JP2022038639A - Diagnosis support apparatus - Google Patents

Abstract

To determine the condition of the skin of an analyte and perform a diagnosis support operation suitable for the condition.SOLUTION: A diagnosis support apparatus according to embodiments comprises a reception unit, a determination unit, and a diagnosis support unit. The reception unit receives input of a captured image of a skin of an analyte. The determination unit determines the condition of the skin on the basis of the image. The diagnosis support unit executes a diagnosis support operation which reports, to a reporting destination corresponding to a result of the destination by the determination unit, the result of the determination or a report content corresponding to the result of the determination.SELECTED DRAWING: Figure 3

Description

The embodiments disclosed in the present specification and the like relate to a diagnostic support device.

Conventionally, in medical facilities such as clinics, patients with various symptoms are diagnosed. For example, in a clinic, a disease occurring on the skin of a subject is also diagnosed.

Further, a technique capable of diagnosing a disease name or the like from an image of the skin of a subject imaged by using an image pickup device such as a camera has appeared. For example, a technique has been proposed that can diagnose a skin disease such as melanoma by analyzing an image of the skin.

On the other hand, in recent years, regional medical cooperation has been promoted in which medical institutions cooperate with each other. For example, when a clinic determines that a detailed examination or the like is necessary, the subject such as a patient is transferred to a core hospital.

By the way, although the initial diagnosis of a skin disease is generally received at a clinic, there are some serious diseases that are difficult to distinguish at the clinic because of symptoms similar to other diseases. For example, severe drug eruption that presents with aggravation is difficult to distinguish in the clinic because the early skin symptoms are very similar to mild drug eruption, and it is desirable to undergo a detailed examination at the hospital for accurate diagnosis.

However, in the conventional medical cooperation system, the diagnosis in the clinic is generally performed by a medical worker such as a doctor. In addition, since the transfer to the hospital is entrusted to the medical staff of the clinic, if the above-mentioned serious illness cannot be identified, the symptoms may become severe due to the delay in contacting the hospital.

Japanese Unexamined Patent Publication No. 2016-174728

One of the problems to be solved by the embodiments disclosed in the present specification and the like is to determine the skin condition of the subject and to carry out a diagnostic support operation suitable for the condition. However, the problems solved by the embodiments disclosed in the present specification and the like are not limited to the above problems. The problem corresponding to each effect by each configuration shown in the embodiment described later can be positioned as another problem solved by the embodiment disclosed in the present specification.

The diagnostic support device according to the embodiment includes a reception unit, a determination unit, and a diagnostic support unit. The reception unit accepts the input of an image of the skin of the subject. The determination unit determines the condition of the skin based on the image. The diagnosis support unit executes a diagnosis support operation of notifying the notification destination according to the determination result of the determination unit of the determination result or the notification content according to the determination result.

FIG. 1 is a diagram showing a configuration example of a diagnostic support system according to an embodiment. FIG. 2 is a diagram showing an example of the configuration of the diagnostic support device according to the embodiment. FIG. 3 is a diagram showing an example of components included in the processing circuit of the diagnostic support device according to the embodiment. FIG. 4 is a diagram showing an example of a skin image according to an embodiment. FIG. 5 is a diagram schematically showing the state of the skin surface shown in the skin image according to the embodiment. FIG. 6 is a diagram showing an example of setting information related to the diagnosis support operation performed by the support function of the embodiment. FIG. 7 is a diagram showing an example of setting information related to the diagnosis support operation performed by the support function of the embodiment. FIG. 8 is a diagram showing an example of setting information related to the diagnosis support operation performed by the support function of the embodiment. FIG. 9 is a flowchart showing an example of processing performed by the diagnostic support device of the embodiment. FIG. 10 is a diagram showing a configuration example of the diagnostic support system according to the first modification of the embodiment.

Hereinafter, embodiments of the diagnostic support device will be described with reference to the drawings.

FIG. 1 is a diagram showing a configuration example of a diagnostic support system according to an embodiment. As shown in FIG. 1, the diagnosis support system 1 includes a clinic terminal 10, a hospital terminal 20, and a diagnosis support device 30.

The clinic terminal 10, the hospital terminal 20, and the diagnosis support device 30 are communicably connected via the network N1. The network N1 may be configured by a closed local network between the clinic H1 and the hospital H2, or may be a network via the Internet.

The clinic terminal 10 is a terminal device installed in the clinic H1. The clinic terminal 10 is a device for inputting and browsing various information by medical staff such as doctors and laboratory technicians working in the clinic H1. For example, the clinic terminal 10 is realized by a personal computer (PC), a tablet PC, a PDA (Personal Digital Assistant), a smartphone having a camera function, or the like.

Further, the clinic H1 is provided with an image pickup device 11. The image pickup apparatus 11 is mainly used for imaging the skin of a subject. For example, the image pickup apparatus 11 is realized by a dermoscopy (or dermoscope), a digital camera, or the like. Further, the image pickup device 11 may be a camera included in a portable device such as a smartphone.

The clinic terminal 10 responds to the operation of the medical staff, and has an image of the skin of the subject (hereinafter, also referred to as a skin image) imaged by the image pickup apparatus 11, test love information regarding the subject, and image information regarding the skin image. The determination information including the above is transmitted to the diagnosis support device 30. The test love information and the image information are examples of additional information.

