Medical information processing system, medical information processing method, and medical information processing program

Abstract

To provide information on the confirmation of validity to abnormality detected in a medical image.SOLUTION: According to this embodiment, a medical information processing device includes an urgency determination part, and a display part. The urgency determination part determines the presence / absence of the urgency of a disease about abnormality on the basis of a type of at least one abnormality detection algorithm to which a medical image about a subject is inputted and information related to the abnormality detected by inputting the medical image to the abnormality detection algorithm. The display part displays confirmation information on confirmation of the abnormality and urgency information showing the urgency adjacently to an inspection order about the abnormality in an inspection list showing a list of inspection orders in the case that the urgency is determined to exist.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present embodiment relates to a medical information processing system, a medical information processing method, and a medical information processing program. [Background technology]

[0002] Conventionally, there is a worklist that displays the order of examinations in which radiologists will perform image diagnosis. The radiologist inputs instructions for displaying the examinations from the displayed worklist. At this time, medical images related to the instructed examinations are displayed in a viewer. The radiologist interprets the displayed medical images and writes down the diagnosis results in an interpretation report, also called an image diagnosis report. For example, if an urgent interpretation is required, such as for an acute case, a mark indicating the urgent situation is displayed on the worklist. At this time, the radiologist gives priority to interpretation of the examinations marked as urgent.

[0003] In recent years, advances in image processing technology for medical images have made it possible to detect abnormalities in medical images using computer algorithms, such as those for computer-aided diagnosis (CAD). Abnormalities detected by computer algorithms include acute diseases such as acute appendicitis, acute myocardial infarction, and cerebral infarction. Acute diseases are abnormalities that require urgent medical attention and treatment. However, the accuracy of abnormality detection by computer algorithms is not perfect. In other words, not all acute diseases detected by computer algorithms are correct. For this reason, radiologists sometimes prioritize interpretation of medical images related to acute diseases detected by computer algorithms. In such cases, there is a problem in that the detection was a false positive by the computer algorithm, and the radiologist did not need to rush to interpret the images. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Special Publication No. 2006-511882 Summary of the Invention [Problem to be solved by the invention]

[0005] The problem to be solved by the present invention is to provide information regarding the validation of abnormalities detected in medical images. [Means for solving the problem]

[0006] The medical information processing system according to this embodiment includes an urgency determination unit and a display unit. The urgency determination unit determines whether or not a disease related to the abnormality is urgent based on the type of at least one abnormality detection algorithm to which a medical image related to a subject is input, or information related to an abnormality detected by inputting the medical image to the abnormality detection algorithm. If the display unit determines that the abnormality is urgent, it displays confirmation information related to confirmation of the abnormality and emergency information indicating the urgency adjacent to the examination order related to the abnormality in an examination list that shows a list of examination orders. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a medical information processing system according to an embodiment. [Figure 2] FIG. 2 is a flowchart illustrating an example of a procedure of a confirmation information providing process according to the embodiment. [Figure 3] FIG. 3 is a diagram showing an example of a purpose addition correspondence table according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an example of confirmation information and emergency information in an examination list according to the embodiment. [Figure 5] FIG. 5 is a diagram showing an example of a display of an enlarged image when a cursor is moved into a display area of ​​a thumbnail image corresponding to "aortic dissection" in the confirmation information according to the embodiment. [Figure 6]6 is a diagram showing an example of a thumbnail image to which link information is added in the confirmation information related to "aortic dissection" shown in FIG. 4 according to the embodiment. [Figure 7] FIG. 7 is a diagram showing an example of a key image and a confirmation reference image displayed in a confirmation layout according to the embodiment. [Figure 8] FIG. 8 is a diagram showing an example of confirmation information and emergency information in an examination list according to a modified example of the embodiment. [Figure 9] FIG. 9 is a diagram showing an example of confirmation information and emergency information in an examination list according to a modified example of the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, a medical information processing system, a medical information processing method, and a medical information processing program will be described in detail with reference to the drawings. In the following embodiments, parts with the same reference numerals perform similar operations, and redundant explanations will be omitted as appropriate. Note that the medical information processing system according to the present application is not limited to the following embodiments.

[0009] (Embodiment) The overall configuration of a medical information processing system according to an embodiment will be described. FIG. 1 is a diagram illustrating an example of the configuration of the medical information processing system 1 according to an embodiment. The medical information processing system 1 includes an electronic medical record server device 3, a radiology department information server device 5, a medical image diagnostic device 7, a medical image management server device 9, a medical information processing server device 11, and a client device 20. The client device 20 may be provided in the medical information processing system 1 as one or more terminal devices for each of the various server devices described above. While the medical information processing system 1 is illustrated as a client-server system in FIG. 1 , this is not limiting. For example, the medical information processing system 1 may be configured with the medical information processing server device 11 and the client device 20, as shown within the dotted line 2 in FIG. 1 . Furthermore, the various server devices in the medical information processing system 1 may be implemented as an integrated server that integrates the functions of each server device. In other words, the server devices in the medical information processing system 1 may be implemented as a single integrated server.

[0010] The medical information processing system 1 may also be realized as a standalone medical information processing device. In this case, the medical information processing device has a communication interface that integrates the functions of the first communication interface 13 and the second communication interface 21 as needed, a memory (storage unit) that integrates the stored contents of the first memory 15 and the second memory 23 as needed, a processing circuit (processing unit) that integrates the functions of the first processing circuit 17 and the second processing circuit 25 as needed, a display 27 (display unit), and an input interface 29 (input unit).

[0011] The electronic medical record server device 3 and a terminal device (hereinafter referred to as an electronic medical record terminal device) electrically connected to the electronic medical record server device 3 constitute an electronic medical record system. The electronic medical record system is an information system that manages electronic medical records for recording medical treatment details. The electronic medical record server device 3 is a computer device that executes processes related to the management of electronic medical records. The electronic medical record terminal device is used by doctors, nurses, and others who input and refer to electronic medical records. The electronic medical record server device 3 and the electronic medical record terminal device are connected to a communication network. The electronic medical record terminal device inputs test orders for subjects at the instruction of clinicians. When the test order is for imaging of a subject for diagnostic imaging, the test order includes, for example, the test area, test type (information on the test content, such as modality), name of the disease (hereinafter referred to as disease name), and test purpose. The test order may also include information such as the patient ID, patient name, test ID, and test date of the subject undergoing the test. In response to the input of the examination order, the electronic medical record server device 3 transmits the examination order to the radiology department information server device 5 together with the patient information of the subject and the like.

