third determination process, the determination module includes a location where oral disease is suspected by analyzing the intraoral image and the content of the oral disease, a location where the oral disease is suspected by analyzing the X-ray image and the content of the oral disease, and learning Based on the results, determine the possibility of oral disease at each site.
In the fourth determination process, the determination module is based on the contents of the oral disease at each annotated location by analyzing the intraoral image, the contents of the oral disease at each annotated location by analyzing the X-ray image, and the learning result. to determine the likelihood of oral disease at each site.

[Treatment History Providing Processing Executed by Computer 10]
Based on FIG. 18, the treatment history providing process executed by the computer 10 will be described. This figure is a diagram showing a flow chart of the treatment history providing process executed by the computer 10 . Processing executed by each module described above will be described together with this processing. This process is a process performed after the medical facility referral process described above. The computer 10 can also be configured to use the result of this process to execute subsequent medical facility referral processes.
Note that detailed descriptions of the same processes as those described above will be omitted.

The treatment history acquisition module acquires the user's treatment history at the introduced medical facility (step S110).
The processing of step S110 is the same as the processing of step S100 described above.

The consent receiving module receives consent for providing the user's treatment history to other medical facilities (step S111).
The user terminal 20 receives an input as to whether or not consent is given to providing the user's treatment history to other medical facilities. The user terminal 20 transmits to the computer 10 the presence or absence of the accepted consent and the user's identifier.
The consent receiving module receives the presence or absence of the consent received and the identifier of the user. If the consent receiving module does not obtain consent, the computer 10 terminates this process.
The consent receiving module receives consent for providing the user's treatment history to other medical facilities when consent is obtained.

The treatment history providing module provides the acquired treatment history of the user to the next medical facility to be introduced to the user (step S113).
The treatment history providing module provides the acquired medical treatment history of the user to the referring medical facility when the above-described medical facility referral process is executed from the next time onward.
That is, after the computer 10 executes the process of introducing the identified medical facility (step S51), the treatment history provision module transmits the user's treatment history to the medical facility terminal 21 of the introduced medical facility. Thus, the acquired medical treatment history of the user is provided to the next medical facility to be introduced to the user.
The medical facility terminal 21 receives this user's treatment history.
When the user visits a medical facility, the medical staff can view the user's treatment history.

The above is the treatment history providing process.

The means and functions described above are realized by a computer (including a CPU, an information processing device, and various terminals) reading and executing a predetermined program. The program may be provided, for example, from a computer via a network (SaaS: software as a service) or provided as a cloud service. Also, the program may be provided in a form recorded on a computer-readable recording medium. In this case, the computer reads the program from the recording medium, transfers it to an internal recording device or an external recording device, records it, and executes it. Alternatively, the program may be recorded in advance in a recording device (recording medium) and provided from the recording device to the computer via a communication line.

Although the embodiments of the present invention have been described above, the present invention is not limited to these embodiments described above. Moreover, the effects described in the embodiments of the present invention are merely enumerations of the most suitable effects resulting from the present invention, and the effects of the present invention are limited to those described in the embodiments of the present invention. is not.

(1) A medical facility introduction system that introduces a user to a medical facility suitable for treatment of oral disease,
Intraoral image acquiring unit (for example, intraoral image acquisition Part 11, intraoral image acquisition module);
an intraoral image analysis unit (for example, an intraoral image analysis unit 13, an intraoral image analysis module) that analyzes the acquired intraoral image;
a determination unit (e.g., determination unit 14, determination module) that determines the possibility of the oral disease (e.g., caries, periodontal disease, intraoral tumor, orthodontics) based on the analysis results;
an identification unit (e.g., identification unit 15, identification module) that identifies a medical facility suitable for treatment of the oral disease based on the determination result;
an introducing unit (for example, an introducing unit 12, an introducing module) that introduces the specified medical facility to the user;
medical facility referral system.

According to the invention of (1), it is possible to determine the possibility of an oral disease and introduce the user to a medical facility suitable for the treatment.

(2) a medical facility community creation unit (for example, a medical facility community creation module) that creates the medical facility community;
a medical facility community invitation module (for example, a medical facility community invitation module) that invites the user to the introduced medical facility community;
The medical facility referral system according to (1), further comprising:

According to the invention of (2), since users can easily consult with each other, it is possible to introduce more appropriate medical facilities to the users.