Here, the method of transferring the skin image from the image pickup apparatus 11 to the clinic terminal 10 is not particularly limited. For example, the transfer of the skin image from the image pickup apparatus 11 to the clinic terminal 10 is automatically or automatically performed via an in-hospital network provided in the clinic H1, a medical image management system (PACS: Picture Archiving and Communication System), or the like. It may be done manually.

The subject information is information about the subject acquired at the clinic H1. For example, the subject information includes personal information such as the subject's name, age, gender, and address, as well as information such as a patient ID, a test result at the clinic H1, and a diagnosis result. Here, the patient ID is an example of identification information that can uniquely identify a subject. A unique identifier within the clinic H1 or a unique identifier between the clinic H1 and the clinic H1 is assigned to the patient ID. The subject information may be manually input by the medical staff, or may be acquired from an electronic medical record system or the like provided in the clinic H1.

The image information includes information on the skin image, information on the image pickup apparatus 11 that has captured the skin image, and the like. For example, the image information includes information indicating, as information on the skin image itself, the image taken on the day of onset, which part of the subject was taken, and the like. Further, for example, as the image information, examples of the information regarding the image pickup device 11 include the type of the image pickup device 11 (dermoscopy, digital camera, smartphone, etc.), image size, and the like.

The information about the skin image itself may be manually input by the medical staff, or may be obtained from an electronic medical record system or the like provided in the clinic H1. Further, the information about the image pickup device 11 may be manually input by the medical staff or may be acquired from the image pickup device 11. Further, the information regarding the image pickup apparatus 11 may be in a form accompanied by a skin image.

The hospital terminal 20 is a terminal device installed in the hospital H2. The hospital terminal 20 is a device in which various information is input, browsed, and the like by medical staff such as doctors and laboratory technicians working in the hospital H2. For example, the hospital terminal 20 is realized by a personal computer, a tablet PC, a PDA, a mobile phone, or the like.

In the present embodiment, the hospital terminal 20 also functions as a reception terminal that accepts reservations and the like for examinations performed at the hospital H2. When the hospital terminal 20 receives a request for an examination reservation from an external device such as a diagnostic support device 30 connected via the network N1, the hospital terminal 20 sends information about the subject to be reserved to a hospital information system (HIS) or the like. By registering, you can make an inspection appointment.

In the diagnosis support system 1, the clinic H1 and the hospital H2 are assumed to have a relationship of, for example, regional medical cooperation. Specifically, if it is determined that a detailed examination or the like is necessary at the clinic H1, it is possible to request a detailed examination from the hospital H2. That is, the hospital H2 is a medical institution capable of performing more advanced examinations and treatments than the clinic H1.

The diagnosis support device 30 is an example of the diagnosis support device. The diagnosis support device 30 determines the condition of the skin of the subject based on the determination information transmitted from the clinic terminal 10, and according to the determination result, the subject is subjected to the clinic terminal 10 or the hospital terminal 20. Perform diagnostic support actions. For example, the diagnostic support device 30 is realized by a computer device such as a server or a workstation.

FIG. 2 is a diagram showing an example of the configuration of the diagnostic support device 30 according to the present embodiment. As shown in FIG. 2, the diagnostic support device 30 includes an input interface 31, a display 32, a storage circuit 33, a communication interface 34, and a processing circuit 35.

The input interface 31 converts the input operation received from the operator into an electric signal and outputs it to the processing circuit 35. For example, the input interface 31 is a trackball, a switch button, a mouse, a keyboard, a touch pad for performing an input operation by touching an operation surface, a touch screen in which a display screen and a touch pad are integrated, and a non-optical sensor. It is realized by an input device such as a contact input interface and a voice input interface. The input interface 31 may be a control circuit such as a connection interface that receives an electronic signal corresponding to the operation from an operation device provided separately from the diagnosis support device 30.

The display 32 displays various information and various images output from the processing circuit 35. For example, the display 32 is realized by a display device such as an organic EL (Electro Luminescence) monitor, a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, and a touch panel. For example, the display 32 displays a GUI (Graphical User Interface) for receiving an operator's instruction, various display image data, and various processing results by the processing circuit 35.

The storage circuit 33 is connected to the processing circuit 35 and stores various data. For example, the storage circuit 33 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, or the like.

The communication interface 34 is connected to the processing circuit 35, and controls the transmission and communication of various data performed with external devices such as the clinic terminal 10 and the hospital terminal 20 via the network N1. More specifically, the communication interface 34 receives various information from the external device and outputs the received information to the processing circuit 35. Further, the communication interface 34 transmits various information input from the processing circuit 35 to the external device. For example, the communication interface 34 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like.

The processing circuit 35 controls each component of the diagnostic support device 30. For example, the processing circuit 35 is realized by a processor. Further, as shown in FIG. 3, the processing circuit 35 according to the present embodiment has a reception function 351 and a check function 352, an estimation function 353, a reject function 354, a storage function 355, a processing function 356, a determination function 357, and a support function. It has a 358.