[0012] The radiology information server device 5 and terminal devices (hereinafter referred to as radiology terminal devices) electrically connected to the radiology information server device 5 constitute a radiology information system (hereinafter referred to as a RIS (Radiology Information Systems)). The RIS is an information system that manages information in the radiology department of a hospital. The radiology information server device (hereinafter referred to as a RIS server) 5 is a computer device that executes processes related to information management in the radiology department. As an example of its operation, the RIS server 5 receives an examination order from the electronic medical record server device 3 and acquires information about the medical imaging diagnostic device 7 (e.g., the examination type) from the examination order. The RIS server 5 transmits the examination order to the medical imaging diagnostic device 7 identified by the examination order. When the examination order is transmitted to the medical imaging diagnostic device 7, the RIS server 5 may add information such as a patient ID and an examination date to a DICOM (Digital Imaging and Communications in Medicine) tag. The radiology terminal device may be used by a radiologist to create an interpretation report on the medical image.

[0013] The medical image diagnostic device 7 is a device for acquiring medical images, such as an X-ray diagnostic device, an X-ray computed tomography (CT) device, or a magnetic resonance imaging (MRI) device. The medical image diagnostic device 7 performs imaging of the subject in response to an operation by a technician or the like to start imaging, based on an examination order from the RIS server 5. By performing imaging, the medical image diagnostic device 7 collects data indicating the state of the subject's internal tissues. The medical image diagnostic device 7 generates a medical image based on the data and transmits the generated medical image to the medical image management server device 9 together with the examination order. The medical image diagnostic device 7 also transmits the generated medical image to the medical information processing server device 11.

[0014] The medical image management server device 9 and a terminal device (hereinafter referred to as an image management terminal device) electrically connected to the medical image management server device 9 constitute a medical image management system (hereinafter referred to as a PACS (Picture Archiving and Communication Systems)). PACS is an information system that manages medical images such as X-ray CT images and MR images, and interpretation reports, also known as image diagnostic reports. The medical image management server device (hereinafter referred to as a PACS server) 9 is a computer device that executes processes related to the management of medical images. Upon receiving medical images and examination orders from the medical image diagnostic device 7, the PACS server 9 associates the medical images with the examination orders and stores them. DICOM meta information (hereinafter referred to as additional information) is attached to the medical images. The additional information includes the patient name, patient ID, and a description of the medical image (e.g., slice thickness, slice number, whether or not contrast is used, etc.). The image management terminal device is used, for example, by a radiologist to create an interpretation report.

[0015] The medical information processing server device 11 has a first communication interface 13, a first memory 15, and a first processing circuit 17. The first memory 15 and the first processing circuit 17 may be incorporated into another server device such as a PACS server 9.

[0016] The first communication interface 13 performs data communication between, for example, the electronic medical record server device 3, the RIS server 5, the PACS server 9, and the second communication interface 21. The standard of communication by the first communication interface 13 may be any standard, for example, HL7 (Hearth Level 7), DICOM, or both. The first communication interface 13 outputs data acquired through data communication with various server devices to the first memory 15. The first communication interface 13 receives an electrical signal of an input operation input to the input interface 29 of the client device 20 via the second communication interface 21. The first communication interface 13 outputs the received electrical signal to the first processing circuit 17.

[0017] The first memory 15 is a storage device that stores various information, such as an HDD (Hard disk Drive), an SSD (Solid State Drive), an integrated circuit storage device, etc. In addition to an HDD or an SSD, the first memory 15 may also be a drive device that reads and writes various information from / to a portable storage medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a flash memory, or a semiconductor memory element such as a RAM (Random Access Memory).

[0018] The first memory 15 stores various programs according to this embodiment. The first memory 15 stores data generated by executing the selection function 172, the abnormality detection function 173, the urgency determination function 174, the confirmation information generation function 175, the layout generation function 176, and the like. The generated data and these functions will be described later. The first memory 15 stores various medical information collected from various server devices and the medical image diagnostic device 7 via the first communication interface 13. For example, the first memory 15 stores an examination order and at least one medical image captured in accordance with the examination order. The examination order is acquired by the first processing circuit 17, for example, from the electronic medical record server device 3 or the RIS server 5 via the first communication interface 13. The medical image is acquired by the first processing circuit 17 from the medical image diagnostic device 7 or the PACS server 9 via the first communication interface 13.

[0019] The first memory 15 stores an algorithm (hereinafter referred to as an anomaly detection algorithm) that uses a medical image to detect at least one abnormality in the medical image. The first memory 15 stores multiple anomaly detection algorithms according to, for example, the type of abnormality, the type of medical image corresponding to the type of medical image diagnostic device 7, the imaged part of the subject, etc. The anomaly detection algorithm corresponds to, for example, an analysis application program that receives a medical image as input and outputs an abnormality location in the medical image, a disease name related to the abnormality, various numerical values ​​related to the abnormality, the accuracy of the disease name, etc. as an abnormality detection result. The abnormality detection result includes, for example, an overlay image and anomaly-related information. The overlay image corresponds to an image in which an abnormality location is superimposed on a medical image in a hue different from that of the medical image. The anomaly-related information corresponds to information related to the abnormality, such as the disease name, various numerical values ​​related to the abnormality, and the accuracy of the disease name.

[0020] The first memory 15 stores a correspondence table indicating whether or not there is an urgency for a disease name (hereinafter referred to as a disease urgency correspondence table) or a correspondence table indicating whether or not there is an urgency for a type of abnormality detection algorithm (hereinafter referred to as an algorithm urgency correspondence table).The first memory 15 may also store a correspondence table in which a test purpose is further added to the disease urgency correspondence table or the algorithm urgency correspondence table (hereinafter referred to as a purpose-added correspondence table).

[0021] The analysis application program is, for example, a trained model such as a DNN, a rule-based analysis program, etc. The anomaly detection algorithm is not limited to these, and may be various computer algorithms related to computer-aided diagnosis (hereinafter referred to as CAD). The first memory 15 stores the accuracy rate of the disease name output from the anomaly detection algorithm in association with the related anomaly detection algorithm. The accuracy rate is determined, for example, in response to the radiologist's input of a judgment (accept or ignore) on the anomaly detection result displayed on the display 27. In other words, the accuracy rate varies depending on the radiologist's judgment on the anomaly detection result.