(3) The medical facility community invitation unit invites the medical staff of the introduced medical facility to the community of the introduced medical facility.
The medical facility referral system according to (2).

According to the invention of (3), since consultation between the user and the medical staff can be easily performed, it is possible to introduce the user to a more appropriate medical facility.

(4) an oral disease community creation unit (for example, an oral disease community creation module) that creates the oral disease community;
an oral disease community invitation module (eg, an oral disease community invitation module) that invites the user to the determined oral disease community;
The medical facility referral system according to (1), further comprising:

According to the invention of (4), since users can easily consult with each other, it is possible to introduce more appropriate medical facilities to the users.

(5) The oral disease community invitation unit invites the identified medical staff of the medical facility to the determined oral disease community.
The medical facility referral system according to (4).

According to the invention of (5), since consultation between the user and the medical staff can be easily performed, it is possible to introduce the user to a more appropriate medical facility.

(6) Harmful participants of the community (for example, participants who have remarkably low frequency of speaking, participants who have posted predetermined keywords, participants who have posted their personal information, participants who have posted false content) a toxic participant detection unit (e.g., a toxic participant detection module) that detects
an exclusion unit (e.g., an exclusion module) that excludes the detected harmful community participant from the community;
The medical facility referral system according to any one of (2) to (5), further comprising:

According to the invention of (6), it becomes easier for the participants to communicate with each other more smoothly, and it becomes possible to introduce more appropriate medical facilities to the user.

(7) a useful participant detection unit (for example, useful participant detection module) and
a granting unit (eg, granting module) that grants points to the detected beneficial community participants;
a service providing unit (e.g., service providing module) that provides the participant with a service (e.g., gift of oral care goods, issuance of a coupon) according to the given points;
The medical facility referral system according to any one of (2) to (5), further comprising:

According to the invention of (7), it is possible to encourage participants to make useful remarks, and to introduce more appropriate medical facilities to the users.

(8) an evaluation acquisition unit (e.g., evaluation acquisition module) that acquires an evaluation of the medical facility from the user who received treatment at the introduced medical facility;
an aggregating unit (e.g., aggregating module) for aggregating the acquired evaluations of the medical facility;
further comprising
The identifying unit identifies the medical facility based on the aggregated evaluation of the medical facility and the judgment result.
The medical facility referral system according to (1).

According to the invention of (8), it is possible to introduce more appropriate medical facilities to the user.

(9) an annotation unit (e.g., annotation module) that annotates (e.g., marks, tags, labels) the acquired intraoral images;
further comprising
The intraoral image analysis unit analyzes the annotated intraoral image,
The medical facility referral system according to (1).

According to the invention of (9), since the accuracy of analysis can be improved, it is possible to introduce more appropriate medical facilities to the user.

(10) an advice unit (e.g., advice module) that executes home treatment advice to the user based on the judgment result;
The medical facility referral system according to (1), further comprising:

According to the invention of (10), it is also possible to prevent aggravation of oral diseases before visiting a medical facility to which the patient is referred.

(11) a treatment history acquisition unit (for example, a treatment history acquisition module) that acquires the user's treatment history at the introduced medical facility;
a treatment history providing unit (for example, a treatment history acquisition/providing module) that provides the acquired treatment history of the user to the medical facility to be introduced to the user next time;
The medical facility referral system according to (1), further comprising:

According to the invention of (11), it is also possible to receive more appropriate treatment at the introduced medical facility.

(12) a treatment history acquisition unit (for example, a treatment history acquisition module) that acquires the user's treatment history at the introduced medical facility;
a learning unit (for example, a learning module) that learns the acquired treatment history;
further comprising
The judgment unit judges the possibility of the oral disease by taking into account the results of learning.
The medical facility referral system according to (1).

According to the invention of (12), the accuracy of analysis can be improved, so that it is possible to introduce more appropriate medical facilities to the user.

(13) an X-ray image acquisition unit (for example, an X-ray image acquisition module) that acquires an X-ray image of the intraoral cavity of the user;
an X-ray image analysis unit (for example, an X-ray image analysis module) that analyzes the acquired X-ray image;
further comprising
The judgment unit judges the possibility of the oral disease based on the analysis result of the intraoral image and the analysis result of the X-ray image.
The medical facility referral system according to (1).