Here, FIG. 3 is a diagram showing an example of components included in the processing circuit 35 of the diagnostic support device 30. For example, each of the reception function 351 and the check function 352, the estimation function 353, the reject function 354, the storage function 355, the processing function 356, the determination function 357, and the support function 358, which are the components of the processing circuit 35 shown in FIG. The processing function is stored in the storage circuit 33 in the form of a program that can be executed by a computer. The processing circuit 35 is a processor that realizes a function corresponding to each program by reading each program from the storage circuit 33 and executing the program. In other words, the processing circuit 35 in the state where each program is read out has each function shown in the processing circuit 35 of FIG.

In FIG. 3, a single processing circuit 35 realizes a reception function 351, a check function 352, an estimation function 353, a reject function 354, a storage function 355, a processing function 356, a determination function 357, and a support function 358. Although described as such, a plurality of independent processors may be combined to form a processing circuit 35, and each processor may execute a program to realize a function. Further, each processing function of the processing circuit 35 may be appropriately distributed or integrated into a single or a plurality of processing circuits.

Further, the processing circuit 35 may realize the function by using the processor of the external device connected via the network N1. For example, the processing circuit 35 reads a program corresponding to each function from the storage circuit 33 and executes it, and also uses a server group (cloud) connected to the diagnostic support device 30 via the network N1 as a computational resource. , Each function shown in FIG. 3 is realized.

The determination information storage unit 331 shown on the outside of the processing circuit 35 in FIG. 3 is realized by a part of the storage area of the storage circuit 33. Further, in FIG. 3, in order to explain the input / output of information to the processing circuit 35, the network N1 is shown in a form in which the communication interface 34 is omitted.

The reception function 351 is an example of the reception unit. The reception function 351 accepts the input of the skin image of the subject from the clinic terminal 10 via the communication interface 34. Specifically, the reception function 351 receives the information (skin image, subject information, image information) of the determination information estimation unit transmitted from the clinic terminal 10.

The check function 352 is an example of an inspection unit. The check function 352 checks (determines) whether or not the skin image received by the reception function 351 satisfies the requirements (hereinafter, also referred to as determination requirements) related to the determination of the determination function 357 described later. Here, the determination requirement means the requirement of the element necessary for determining the condition of the skin from the skin image. For example, the determination requirement includes the skin image itself, the image quality (color, brightness, contrast, etc.) of the skin image and the like.

Further, when the determination function 357 described later makes a determination using the elements included in the subject information and the image information, the check function 352 checks whether or not the determination requirements are satisfied for these elements as well. .. In this case, for example, the determination requirements include the image pickup site of the subject, the type of the image pickup device, the image size, and the like, as well as the time from the onset.

The check function 352 compares the determination information with the determination requirement, and determines whether or not the element included in the determination information satisfies the determination requirement. Here, when it is determined that the determination requirement is satisfied, the check function 352 outputs the determination information to the storage function 355.

Further, when it is determined that the determination requirement is not satisfied, the check function 352 further determines whether or not the insufficient requirement (element lacking in the determination information) is only the above-mentioned image size. For example, when the image is taken with a digital camera or a smartphone, the image size of the skin image may be unknown.

Here, if there is a missing requirement other than the image size, the check function 352 notifies the reject function 354 of the missing requirement and suppresses the output of the determination information to the storage function 355. Further, when the insufficient requirement is only the image size, the check function 352 outputs the skin image to the estimation function 353, so that the estimation function 353 estimates the image size.

The estimation function 353 is an example of an estimation unit. The estimation function 353 estimates the image size of the skin image based on the size of the skin field represented in the skin image. Hereinafter, the operation of the estimation function 353 will be described with reference to FIGS. 4 and 5.

FIG. 4 is a diagram showing an example of a skin image. The skin image G1 shown in FIG. 4 shows the state of the skin on which the rash G11 appears.

The estimation function 353 analyzes the skin image G1 and measures the size of the skin field (skin field area) represented by the skin image G1. As shown in FIG. 5, the skin field means a region portion of the skin hill G13 divided into polygons such as triangles and rhombuses by the skin groove G12 existing on the skin surface. Here, FIG. 5 is a diagram schematically showing the state of the skin surface shown in the skin image.

The region on the skin image G1 to be measured is not particularly limited, and may be, for example, a region where the rash G11 does not exist or a region where the rash G11 appears. Also. The estimation function 353 may enlarge (or reduce) the skin image G1.

Generally, the area of the skin field is characterized by having an almost constant value (about 0.08 mm ² ) regardless of age and gender. Therefore, the estimation function 353 estimates the size of the entire skin image G1, that is, the image size, based on the skin area measured from the skin image G1 based on this feature. For example, the estimation function 353 estimates the image size of the skin image G1 by multiplying the reciprocal of the ratio of the skin area to the total area of the skin image G1 by the above-mentioned constant value. Further, when the skin image G1 is enlarged (or reduced), the estimation function 353 estimates the image size in consideration of the magnification.

The unit of the image size estimated by the estimation function 353 is not particularly limited as long as it is a unit that can be handled by the determination function 357 described later, and may be a unit such as a pixel or a dpi (dots per inchi).

Further, in the above-mentioned operation example, the image size of the entire skin image G1 is estimated as the image size, but the present invention is not limited to this, and the image size of the main subject portion included in the skin image G1 is estimated. May be good. For example, the estimation function 353 may estimate the image size of the rash G11 represented by the skin image G1. Further, in this case, the estimation function 353 may estimate the minimum image size and the maximum image size of the rash G11.