[0022] The abnormality detection algorithm may be stored in a memory in an analysis server device (hereinafter referred to as an analysis server) that detects abnormalities in medical images. In this case, the medical information processing system 1 further includes an analysis server. The accuracy rate and abnormality detection results may be stored in a memory in the PACS server 9. In this case, the PACS server 9 tallys up the radiologist's judgment results for the abnormality detection results in the client device 20 and updates the accuracy rate.

[0023] The first processing circuit 17 has, as hardware resources, for example, a processor such as a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or a GPU (Graphics Processing Unit), and memories such as a ROM (Read Only Memory), a RAM, etc. The first processing circuit 17 may also be realized by an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), another complex programmable logic device (CPLD), a simple programmable logic device (SPLD), or the like.

[0024] The first processing circuit 17 has a system control function 171, a selection function 172, an abnormality detection function 173, an urgency determination function 174, a confirmation information generation function 175, and a layout generation function 176. Each of the system control function 171, the selection function 172, the abnormality detection function 173, the urgency determination function 174, the confirmation information generation function 175, and the layout generation function 176 is stored in the first memory 15 in the form of a program executable by a computer. The first processing circuit 17 executes the system control function 171, the selection function 172, the abnormality detection function 173, the urgency determination function 174, the confirmation information generation function 175, and the layout generation function 176 by a processor that executes the program deployed in the memory.

[0025] That is, the first processing circuit 17 corresponds to a processor that reads out programs from the first memory 15 and executes them to realize the functions corresponding to the programs. In other words, the first processing circuit 17, once it has read out each program, has the functions corresponding to the read out programs. Note that each function (171 to 176) is not limited to being realized by a single processing circuit. A processing circuit may be configured by combining multiple independent processors, and each processor may execute a program to realize each function (171 to 176).

[0026] The first processing circuit 17 controls each function of the first processing circuit 17 using the system control function 171 based on an electrical signal corresponding to an input operation received from an operator via the input interface 29. Specifically, the first processing circuit 17 reads a control program stored in the first memory 15, loads it on the memory within the first processing circuit 17, and controls each unit of the medical information processing server device 11 according to the loaded control program. If the anomaly detection algorithm is installed in the analysis server, the processing circuit (processor) in the analysis server will have a selection function 172 and an anomaly detection function 173. Furthermore, the system control function 171, urgency determination function 174, confirmation information generation function 175, and layout generation function 176 may be installed in the PACS server 9. That is, various functions of the medical information processing server device 11 may be appropriately distributed between the analysis server and the PACS server 9. In this case, the medical information processing server device 11 is realized by combining the analysis server and the PACS server 9.

[0027] The selection function 172 selects at least one anomaly detection algorithm based on a medical image of the subject. The anomaly detection function 173 detects an anomaly in the medical image by inputting the medical image to the selected anomaly detection algorithm. The urgency determination function 174 determines whether the disease associated with the anomaly is urgent, i.e., whether urgent medical treatment is required for the disease associated with the detected anomaly, based on information about the anomaly or the type of anomaly detection algorithm. The urgency determination function 174 may also determine whether the disease associated with the detected anomaly is urgent based on the purpose of the examination in the examination order for the subject associated with the medical image. The confirmation information generation function 175 generates information (hereinafter referred to as confirmation information) for confirming the urgency of the anomaly detected by the anomaly detection algorithm based on the output from the anomaly detection algorithm. If the layout generation function 176 determines that there is an urgency, the layout generates a layout (hereinafter referred to as confirmation layout) for displaying medical images containing the detected anomaly, allowing a radiologist to confirm the anomaly. The confirmation layout corresponds to a display layout suitable for the environment in which the medical image associated with the detected anomaly is interpreted.

[0028] The first processing circuit 17 that realizes the system control function 171, the selection function 172, the abnormality detection function 173, the urgency determination function 174, the confirmation information generation function 175, and the layout generation function 176 is an example of a system control unit, a selection unit, an abnormality detection unit, an urgency determination unit, a confirmation information generation unit, and a layout generation unit. The selection function 172, the abnormality detection function 173, the urgency determination function 174, the confirmation information generation function 175, and the layout generation function 176 realized by the first processing circuit 17 will be described later along with the procedure for executing a process of providing confirmation information to an operator such as a radiologist (hereinafter referred to as a confirmation information provision process).

[0029] The client device 20 includes a second communication interface 21, a second memory 23, a second processing circuit 25, a display 27, and an input interface 29. The client device 20 may also be used as another terminal device such as an image management terminal device. For example, the client device 20 is used by a radiologist to create an interpretation report for a medical image.

[0030] The second communication interface 21 performs data communication between the electronic medical record server device 3, the RIS server 5, the PACS server 9, and the first communication interface 13. The communication standard used by the second communication interface 21 may be any standard, such as HL7 (Hearth Level 7), DICOM, or both. The second communication interface 21 outputs data acquired through data communication with various server devices to the second memory 23. The second communication interface 21 transmits electrical signals representing input operations input to the input interface 29 to the first communication interface 13.

[0031] The second memory 23 is a storage device such as an HDD, SSD, or integrated circuit storage device that stores various information. In addition to an HDD or SSD, the second memory 23 may be a drive that reads and writes various information from / to portable storage media such as CDs, DVDs, and flash memory, or semiconductor memory devices such as RAM. The second memory 23 stores various medical information collected from various server devices via the second communication interface 21. For example, the second memory 23 stores an examination order acquired by the second processing circuit 25 via the second communication interface 21 and at least one medical image captured in accordance with the examination order. The second memory 23 stores an examination list (also referred to as a work list) that lists the acquired examination orders. The examination list will be described later along with the procedure for executing the confirmation information provision process. The second memory 23 stores a program related to the display function 251.

[0032] The second processing circuit 25 has, for example, a processor such as a CPU, MPU, or GPU, and a memory such as a ROM or RAM, as hardware resources. The second processing circuit 25 may also be realized by an ASIC, FPGA, CPLD, or SPLD. The second processing circuit 25 has a display function 251 and the like. The display function 251 is stored in the second memory 23 in the form of a program executable by a computer. The second processing circuit 25 executes the display function 251 using a processor that executes the program deployed in the memory. In other words, the second processing circuit 25 corresponds to a processor that realizes a function corresponding to the program by reading the program from the second memory 23 and executing it.