According to the invention of (13), in addition to the image of the intraoral surface photographed by a normal imaging device, the analysis accuracy is improved by using the X-ray image of the surface other than the intraoral surface. Therefore, it is possible to introduce a more appropriate medical facility to the user.

(14) a registration unit (for example, a treatment content registration module) for registering treatment details for the oral disease that the medical facility is good at;
further comprising
The identifying unit identifies the medical facility based on the registered treatment content and the judgment result.
The medical facility referral system according to (1).

According to the invention of (14), it is possible to improve the accuracy of identifying a medical facility, so that it is possible to introduce a more appropriate medical facility to the user.

(15) a bidding unit (e.g., a bidding module) for bidding the medical facility to treat the oral disease;
further comprising
The identifying unit identifies the medical facility based on the bidding result and the judgment result.
The medical facility referral system according to (1).

According to the invention of (15), it is possible to introduce a more appropriate medical facility to the user by specifying the medical facility where the user desires treatment.

(16) a schedule creation unit (eg, a schedule creation module) that creates a schedule for regular visits to the specified medical facility;
a schedule providing unit (for example, a schedule providing module) that provides the user with the created regular medical examination schedule;
The medical facility referral system according to (1), further comprising:

According to the invention of (16), it is possible to introduce more appropriate medical facilities to the user.

(17) A computer-executed medical facility referral method for referring a user to a medical facility suitable for treatment of an oral disease, comprising:
a step of acquiring an intraoral image of the user's oral cavity (for example, step S10);
a step of analyzing the acquired intraoral image (for example, step S11);
a step of determining the possibility of the oral disease based on the analysis results (for example, step S12);
a step of identifying a medical facility suitable for treatment of the oral disease based on the determination result (for example, step S50);
a step of introducing the identified medical facility to the user (for example, step S51);
A medical facility referral method comprising:

(18) to a computer that refers the user to medical facilities suitable for treatment of oral disease;
obtaining an intraoral image of the user's oral cavity (for example, step S10);
a step of analyzing the acquired intraoral image (for example, step S11);
a step of determining the possibility of oral disease based on the analysis results (for example, step S12);
identifying a medical facility suitable for treatment of the oral disease based on the judgment result (for example, step S50);
a step of introducing the specified medical facility to the user (for example, step S51);
A computer readable program for executing

1 medical facility introduction system 9 network 10 computer 11 intraoral image acquisition unit 12 introduction unit 13 intraoral image analysis unit 14 determination unit 15 identification unit 20 user terminal 21 medical facility terminal 30 mark

Claims (19)