Returning to FIG. 3, when the image size is estimated by the estimation function 353, the check function 352 includes the image size estimated by the estimation function 353 in the determination information and outputs the image size to the storage function 355.

The reject function 354 is an example of a notification unit. When the reject function 354 determines that the determination requirement is not satisfied by the check function 352, the reject function 354 notifies the transmission source of the determination information of the insufficient determination requirement (element lacking in the determination information).

Specifically, the reject function 354 sends reject information such as a message requesting acquisition (retransmission) of the element based on the element of the shortage notified from the check function 352 to the clinic terminal 10 of the transmission source. Send to.

As an example, when the check function 352 determines that the image quality of the skin image or the imaged portion does not satisfy the determination requirement, the reject function 354 provides reject information for guiding the condition of the image quality satisfying the determination requirement, the region to be imaged, and the like. Send.

In this case, the medical staff who operates the clinic terminal 10 retransmits the determination information to which the insufficient element is added, based on the reject information notified from the diagnosis support device 30. As a result, the diagnostic support device 30 can determine the skin condition of the subject based on the retransmitted determination information.

When the reject function 354 transmits the reject information, it issues an identifier (hereinafter, also referred to as a recheck identifier) that can identify the determination information that has been rejected, and includes the identifier in the reject information for transmission. You may. Further, in this case, the reject function 354 cooperates with the check function 352, the save function 355, etc., to associate the recheck identifier with the rejected determination information and store it in the determination information storage unit 331 or the like. Is preferable.

With such a configuration, when the new determination information input from the clinic terminal 10 includes the recheck identifier, the determination of the corresponding recheck identifier held in the determination information storage unit 331 or the like is made. It can be processed together with the information. As a result, the medical staff who operates the clinic terminal 10 can supplement the missing elements with the previously transmitted judgment information by transmitting the missing elements together with the recheck identifier as judgment information. , Convenience can be improved.

The storage function 355 stores (stores) the determination information checked by the check function 352 in the determination information storage unit 331. Further, the storage function 355 controls the processing function 356 when storing the determination information in the determination information storage unit 331, and performs a processing process for anonymizing the personally identifiable information included in the determination information. Let it run.

The processing function 356 executes a processing process for anonymizing the personally identifiable information included in the determination information. Specifically, when the processing function 356 detects a region showing the eyes of the subject from the skin image included in the determination information, the processing function 356 performs anonymization processing such as removing or filling the region. By such anonymization processing, the determination information storage unit 331 stores the determination information including the anonymized skin image.

The target of the anonymization process is not limited to the skin image, but may be subject information or image information. For example, the processing function 356 may perform anonymization by deleting personal information included in the subject information. However, in the diagnosis support operation described later, personal information may be required when making an examination reservation to the hospital terminal 20, so an item to be anonymized is set in advance so as not to interfere with the diagnosis support operation. It is preferable to keep it.

Further, the processing function 356 may execute a process other than the anonymization process. For example, when the determination information includes an element that interferes with the determination process of the determination function 357, a process of removing the element or storing it as separate data may be executed.

The determination function 357 is an example of a determination unit. The determination function 357 determines the state of the skin represented in the skin image based on the skin image of the subject. In particular. The determination function 357 determines the skin condition of the subject, that is, the disease name and its severity, based on the elements related to the determination requirements included in the subject information stored in the determination information storage unit 331. Here, it is assumed that at least a skin image is included in the elements related to the determination requirement.

The determination method and algorithm of the determination function 357 are not particularly limited, and various techniques can be used. For example, the determination function 357 may determine the condition of the skin using a trained model generated by machine learning such as deep learning. In this case, it is assumed that the trained model has been trained in advance so that the disease name and the severity are output as inference results by inputting the elements related to the determination requirements. Further, in this case, the inference accuracy (determination accuracy) can be improved by preparing a trained model for each of the above-mentioned image sizes. When the trained model is used, the judgment function 357 inputs various elements extracted from the subject information into the trained model, and determines the disease name and severity inferred by the trained model as the judgment result. Output.

Further, the severity derived as a determination result is an index value indicating the degree of the state of the disease, and is represented by, for example, a numerical value in three stages of mild = 1, moderate = 2, and severe = 3. The determination function 357 may be configured to determine the degree of urgency, which indicates the degree of urgency, together with the severity or instead of the severity.

In addition, the severity may be an index value indicating the possibility of suffering from a specific disease. For example, the determination function 357 derives information such as a numerical value that quantitatively indicates the possibility of suffering from a specific disease such as melanoma or severe drug eruption as a determination result of severity. Here, the severity may be a numerical value such as a percentage or a binary numerical value indicating the presence or absence of possibility.

The support function 358 is an example of the diagnostic support unit. The support function 358 executes a diagnosis support operation for notifying the determination result or the notification content according to the determination result to the notification destination corresponding to the determination result of the determination function 357. Specifically, the support function 358 executes a diagnostic support operation that changes the notification destination of the determination result according to the disease name or severity determined by the determination function 357. The support function 358 can be usefully functioned by prescribing the diagnosis support operation as setting information based on the relationship between the severity (or urgency) of the disease and the actual medical cooperation.