[0033] In other words, once the program has been read, the second processing circuit 25 has the function corresponding to the read program. Note that the display function 251 is not limited to being realized by a single processing circuit. A processing circuit may be configured by combining multiple independent processors, and the display function 251 may be realized by each processor executing a program. The second processing circuit 25 that realizes the display function 251 is an example of a display control unit. The second processing circuit 25 controls the display 27 with respect to various displays on the display 27 using the display function 251. Details of the display function 251 will be explained later along with the procedure for executing the confirmation information provision process.

[0034] The display 27 displays various types of information. For example, the display 27 outputs a GUI (Graphical User Interface) for receiving various operations from an operator. As the display 27, for example, a liquid crystal display (LCD), a cathode ray tube (CRT), an organic electroluminescence display (OLED), a plasma display, or any other display can be used as appropriate. The display 27 may be a desktop type, or may be configured as a tablet terminal or the like capable of wireless communication with the medical information processing server device 11.

[0035] When the urgency determination function 174 determines that an abnormality is urgent, the display 27 displays confirmation information regarding the detected abnormality and emergency information indicating the urgency adjacent to the examination order related to the abnormality in an examination list showing a list of examination orders. In this case, the examination list may have an emergency cancellation area for canceling the display of the confirmation information and emergency information. When a thumbnail image of a medical image containing an abnormality is displayed as confirmation information, the display 27, under the control of the display function 251, displays an enlarged image of the thumbnail image in response to a cursor movement into the display area of ​​the thumbnail image. The display 27 cancels the display of the confirmation information and emergency information in response to a cancellation operation in the emergency cancellation area via the input interface 29. The display 27 displays at least one medical image related to the abnormality in a confirmation layout in response to a predetermined operation in the display area of ​​the confirmation information.

[0036] The input interface 29 accepts various input operations from the operator, converts the accepted input operations into electrical signals, and outputs them to the second processing circuit 25. The converted electrical signals are then output to the first processing circuit 17 via the second communication interface 21 and the first communication interface 13. For example, the input interface 29 accepts selection instructions, various conditions, and the like from the operator. As the input interface 29, for example, a mouse, keyboard, trackball, switch, button, joystick, touchpad, touch panel display, and the like can be used as appropriate.

[0037] In this embodiment, the input interface 29 is not limited to one having physical operation components such as a mouse, keyboard, trackball, switch, button, joystick, touchpad, and touch panel display. For example, an example of the input interface 29 is an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and outputs the electrical signal to the first processing circuit 17 and the second processing circuit 25. The input interface 29 may also be configured as a tablet terminal or the like that is capable of wireless communication with the medical information processing server device 11.

[0038] The above describes the overall configuration of the medical information processing system 1. The following describes the procedure for the confirmation information providing process. Figure 2 is a flowchart showing an example of the procedure for the confirmation information providing process.

[0039] (Confirmation information provision process) (Step S201) The selection function 172 identifies the examination area by identifying anatomical landmarks from the medical image using existing image processing. The selection function 172 identifies the presence or absence of contrast in the medical image by analyzing the medical image using an existing segmentation algorithm. The selection function 172 extracts the examination type, such as the presence or absence of contrast and the type of modality used to generate the medical image, from the supplementary information in the medical image. The selection function 172 selects at least one anomaly detection algorithm from multiple anomaly detection algorithms to which the medical image is input, using the examination type, examination area, the presence or absence of contrast, the type of modality, etc. Note that the selection function 172 may select an anomaly detection algorithm by extracting the purpose of the examination, examination type, examination area, the presence or absence of contrast, etc. from the examination order obtained from the electronic medical record server device 3 or the RIS server 5.

[0040] For example, if the medical image is an image with contrast and the examination site is the brain, the selection function 172 selects an abnormality detection algorithm related to cerebral infarction (hereinafter referred to as LVO (Large Vessel Occlusion)). If the medical image is an image without contrast and the examination site is the brain, the selection function 172 selects an abnormality detection algorithm related to cerebral hemorrhage (hereinafter referred to as ICH (Intracranial Hemorrhage)). If the medical image is an image without contrast and the examination site is the lung, the selection function 172 selects an abnormality detection algorithm for detecting pulmonary nodules (hereinafter referred to as oncology).

[0041] (Step S202) The anomaly detection function 173 inputs a medical image into a selected anomaly detection algorithm. The anomaly detection function 173 detects an anomaly in the input medical image using the anomaly detection algorithm and outputs an anomaly detection result. The anomaly detection result is output in, for example, JSON (Java (registered trademark) Script Object Notation) format. If no anomaly is detected in the medical image, the anomaly detection function 173 outputs a message indicating that no anomaly was detected in the medical image (hereinafter referred to as an anomaly not detected).

[0042] (Step S203) If the abnormality detection function 173 outputs an abnormality detection result (Yes in step S203), the process of step S204 is executed. If the abnormality detection function 173 does not output an abnormality detection result, that is, if the abnormality detection function 173 outputs an abnormality not detected (No in step S203), the confirmation information provision process ends.

[0043] (Step S204) The urgency determination function 174 determines whether or not the abnormality detected by the abnormality detection function 173 is urgent, using the abnormality-related information or the type of abnormality detection algorithm. Specifically, the urgency determination function 174 extracts a disease name from the abnormality-related information and determines whether or not the abnormality is urgent by comparing the extracted disease name with a disease emergency response table. Disease names determined to be urgent include, for example, stroke, cerebral hemorrhage, and large blood vessel occlusion. Disease names determined to be non-urgent include, for example, pulmonary nodule and various cancers. The urgency determination function 174 determines whether or not the abnormality is urgent by comparing the type of abnormality detection algorithm used to detect the abnormality with the algorithm emergency response table. An abnormality detection algorithm determined to be urgent includes, for example, ICH and LVO. An abnormality detection algorithm determined to be non-urgent includes, for example, oncology.

[0044] The urgency determination function 174 may extract the test purpose from the test order for the subject and determine whether or not there is an urgency by comparing the extracted test purpose with the purpose addition correspondence table. Fig. 3 is a diagram showing an example of the purpose addition correspondence table ALT. As shown in Fig. 3, for example, if the test purpose is a follow-up (progression observation) for the subject, the urgency determination function 174 determines that there is no urgency even if an abnormality is detected.

[0045] If the urgency determination function 174 determines that there is an urgency (Yes in step S204), the processes of step S205 and step S206 are executed. At this time, the urgency determination function 174 transmits to the client device 20 via the first communication interface 13 and the second communication interface 21 that the detected abnormality has an urgency. If the urgency determination function 174 determines that there is no urgency (No in step S204), the confirmation information provision process ends.