A medical facility referral system that introduces a user to a medical facility suitable for treatment of an oral disease,
an intraoral image acquiring unit that acquires an intraoral image of the user's intraoral cavity;
an intraoral image analysis unit that analyzes the acquired intraoral image;
a determination unit that determines the possibility of the oral disease based on the analysis result;
an identification unit that identifies a medical facility suitable for treatment of the oral disease based on the determination result;
an introduction unit that introduces the specified medical facility to the user;
a medical facility community creation unit that creates the medical facility community;
a medical facility community invitation unit that invites the user to the introduced medical facility community;
medical facility referral system. A medical facility referral system that introduces a user to a medical facility suitable for treatment of an oral disease,
an intraoral image acquiring unit that acquires an intraoral image of the user's intraoral cavity;
an intraoral image analysis unit that analyzes the acquired intraoral image;
a determination unit that determines the possibility of the oral disease based on the analysis result;
an identification unit that identifies a medical facility suitable for treatment of the oral disease based on the determination result;
an introduction unit that introduces the specified medical facility to the user;
an oral disease community creation unit that creates the oral disease community;
an oral disease community invitation unit that invites the user to the determined oral disease community;
medical facility referral system. The medical facility community invitation unit invites the medical staff of the introduced medical facility to the community of the introduced medical facility,
The medical facility referral system according to claim 1 . The oral disease community invitation unit invites the identified medical staff of the medical facility to the determined oral disease community,
The medical facility referral system according to claim 2 . a harmful participant detection unit that detects harmful participants of the community;
an exclusion unit that excludes the detected harmful community participant from the community;
The medical facility referral system according to claim 1 or 2, further comprising: a beneficial participant detection unit that detects beneficial participants in the community; and a granting unit that provides points to the detected beneficial community participants;
a service providing unit that provides the participant with a service corresponding to the given points;
The medical facility referral system according to claim 1 or 2, further comprising: an evaluation acquisition unit that acquires an evaluation of the medical facility from the user who received treatment at the introduced medical facility;
and an aggregation unit that aggregates the acquired evaluation of the medical facility,
The identifying unit identifies the medical facility based on the aggregated evaluation of the medical facility and the judgment result.
The medical facility referral system according to claim 1 or 2. an annotation unit that annotates the acquired intraoral image;
further comprising
The intraoral image analysis unit analyzes the annotated intraoral image,
The medical facility referral system according to claim 1 or 2. an advice unit that advises the user on home treatment based on the judgment result;
The medical facility referral system according to claim 1 or 2, further comprising: a treatment history acquisition unit that acquires the user's treatment history at the introduced medical facility;
a treatment history providing unit that provides the acquired treatment history of the user to the medical facility to be introduced to the user next time;
The medical facility referral system according to claim 1 or 2, further comprising: a treatment history acquisition unit that acquires the user's treatment history at the introduced medical facility;
a learning unit that learns the acquired treatment history;
further comprising
The judgment unit judges the possibility of the oral disease by taking into account the results of learning.
The medical facility referral system according to claim 1 or 2. an X-ray image acquisition unit that acquires an X-ray image of the intraoral cavity of the user;
an X-ray image analysis unit that analyzes the acquired X-ray image;
further comprising
The judgment unit judges the possibility of the oral disease based on the analysis result of the intraoral image and the analysis result of the X-ray image.
The medical facility referral system according to claim 1 or 2. a registration unit that registers treatment details for the oral disease that the medical facility is good at;
further comprising
The identifying unit identifies the medical facility based on the registered treatment content and the judgment result.
The medical facility referral system according to claim 1 or 2. a bidding unit for bidding the medical facility to treat the oral disease;
further comprising
The identifying unit identifies the medical facility based on the bidding result and the judgment result.
The medical facility referral system according to claim 1 or 2. a schedule creation unit that creates a schedule for regular visits to the specified medical facility;
a schedule providing unit that provides the user with the created regular medical examination schedule;
The medical facility referral system according to claim 1 or 2, further comprising: A computer-implemented medical facility referral method for referring a user to a medical facility suitable for treatment of an oral disease, comprising:
obtaining an intraoral image of the user's oral cavity;
analyzing the acquired intraoral image;
a step of determining the possibility of the oral disease based on the analysis results;
Identifying a medical facility suitable for treatment of the oral disease based on the determination result;
introducing the user to the identified medical facility;
creating a community of said medical facilities;
inviting the user to the referral community of the medical facility;
A medical facility referral method comprising: A computer-implemented medical facility referral method for referring a user to a medical facility suitable for treatment of an oral disease, comprising:
obtaining an intraoral image of the user's oral cavity;
analyzing the acquired intraoral image;
a step of determining the possibility of the oral disease based on the analysis results;
Identifying a medical facility suitable for treatment of the oral disease based on the determination result;
introducing the user to the identified medical facility;
creating the oral disease community;
inviting the user to the determined oral disease community;
A medical facility referral method comprising: A computer that introduces the user to medical facilities suitable for treatment of oral diseases,
obtaining an intraoral image of the user's oral cavity;
analyzing the acquired intraoral image;
determining the possibility of the oral disease based on the analysis results;
Identifying a medical facility suitable for treatment of the oral disease based on the determination result;
introducing the user to the identified medical facility;
creating a community of said medical facilities;
inviting the user to the referral community of the medical facility;
A computer readable program for executing A computer that introduces the user to medical facilities suitable for treatment of oral diseases,
obtaining an intraoral image of the user's oral cavity;
analyzing the acquired intraoral image;
determining the possibility of the oral disease based on the analysis results;
Identifying a medical facility suitable for treatment of the oral disease based on the determination result;
introducing the user to the identified medical facility;
creating said oral disease community;
inviting the user to the determined oral disease community;
A computer readable program for executing

Images