Hereinafter, an example of the diagnostic support operation performed by the support function 358 will be described with reference to FIGS. 6 to 8. Here, FIGS. 6 to 8 are diagrams showing an example of setting information related to the diagnosis support operation executed by the support function 358.

First, the setting information of FIG. 6 will be described. As shown in FIG. 6, the setting information is composed of, for example, a set of an operating condition and a notification destination.

The operation condition is a condition when the support function 358 performs the diagnosis support operation, and can be separated according to the severity, for example. Here, an example is shown in which the severity is classified into the case where the severity is less than the threshold value Th and the case where the severity is equal to or higher than the threshold value Th. The threshold value Th is any one of the above-mentioned three-stage numerical values (1 to 3) of mild, moderate, and severe. For example, by setting the threshold value Th to "3", the diagnostic support operation can be changed between mild and moderate cases and severe cases.

The notification destination defines a notification destination for notifying the determination result of the determination function 357. In the example of FIG. 6, the notification destination when the severity is less than the threshold value Th is the transmission source of the determination information, that is, the clinic H1. Further, when the severity is the threshold value Th or more, the notification destination is the transmission source of the determination information (clinic H1) and the hospital H2.

When the setting information of FIG. 6 is used, the support function 358 notifies the clinic terminal 10 of the determination result of the determination function 357 when the severity determined by the determination function 357 is less than the threshold value Th. Further, when the severity determined by the determination function 357 is equal to or higher than the threshold value Th, the support function 358 notifies both the clinic terminal 10 and the hospital terminal 20 of the determination result of the determination function 357.

As a result, the support function 358 notifies the clinic H1 that has transmitted the determination information of the determination result when the severity determined by the determination function 357 is mild or moderate, and in the case of severe cases, the medical treatment is performed. The determination result can be notified to both the clinic H1 and the hospital H2.

As described above, the support function 358 executes the diagnosis support operation of notifying the determination destination according to the determination result of the determination function 357. By performing such a diagnostic support operation, the support function 358 can promptly notify the clinic H1 and the hospital H2 that a serious subject is present when the condition of the subject is severe. .. Therefore, since the support function 358 can save the trouble of notifying the hospital H2 of the state of the subject from the clinic H1, it is possible to support the medical cooperation between the clinic H1 and the hospital H2.

FIG. 7 shows other setting information. The setting information in FIG. 7 has a configuration in which the operation content is added to the above-mentioned operation conditions and notification destination. Here, the operation content defines the operation to be performed by the support function 358.

In the example of FIG. 7, when the severity is less than the threshold value Th, it is stipulated that the notification destination (clinic H1) is notified of the determination result of the determination function 357. Further, when the severity is equal to or higher than the threshold value Th, the notification destination (hospital H2) is notified of the determination result of the determination function 357 and the operation of reserving the examination of the subject. Further, when the severity is equal to or higher than the threshold value Th, the notification destination (hospital H2) is notified of the judgment result of the judgment function 357 and the hospital H2 is notified that the test of the subject has been reserved. It stipulates.

Here, for the examination reservation for the hospital H2, for example, the personal information and patient ID of the subject included in the determination information, and the information about the clinic H1 to which the determination information is transmitted are sent to the hospital terminal 20 as the examination reservation information. It is executed by sending.

When the setting information of FIG. 7 is used, the support function 358 notifies the clinic terminal 10 of the determination result of the determination function 357 when the severity determined by the determination function 357 is less than the threshold value Th. Further, when the severity determined by the determination function 357 is equal to or higher than the threshold value Th, the support function 358 notifies both the clinic terminal 10 and the hospital terminal 20 of the determination result of the determination function 357. Further, when the severity determined by the determination function 357 is equal to or higher than the threshold Th, the support function 358 makes an examination reservation by transmitting (notifying) the examination reservation information related to the examination reservation of the subject to the hospital terminal 20. , Notifies (notifies) the clinic terminal 10 that the examination reservation for the subject has been made to the hospital H2.

As a result, the support function 358 notifies the clinic H1 that has transmitted the determination information of the determination result when the severity determined by the determination function 357 is mild or moderate, and in the case of severe cases, the medical treatment is performed. The determination result can be notified to both the clinic H1 and the hospital H2. Further, the support function 358 indicates that when the severity determined by the determination function 357 is severe, the examination reservation for the corresponding subject is made to the hospital H2 and the examination reservation for the hospital H2 is made. It is possible to notify H1.

As described above, the support function 358 executes the diagnosis support operation of notifying the notification destination according to the determination result of the determination function 357 of the determination result or the notification content according to the determination result. By performing such a diagnostic support operation, the support function 358 can promptly notify the clinic H1 and the hospital H2 that a serious subject is present when the condition of the subject is severe. At the same time, the examination reservation of the subject can be automatically made to the hospital H2. Therefore, since the support function 358 can save the trouble of notifying the hospital H2 of the status of the critically ill patient (subject) from the clinic H1, it is possible to support the medical cooperation between the clinic H1 and the hospital H2. Further, since the support function 358 can automatically make an examination reservation for a seriously ill subject to the hospital H2, it is possible to save the trouble of making an examination reservation from the clinic H1 to the hospital H2, and thus the processing can be performed. Efficiency can be improved.