[0046] (Step S205) The confirmation information generation function 175 generates confirmation information based on the anomaly detection result. The confirmation information includes, for example, at least one of a thumbnail image of the medical image, i.e., the overlay image, including the detected anomaly, the disease name related to the detected anomaly, the name of the anomaly detection algorithm (hereinafter referred to as the algorithm name), and the accuracy rate related to the disease name. In other words, the confirmation information corresponds to information indicating a summary of the anomaly detection result.

[0047] Specifically, the confirmation information generation function 175 searches the first memory 15 using the examination site, disease name, and algorithm name in the medical image in which the abnormality was detected, and obtains the accuracy rate corresponding to the abnormality detection result from the first memory 15. The confirmation information generation function 175 generates a thumbnail image by performing a predetermined reduction process on the overlay image. At this time, the confirmation information generation function 175 links the generated thumbnail image with the overlay image from which the thumbnail image was generated. The confirmation information generation function 175 also extracts the disease name, algorithm name, and accuracy rate from the abnormality-related information in the abnormality detection result. The confirmation information generation function 175 generates confirmation information by integrating the thumbnail image, disease name, algorithm name, and accuracy rate. The confirmation information is sent to the client device 20 via the first communication interface 13 and the second communication interface 21 and stored in the second memory 23.

[0048] (Step S206) The layout generation function 176 generates a confirmation layout based on the overlay image. The confirmation layout corresponds to a display layout suitable for interpreting a medical image having a detected abnormality (hereinafter referred to as a key image). If the key image is a CT image or an MRI image, the slice position of the key image corresponds to the slice position where the abnormality was detected. The layout generation function 176 generates at least one image suitable for diagnosing a disease related to the abnormality, i.e., for interpretation, based on multiple medical images of the subject. For example, the layout generation function 176 generates three orthogonal cross-sectional images including the key image, an oblique image including the abnormality, a curved MPR image including the abnormality, etc., by performing multi-planar reconstruction processing on volume data related to the subject.

[0049] The layout generation function 176 also generates various rendering images (3D images) including abnormalities by rendering the volume data. Hereinafter, for ease of explanation, a medical image generated by the layout generation function 176 and including an abnormality will be referred to as a confirmation reference image. The confirmation reference image may be generated by the confirmation information generation function 175. The confirmation reference image corresponds to an image useful for confirming and diagnosing an abnormality detection result. The layout generation function 176 generates a confirmation layout capable of displaying a key image and a confirmation reference image. The confirmation layout may further display abnormality-related information. The confirmation layout, key image, and confirmation reference image are transmitted to the client device 20 via the first communication interface 13 and the second communication interface 21 and stored in the second memory 23. The confirmation layout, key image, and confirmation reference image may be stored in the first memory 15. The layout generation function 176 attaches link information between the thumbnail image and the confirmation layout to the thumbnail image. The layout generation function 176 may attach the link information to the confirmation information. For the sake of simplicity, it is assumed below that link information is attached to thumbnail images.

[0050] (Step S207) The display function 251 displays confirmation information and emergency information indicating urgency on the display 27 adjacent to an examination order related to an abnormality in the examination list. FIG. 4 is a diagram showing an example of confirmation information CI and emergency information EI indicating urgency in the examination list SL. In the examination list SL, examination orders are arranged, for example, in the order in which the examination orders were received or in the order in which medical images were acquired. An "urgent" flag is displayed on the top examination order in the examination list SL at the instruction of a clinician for patient A. In addition, if the item of the determination result (hereinafter referred to as CAD result) by the urgency determination function 174 does not indicate urgency, the emergency information EI is hidden. In the examination list SL in FIG. 4, two columns related to emergency status are shown, one by a clinician and one by a CAD result. However, this is not limiting. For example, a flag indicating emergency interpretation by a clinician and a flag indicating emergency interpretation based on CAD results may be displayed in different display modes in a single column in the examination list SL.

[0051] As shown in Figure 4, the second-level examination order SOI in the examination list SL does not have an "urgent" flag because there is no urgent instruction from a clinician for patient B. However, in the second-level examination order SOI, the analysis results of the medical image using the anomaly detection algorithm have been determined to be urgent, so the word "urgent" is displayed as emergency information EI in the CAD results section. In addition, confirmation information CI is displayed in the second-level examination order SOI.

[0052] In the confirmation information CI shown in Fig. 4, the disease name "aortic dissection," the name of the abnormality detection algorithm that output the disease name "Cardiac Deep Mind," and the accuracy rate (acceptance rate) of the abnormality detection algorithm that output the disease name "80%" are displayed together with a thumbnail image SI of the key image. Furthermore, in the confirmation information CI, the disease name "stroke," the name of the abnormality detection algorithm that output the disease name "Stroke Finder," and the accuracy rate (acceptance rate) of the abnormality detection algorithm that output the disease name "95%" are displayed together with a thumbnail image SI of the key image.

[0053] When the cursor displayed on the display 27 is moved into the display area of ​​a thumbnail image SI in response to an instruction from an operator such as a radiologist, the display function 251 displays an enlarged image of the thumbnail image SI on the display 27, superimposed on the examination list SL. Note that instead of the enlarged image, the display function 251 may display a key image on the display 27 in a display area larger than the thumbnail image SI. FIG. 5 is a diagram showing an example of how the enlarged image EXI is displayed when the cursor KSR is moved into the display area of ​​the thumbnail image SI corresponding to "aortic dissection" in the confirmation information CI. When the position of the cursor KSR moves out of the display area of ​​the thumbnail image SI, the display function 251 cancels the display of the enlarged image EXI.

[0054] (Step S208) When a predetermined operation is input in the display area of ​​the thumbnail image SI (Yes in step S208), the process of step S209 is executed. The predetermined operation is a simple operation, such as a one-click operation with the mouse, when the cursor KSR is moved to the display area of ​​the thumbnail image SI. When a predetermined operation is not input in the display area of ​​the thumbnail image SI (No in step S208), the process of step S210 is executed. Note that when link information is attached to the confirmation information CI, the area in which the predetermined operation is valid is the display area of ​​the confirmation information CI. FIG. 6 is a diagram showing an example of a thumbnail image SI to which link information is attached in the confirmation information CI related to "aortic dissection" shown in FIG. 4. The thumbnail image SI shown in FIG. 6 has "link information attached" written on it, but the words "link information attached" are not displayed when displayed on the display 27.

[0055] (Step S209) In response to a predetermined operation in the display area of ​​the confirmation information CI, the display function 251 displays at least one medical image related to the detected abnormality, i.e., a confirmation reference image, in a confirmation layout. When a one-click operation is input with the cursor KSR moved to the display area of ​​the thumbnail image SI shown in FIGS. 4 and 6, the display function 251 displays the key image and the confirmation reference image in the confirmation layout on the display 27. FIG. 7 is a diagram showing an example of the key image KI and the confirmation reference image CRI displayed in the confirmation layout CL. As shown in FIG. 7, the confirmation layout CL provides an operator, such as a radiologist, with an environment for reading the key image KI and the confirmation reference image CRI.

[0056] (Step S210) When confirmation information CI is displayed adjacent to an examination order, the examination list SL has an emergency cancellation area for canceling the display of the confirmation information CI and emergency information EI (hereinafter referred to as emergency display cancellation). The emergency cancellation area may be, for example, a blank area in the examination order SOI or an area where the emergency information EI is displayed, as shown in FIG. 4. The emergency cancellation area is not limited to the above and may be set at any position on the display screen of the examination list SL. When an instruction to cancel the emergency display is input by the operator via the input interface 29 (Yes in step S210), the process of step S211 is executed. The input of the instruction to cancel the emergency display corresponds to, for example, a one-click operation with the mouse when the cursor KSR is moved to the emergency cancellation area. When an instruction to cancel the emergency display is not input (No in step S210), the confirmation information providing process ends.

[0057] (Step S211) In response to the input of an instruction to cancel the emergency display, the display function 251 cancels the display of the confirmation information CI and the emergency information EI in the examination list SL. That is, in response to the operation to cancel the emergency display within the emergency cancellation area, the display 27 cancels the display of the confirmation information CI and the emergency information EI. As a result, the confirmation information CI and the emergency information EI are no longer displayed in the examination list SL. This completes the confirmation information providing process. The processes of steps S201 to S211 are executed, for example, every time a medical image collected by the medical image diagnostic apparatus 7 in accordance with an examination order is transmitted to the medical information processing server apparatus 11 or an analysis apparatus.

[0058] According to the medical information processing system 1 of the embodiment described above, at least one abnormality detection algorithm is selected based on a medical image of a subject, and an abnormality in the medical image is detected by inputting the medical image into the abnormality detection algorithm. The system determines whether the disease associated with the abnormality is urgent based on the abnormality-related information or the type of abnormality detection algorithm. If the abnormality is urgent, the system displays confirmation information CI and emergency information EI adjacent to the test order for the abnormality in the test list SL. That is, according to the present medical information processing system 1, if the abnormality detection result output by the abnormality detection algorithm is urgent, the system displays confirmation information CI and emergency information EI in the test list SL, each containing at least one of a thumbnail image SI, the name of the disease associated with the abnormality, the name of the abnormality detection algorithm, and the accuracy rate.

[0059] In other words, information that enables an operator such as a radiologist to determine the validity of the abnormality detection result can be provided on the examination list SL. As a result, according to the medical information processing system 1, the operator can confirm on the examination list SL whether emergency interpretation is necessary and the validity of the abnormality detection result for a medical image in which an abnormality has been detected by the abnormality detection algorithm, without having to perform full-scale preparation for interpretation by displaying an interpretation screen for the medical image from the examination list SL.

[0060] Furthermore, according to the medical information processing system 1, the purpose of the examination in the examination order for the subject related to the medical image is further used to determine whether or not there is an emergency. As a result, if the purpose of the examination is a post-operative follow-up or a post-medical follow-up, the disease related to the abnormality detected by the abnormality detection algorithm is determined to be non-urgent, thereby reducing the workload of the operator related to emergency image interpretation.

[0061] Furthermore, according to the medical information processing system 1, when a thumbnail image SI of a medical image containing an abnormality detected by the abnormality detection algorithm is displayed as confirmation information CI on the display 27, the display 27 displays an enlarged image EXI obtained by enlarging the thumbnail image SI when the cursor KSR is moved into the display area of ​​the thumbnail image SI. This allows the enlarged image EXI to be displayed by moving the cursor KSR into the display area of ​​the thumbnail image SI without any additional operations such as clicking the mouse, thereby reducing the operational burden on the operator.

[0062] Furthermore, according to the medical information processing system 1, the examination list SL has an emergency cancellation area for canceling the display of the confirmation information CI and the emergency information EI, and the display of the confirmation information CI and the emergency information EI in the examination list SL is canceled in response to a cancellation operation within the emergency cancellation area. This allows the display of the confirmation information CI and the emergency information EI to be canceled with a single operation while the cursor KSR is moved to the emergency cancellation area, thereby reducing the operational burden on the operator.

[0063] Furthermore, according to the medical information processing system 1, when a detected abnormality is determined to be urgent, a confirmation layout CL is generated for displaying medical images containing the abnormality, allowing confirmation of the abnormality, and at least one medical image containing the abnormality is displayed in the confirmation layout CL in response to a predetermined operation in the display area of ​​the confirmation information CI. In other words, according to the medical information processing system 1, a confirmation layout capable of displaying a key image and a confirmation reference image is generated in advance. Therefore, the operator can instantly be provided with an interpretation environment in which the target disease can be diagnosed and confirmed with a single simple operation, such as a one-click operation in the display area of ​​a thumbnail image SI, without having to search for a medical image containing the abnormality prior to interpretation. This improves the efficiency of confirmation and diagnosis of abnormality detection results that require urgent interpretation.

[0064] As another modification of this embodiment, the medical information processing system 1 may be incorporated into a hospital information system (HIS). The medical information processing system 1 may also be realized by cloud computing or the like. In this case, the first communication interface 13, the first memory 15, and the first processing circuit 17 are installed in a server on a network.

[0065] (Variation) This modification has as confirmation information at least one of an index relating to the reliability of an abnormality detected by the anomaly detection algorithm (hereinafter referred to as a confidence index) and an index relating to the priority of treatment for the abnormality (hereinafter referred to as a priority index). The confidence index includes a confidence level indicating the reliability or credibility of the anomaly detection result (analysis result) output from the anomaly detection algorithm, an average value of multiple such confidence levels relating to similar past cases or medical images, a mode value of such confidence levels, a median value of such confidence levels, a histogram of such confidence levels, a standard deviation of such confidence levels, and confidence intervals of such confidence levels.