The support function 358 may be configured to provide the determination information (skin image or the like) stored in the determination information storage unit 331 to the hospital terminal 20 when making an examination reservation for the hospital terminal 20. In this case, the support function 358 may transmit the determination information together with the examination reservation information to the hospital terminal 20, or the determination information of the corresponding subject stored in the determination information storage unit 331 may be transmitted from the hospital terminal 20. It may be accessible.

Further, the support function 358 may also notify the clinic terminal 10 of a message requesting arrangement of a letter of introduction (medical information provision form) when notifying the clinic terminal 10 that an examination reservation has been made. Further, in this case, in the diagnosis support device 30, when the information indicating the referral letter (hereinafter, also referred to as the referral letter information) is separately input from the clinic terminal 10, the input referral letter information is automatically transmitted to the hospital terminal 20. It may be configured to transfer with.

FIG. 8 shows other setting information. The setting information in FIG. 8 is obtained by substituting the operating condition of the setting information in FIG. 7 described above with a disease name. Here, an example is shown in which the disease name determined by the determination function 357 is classified into a specific disease name X and a case other than the disease name X. The disease name X can be arbitrarily set, and a plurality of disease names can be set. For example, it is preferable to specify a disease name having a high severity (urgency) such as melanoma or severe drug eruption in the disease name X.

When the setting information of FIG. 8 is used, the support function 358 transfers the determination result of the determination function 357 to both the clinic terminal 10 and the hospital terminal 20 when the disease name determined by the determination function 357 is the disease name X. Notice. Further, when the disease name determined by the determination function 357 is the disease name X, the support function 358 makes an examination reservation for the subject to the hospital terminal 20 and notifies the clinic terminal 10 that the examination reservation has been made. .. Further, when the disease name determined by the determination function 357 is other than the disease name X, the determination result of the determination function 357 is notified to the clinic terminal 10.

As described above, the support function 358 executes the diagnosis support operation of notifying the notification destination according to the determination result of the determination function 357 of the determination result or the notification content according to the determination result. By performing such a diagnosis support operation, the support function 358 indicates that the subject of the disease name X exists when the disease name of the subject is the disease name X having a high severity and urgency. Can be promptly notified to the hospital H2, and the examination reservation for the subject can be automatically made to the hospital H2. Therefore, since the support function 358 can save the trouble of notifying the hospital H2 of the status of the critically ill patient (subject) from the clinic H1, it is possible to support the medical cooperation between the clinic H1 and the hospital H2. Further, since the support function 358 can automatically make an examination reservation for a seriously ill subject to the hospital H2, it is possible to save the trouble of making an examination reservation from the clinic H1 to the hospital H2, and thus the processing can be performed. Efficiency can be improved.

Although three examples of setting information have been given above, the content of the setting information is not limited to these. The content of the setting information can be changed as appropriate according to changes in medical cooperation, legal system, etc. Further, for example, when the diagnosis support device 30 comprehensively manages the cooperation between the clinic H1 (clinic terminal 10) and the hospital H2 (hospital terminal 20) in a plurality of regions, the clinic H1 and the hospital in a cooperative relationship are managed. The setting information indicating the relationship with H2 may be separately stored, and the hospital H2 as the notification destination may be switched for each clinic H1.

Hereinafter, an example of the processing performed by the diagnosis support device 30 will be described with reference to FIG. 9. FIG. 9 is a flowchart showing an example of processing performed by the diagnosis support device 30.

First, the reception function 351 accepts the input of the determination information transmitted from the clinic H1 (clinic terminal 10) via the communication interface 34 (step S11). Next, the check function 352 checks whether the element included in the determination information satisfies the determination requirement of the determination function 357 (step S12). Here, when it is determined that the determination requirement is satisfied (step S12; Yes), the check function 352 outputs the determination information received by the reception function 351 to the storage function 355, and shifts to step S16.

Further, when it is determined that the determination requirement is not satisfied (step S12; No), the check function 352 determines whether or not the shortage requirement is the image size (step S13). Here, when the requirement for the shortage includes a requirement other than the image size (step S13; No), the check function 352 shifts to step S14. In this case, the reject function 354 generates reject information based on the processing result of step S12, and executes a reject operation of returning the generated reject information to the clinic terminal 10 (step S14).

Further, when the requirement for the shortage is only the image size (step S13; Yes), the check function 352 shifts to step S15. In this case, the estimation function 353 estimates the image size of the skin image by analyzing the skin image included in the determination information (step S15). Then, the check function 352 includes the image size estimated in step S15 in the determination information received by the reception function 351 and outputs it to the storage function 355, and shifts to step S16.

Subsequently, the processing function 356 determines whether or not the determination information input to the storage function 355 includes information that can identify an individual (step S16). When it is determined that the personally identifiable information is not included (step S16; No), the processing function 356 shifts to step S18. Further, when it is determined that the information that can identify an individual is included (step S16; Yes), the processing function 356 executes an anonymization process such as removing the information (step S17), and shifts to step S18. ..