[0066] The reliability or confidence level is, for example, a numerical value indicating the degree of likelihood of an anomaly detected by an anomaly detection algorithm (the confidence of the anomaly detection algorithm). The average reliability, the mode of the reliability, the median reliability, the histogram of the reliability, the standard deviation of the reliability, the confidence interval of the reliability, etc., are indicators used by an operator to determine the reliability of an anomaly detected by the anomaly detection algorithm. Furthermore, the histogram of the reliability, the standard deviation of the reliability, the confidence interval of the reliability, etc., correspond to data indicating the variation in multiple reliabilities corresponding to multiple similar anomalies detected in the past.

[0067] The priority index is, for example, numerical data such as a value indicating the likelihood that a subject will recover as a result of treatment for the abnormality (e.g., mismatch ratio), the degree to which the treatment will improve the prognosis of the abnormality, the degree to which the treatment is effective, the priority of treatment for the abnormality, etc. The priority index is used to determine whether or not a detected abnormality should be given priority in interpretation and treatment.

[0068] The anomaly detection function 173 outputs at least one of a reliability index and a priority index along with the anomaly detection result using an anomaly detection algorithm. The anomaly detection function 173 may output at least one of the reliability index and the priority index by inputting the anomaly detection result to an algorithm different from the anomaly detection algorithm. The different algorithm may be, for example, a trained model such as a DNN or a rule-based analysis program. At least one of the reliability index and the priority index may be generated by the confirmation information generation function 175 based on the anomaly detection result output from the anomaly detection algorithm.

[0069] Furthermore, the anomaly detection function 173 or the confirmation information generation function 175 may calculate and update the average value of the reliability, the mode of the reliability, the median of the reliability, a histogram of the reliability, the standard deviation of the reliability, the confidence interval of the reliability, etc. of the reliability index based on the reliability index corresponding to the anomaly detection result output by the anomaly detection function 173 and the reliability index related to similar past cases or medical images stored in the first memory 15. At this time, the updated average value, mode, median, histogram, standard deviation, confidence interval, etc. are stored in the first memory 15.

[0070] The first memory 15 stores the average value of the reliability for similar cases or medical images in the anomaly detection results, the mode of the reliability, a histogram of the reliability, a standard deviation of the reliability, and confidence intervals of the reliability. Note that the average value, mode, histogram, standard deviation, and confidence interval may be updated as appropriate every time a new reliability index is output by the anomaly detection function 173.

[0071] (Confirmation information generation process) The processing procedure in this modification is the same as that shown in the flowchart of FIG. 6, but the steps in the processing that differ will be explained below.

[0072] (Step S205) The confirmation information generation function 175 generates confirmation information by integrating a thumbnail image, a disease name, an algorithm name, a accuracy rate, and a reliability index. The confirmation information generation function 175 also generates confirmation information by integrating a thumbnail image, a disease name, an algorithm name, a accuracy rate, and a priority index. The confirmation information generation function 175 may also generate confirmation information by integrating a thumbnail image, a disease name, an algorithm name, a accuracy rate, a reliability index, and a priority index.

[0073] (Step S207) The display function 251 displays confirmation information and emergency information indicating urgency on the display 27 adjacent to test orders related to abnormalities in the test list. FIG. 8 is a diagram showing an example of confirmation information CI and emergency information EI indicating urgency in the test list SL. FIG. 8 differs from FIG. 4 in that the confirmation information CI may display a reliability index according to the abnormality detection result. As shown in FIG. 8, the reliability CLV is indicated, for example, in a range from 0 to 100. As shown in FIG. 8, for example, the reliability CLV of an abnormality detection result obtained by "Cardiac Deep Mind" is 80. Also, as shown in FIG. 8, for example, the reliability CLV of an abnormality detection result obtained by "Stroke Finder" is 75. The reliability displayed as shown in FIG. 8 may display a bar indicating a confidence interval (error bar). Furthermore, a histogram HIS showing the frequency distribution of multiple reliability levels may be displayed near the bar indicating the range of the reliability levels, as shown in FIG. 8. In this case, the histogram HIS may display the mode MOD of the reliability, the median MED of the reliability, and the average MEA of the reliability.

[0074] FIG. 9 is a diagram showing an example of confirmation information CI and emergency information EI indicating urgency in an examination list SL. The difference between FIG. 9 and FIG. 4 is that the confirmation information CI may display a priority index according to the abnormality detection result. In FIG. 9, the mismatch ratio is displayed as the priority index. For example, as shown in FIG. 9, the mismatch ratio of the abnormality detection result obtained by "Cardiac Deep Mind" is 90, and the mismatch ratio of the abnormality detection result obtained by "Stroke Finder" is 75. As an application example of this modification, when the confirmation information has a reliability index and a priority index, the display 27 further displays a priority index such as the mismatch ratio in the confirmation information CI shown in FIG. 8.

[0075] According to the medical information processing system 1 of the modified embodiment described above, the confirmation information further includes at least one of a reliability index indicating the reliability of the detected abnormality and a priority index indicating the priority of treatment for the abnormality. As a result, the display 27 further displays at least one of the reliability index and the priority index. This allows the operator to be informed of the reliability of the abnormality detection result obtained by the abnormality detection algorithm and statistical information regarding the reliability. Additionally, this modification allows the operator to be informed of information regarding the priority of treatment for the detected abnormality. As a result, the medical information processing system 1 of this modification allows the operator to easily confirm the need for emergency image interpretation and the validity of the abnormality detection result, thereby reducing the operator's workload, such as determining the order of image interpretation for emergency image interpretation. Other effects are similar to those of the embodiment, and therefore will not be described here.

[0076] When the technical idea of ​​this embodiment is realized in a medical information processing method, the medical information processing method determines whether or not the disease related to the abnormality is urgent based on the type of at least one abnormality detection algorithm to which a medical image is input based on a medical image of a subject, or based on information related to the abnormality detected by inputting the medical image to the abnormality detection algorithm, and if it is determined that there is urgent need, displays confirmation information CI regarding confirmation of the abnormality and emergency information EI indicating the urgency adjacent to the examination order related to the abnormality in an examination list SL that lists examination orders on the display 27. The processing procedures and effects of the medical information processing method are similar to those of the embodiment, and therefore will not be described again.

[0077] When the technical idea of ​​this embodiment is realized by a medical information processing program, the medical information processing program causes a computer to determine whether or not the disease related to the abnormality is urgent, based on a medical image of a subject, and based on the type of at least one abnormality detection algorithm to which the medical image is input, or information related to the abnormality detected by inputting the medical image into the abnormality detection algorithm, and if it is determined that there is an urgency, display confirmation information CI regarding confirmation of the abnormality and emergency information EI indicating the urgency on the display 27, adjacent to the test order related to the abnormality, in an test list SL that shows a list of test orders.