Subsequently, the storage function 355 stores the determination information in the determination information storage unit 331 (step S18). The determination function 357 determines the skin condition of the subject based on the determination information stored in step S18 (step S19). Then, the support function 358. The diagnosis support operation according to the determination result in step S19 is executed (step S20), and this process is terminated.

As described above, when the diagnosis support device 30 receives the input of the skin image of the subject's skin from the clinic H1 (clinic terminal 10), the diagnosis support device 30 determines the skin condition of the subject based on the received skin image. Then, the diagnosis support operation is executed according to the judgment result.

As a result, in the diagnosis support device 30, for example, even if the disease occurring on the skin of the subject is a disease such as a severe drug eruption that is difficult to distinguish in the clinic H1, it is input from the clinic terminal 10. The name of the disease and its severity can be determined based on the skin image or the like. Further, since the diagnostic support device 30 can switch the diagnostic support operation related to the treatment of the subject according to the determination result, when the severity of the disease is high, the hospital H2 is promptly notified or reserved. Can be done.

Therefore, the diagnosis support device 30 can promote the efficiency of cooperation between the clinic H1 and the hospital H2, and can guide the subject to an appropriate medical institution or treatment.

It should be noted that the above-described embodiment can be appropriately modified and implemented by changing a part of the configuration or function of each device. Therefore, in the following, some modifications according to the above-described embodiment will be described as other embodiments. In the following, points different from the above-described embodiment will be mainly described, and detailed description of points common to the contents already described will be omitted. Further, the modifications described below may be carried out individually or in combination as appropriate.

(Modification 1)
In the above-described embodiment, the diagnostic support device 30 supports medical cooperation between the clinic H1 and the hospital H2, but the medical facilities to be supported are not limited to these, and rehabilitation facilities, nursing care facilities, etc. May include.

Further, the diagnostic support device 30 is not limited to the cooperation between medical facilities, and may be in a form of supporting the cooperation between the individual user as a subject and the medical facility, as shown in FIG. 10, for example.

Here, FIG. 10 is a diagram showing a configuration example of the diagnostic support system according to the modified example 1. As shown in FIG. 10, the diagnosis support system 1 includes the hospital terminal 20, the diagnosis support device 30, and the user terminal 40 described above. The hospital terminal 20, the diagnosis support device 30, and the user terminal 40 are communicably connected via the network N1.

The user terminal 40 is a terminal device operated by the user who is the subject. For example, the user terminal 40 is realized by a personal computer, a tablet PC, a PDA, a smartphone having a camera function, or the like. In this modification, the user terminal 40 will be described as a smartphone.

In the diagnosis support system 1 according to the present modification, the user can transmit the self-skin image captured by the user terminal 40 to the diagnosis support device 30 as determination information. Further, in this case, the user may also transmit information indicating his / her name, contact information, the day after the onset of the image, etc. as the determination information.

The reception function 351 of the diagnosis support device 30 receives the input of the determination information transmitted from the user terminal 40 via the communication interface 34. The reception function 351 may be in the form of providing the user terminal 40 with a Web page for transmitting the determination information so that the element related to the determination requirement can be input together with the skin photograph.

In the diagnosis support device 30, the support function 358 is the subject (user) determined by the determination function 357 by executing the same processing as the above-described embodiment based on the determination information received from the user terminal 40. Diagnosis support operation can be performed according to the state.

In addition, in the configuration of this modification, the image quality of the skin image may be deteriorated as compared with the configuration of the above-described embodiment. Further, since the information other than the skin image included in the determination information is input by the user himself / herself, the determination function is performed because the information obtained by medical knowledge is less than the configuration of the above-described embodiment. There is a possibility that the determination by 357 cannot be performed or the determination accuracy is lowered.

Therefore, in the case of this modification, it is preferable to customize the operation of the reject function 354 and the support function 358, the determination requirement of the determination function 357, and the like. For example, instead of relaxing the determination requirement of the determination function 357, the determination result of the determination function 357 may be notified including the determination accuracy and the determination accuracy. Further, for example, the support function 358 notifies the user terminal 40 of a skin photograph taken at a different imaging angle or a message requesting that the skin photograph be transmitted again after a predetermined time, depending on the determination result of the determination function 357. It may be in the form of As described above, by using a plurality of skin photographs having different imaging angles and a plurality of skin photographs captured at different timings, it is possible to improve the determination accuracy of the determination function 357.

Further, the support function 358 can automatically make an examination reservation to the hospital terminal 20 as a diagnostic support operation when the severity of the user is high, but the support function 358 is not limited to this operation example and defines other operations. May be good. For example, the support function 358 notifies the user terminal 40 of the determination result when the severity is 1, and when the severity is 2, makes an examination reservation to the above-mentioned clinic H1 (clinic terminal 10). When the degree is 3, an examination reservation may be made to the hospital H2 (hospital terminal 20).

As described above, the diagnostic support device 30 according to the present modification executes the diagnostic support operation of notifying the notification destination according to the determination result of the determination function 357 of the determination result or the notification content according to the determination result. Thereby, for example, even if the disease occurring on the skin of the subject is a disease such as severe drug eruption, the diagnosis support device 30 is based on the skin image or the like input from the user terminal 40 and the disease name. And its severity can be determined. Further, since the diagnostic support device 30 can switch the diagnostic support operation related to the treatment of the subject according to the determination result, when the severity of the disease is high, the hospital H2 is promptly notified or reserved. be able to.

Therefore, the diagnostic support device 30 can promote the efficiency of cooperation between the user and the medical facility, and can guide the subject to an appropriate medical institution or treatment.

(Modification 2)
In the above-described embodiment, the embodiment in which the diagnosis support device 30 is provided outside the clinic H1 has been described. However, the installation position of the diagnosis support device 30 is not limited to the above embodiment. For example, the diagnosis support device 30 may be provided in the clinic H1. In this case, the diagnosis support device 30 may be mounted in the form of the clinic terminal 10 or the like described above.

In the above-described embodiment, an example in which the functional configuration included in the diagnostic support device 30 is realized by the processing circuit 35 has been described, but the embodiment is not limited to this. For example, the functional configuration in the present specification may be hardware alone or a mixture of hardware and software to realize the same function.

Further, the term "processor" used in the above description means, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an integrated circuit for a specific application (ASIC), or a programmable logic device. (For example, a circuit such as a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)) is meant. When the processor is, for example, a CPU, the processor realizes the function by reading and executing the program stored in the storage circuit 33. On the other hand, when the processor is, for example, an ASIC, the function is directly incorporated as a logic circuit in the circuit of the processor instead of storing the program in the storage circuit 33. It should be noted that each processor of the present embodiment is not limited to the case where each processor is configured as a single circuit, and a plurality of independent circuits may be combined to form one processor to realize its function. good. Further, a plurality of components in each figure may be integrated into one processor to realize the function.

Here, the program executed by the processor is provided by being incorporated in a ROM (Read Only Memory), a storage circuit, or the like in advance. This program is a file in a format that can be installed or executed on these devices, such as CD (Compact Disk) -ROM, FD (Flexible Disk), CD-R (Recordable), DVD (Digital Versatile Disk), etc. It may be recorded and provided on a computer-readable storage medium. Further, this program may be stored on a computer connected to a network such as the Internet, and may be provided or distributed by being downloaded via the network. For example, this program is composed of modules including each of the above-mentioned functional parts. As actual hardware, the CPU reads a program from a storage medium such as a ROM and executes the program, so that each module is loaded on the main storage device and generated on the main storage device.

According to at least one embodiment described above, it is possible to determine the condition of the skin of the subject and carry out a diagnostic support operation suitable for the condition.

Although some embodiments (modifications) have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other embodiments, and various omissions, replacements, changes, and combinations of embodiments can be made without departing from the gist of the invention. These embodiments and variations thereof are included in the scope of the invention described in the claims and the equivalent scope thereof, as are included in the scope and gist of the invention.

1 Diagnosis support system 10 Clinic terminal 20 Hospital terminal 30 Diagnosis support device 40 User terminal 351 Reception function 352 Check function 353 Estimation function 354 Reject function 355 Save function 356 Processing function 357 Judgment function 358 Support function

Claims (9)

A reception section that accepts input of images of the skin of the subject,
A determination unit that determines the condition of the skin based on the image,
A diagnostic support unit that executes a diagnostic support operation to notify the judgment result or the notification content according to the judgment result to the notification destination corresponding to the judgment result of the judgment unit.
A diagnostic support device equipped with. The determination unit determines the disease name and severity of the disease occurring on the skin, and determines the disease name and severity.
The diagnostic support device according to claim 1, wherein the diagnostic support unit changes the notification destination according to the determination result of the determination unit. The determination unit determines the severity of the rash that occurs on the skin, which is an index indicating the possibility that the rash is a severe drug eruption.
The diagnostic support device according to claim 1, wherein the diagnostic support unit changes the notification destination according to the determination result of the determination unit. When the severity determined by the determination unit is less than the threshold value, the diagnosis support unit notifies the input source of the image of the determination result of the determination unit, and the severity determined by the determination unit is equal to or higher than the threshold value. The diagnostic support device according to claim 2 or 3, wherein the determination result of the determination unit is notified to a medical facility capable of performing an advanced examination from the input source. When the disease name determined by the determination unit is other than a specific disease name, the diagnosis support unit notifies the input source of the image of the determination result of the determination unit, and the disease determined by the determination unit. The diagnostic support device according to claim 2, wherein when the name is the specific disease name, the determination result of the determination unit is notified to a medical facility capable of performing an advanced examination from the input source. The diagnostic support device according to claim 4 or 5, wherein the diagnostic support unit executes a test reservation for the subject to the medical facility. The reception unit receives the input of the subject or additional information regarding the imaging of the image together with the image, and receives the input.
The diagnostic support device according to claim 1, wherein the determination unit determines the condition of the skin based on the image and the additional information. An inspection unit that inspects whether the image and the additional information received by the reception unit satisfy the requirements related to the determination of the determination unit.
When the inspection unit determines that the requirements are not satisfied, the notification unit that notifies the input source of the image of the insufficient requirements, and the notification unit.
7. The diagnostic support device according to claim 7. Further provided with an estimation unit for estimating the image size of the image based on the size of the skin field represented in the image.
The diagnostic support device according to any one of claims 1 to 8, wherein the determination unit determines the condition of the skin based on the image and the image size estimated by the estimation unit.

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