[0078] For example, the confirmation information provision process can be realized by installing a medical information processing program in a computer such as the PACS server 9 or integrated server in a hospital information system and expanding the program in memory. In this case, the program that can cause a computer to execute the method can also be stored and distributed on a storage medium such as a magnetic disk (such as a hard disk), an optical disk (such as a CD-ROM or DVD), or a semiconductor memory. The processing procedures and effects of the medical information processing program are the same as those in the embodiment, so a description thereof will be omitted.

[0079] According to at least one of the embodiments described above, it is possible to provide information relating to confirmation of the legitimacy of an abnormality detected in a medical image. As a result, the medical information processing system 1 can reduce the workload of the operator and save time and effort in confirming the legitimacy of an abnormality detection result that requires urgent interpretation, thereby improving the throughput of interpretation.

[0080] Although several embodiments of the present invention 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 forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention described in the claims and their equivalents. [Explanation of symbols]

[0081] 1 Medical information processing system 3. Electronic medical record server device 5. Radiology department information server device (RIS server) 7 Medical imaging diagnostic equipment 9. Medical image management server device (PACS server) 11 Medical information processing server device 13 First communication interface 15 First Memory 17 First processing circuit 20 Client Device 21 Second communication interface 23 Second Memory 25 Second processing circuit 27 Display 29 Input Interface 171 System Control Functions 172 Selection Function 173 Anomaly detection function 175 Confirmation information generation function 176 Layout generation function 251 Display function

Claims

1. an urgency determination unit that determines whether or not a disease related to the abnormality is urgent based on the type of at least one abnormality detection algorithm to which a medical image related to a subject is input, or information related to an abnormality detected by inputting the medical image to the abnormality detection algorithm; a display unit that displays, when it is determined that there is an urgency, confirmation information regarding confirmation of the abnormality and emergency information indicating the urgency adjacent to the test order regarding the abnormality in an examination list that shows a list of test orders; Equipped with the confirmation information includes at least one of a medical image including an abnormality detected by the abnormality detection algorithm, a disease name related to the detected abnormality, a name of the abnormality detection algorithm, a correct answer rate related to the disease name, and an index related to the priority of treatment for the abnormality, and an index related to the reliability of the detected abnormality; the display unit displays the reliability of the anomaly detection result obtained by the anomaly detection algorithm and statistical information related to the reliability as indicators related to the reliability of the detected anomaly; the statistical information includes a plurality of histograms of reliability, each of which indicates a plurality of reliability levels with respect to past cases similar to the abnormality or a plurality of reliability levels with respect to a plurality of past medical images similar to the abnormality; Medical information processing system.

2. the urgency determination unit determines whether or not there is an urgency by further using an examination purpose in an examination order for the subject related to the medical image. The medical information processing system according to claim 1 .

3. When a thumbnail image of the medical image including the abnormality is displayed as the confirmation information, the display unit displays an enlarged image of the thumbnail image when a cursor is moved into a display area of ​​the thumbnail image. The medical information processing system according to claim 1 or 2.

4. the examination list has an emergency cancellation area for canceling the display of the confirmation information and the emergency information, the display unit cancels the display of the confirmation information and the emergency information in response to the cancellation operation within the emergency cancellation area. The medical information processing system according to any one of claims 1 to 3.

5. a layout generating unit that is capable of executing confirmation of the abnormality when it is determined that there is an emergency and that generates a confirmation layout for displaying a medical image including the abnormality; the display unit displays at least one medical image related to the abnormality in the confirmation layout in response to a predetermined operation in the display area of ​​the confirmation information. The medical information processing system according to any one of claims 1 to 4.

6. a selection unit that selects, based on the medical image of the subject, at least one of the abnormality detection algorithms to which the medical image is input; an anomaly detection unit that detects an anomaly in the medical image by inputting the medical image into the anomaly detection algorithm; The medical information processing system according to claim 1 , further comprising:

7. the statistical information further includes an average value of the plurality of reliabilities, a mode value of the plurality of reliabilities, a median value of the plurality of reliabilities, a standard deviation of the plurality of reliabilities, and a confidence interval of the plurality of reliabilities; The medical information processing system according to any one of claims 1 to 6.

8. The display unit displaying a bar indicating a confidence interval for the reliability according to the anomaly detection result; displaying the histogram alongside the bar, along with the mean, mode, and median; The medical information processing system according to claim 7.

9. determining whether or not there is an emergency regarding the abnormality based on the type of at least one abnormality detection algorithm to which a medical image of a subject is input, or information related to the abnormality detected by inputting the medical image to the abnormality detection algorithm; When it is determined that there is an urgency, displaying confirmation information regarding confirmation of the abnormality and emergency information indicating the urgency on a display adjacent to the test order related to the abnormality in an examination list showing a list of test orders; Equipped with the confirmation information includes at least one of a medical image including an abnormality detected by the abnormality detection algorithm, a disease name related to the detected abnormality, a name of the abnormality detection algorithm, a correct answer rate related to the disease name, and an index related to the priority of treatment for the abnormality, and an index related to the reliability of the detected abnormality; displaying the reliability of the anomaly detection result by the anomaly detection algorithm and statistical information regarding the reliability as indicators regarding the reliability of the detected anomaly; A medical information processing method performed by a computer, wherein the statistical information has a histogram of multiple reliability levels, each indicating multiple reliabilities regarding past cases similar to the abnormality or multiple reliabilities regarding multiple past medical images similar to the abnormality.

10. On the computer, determining whether or not there is an emergency regarding the abnormality based on the type of at least one abnormality detection algorithm to which a medical image of a subject is input, or information related to the abnormality detected by inputting the medical image to the abnormality detection algorithm; When it is determined that there is an urgency, displaying confirmation information regarding confirmation of the abnormality and emergency information indicating the urgency on a display adjacent to the test order related to the abnormality in an examination list showing a list of test orders; To achieve this, the confirmation information includes at least one of a medical image including an abnormality detected by the abnormality detection algorithm, a disease name related to the detected abnormality, a name of the abnormality detection algorithm, a correct answer rate related to the disease name, and an index related to the priority of treatment for the abnormality, and an index related to the reliability of the detected abnormality; displaying the reliability of the anomaly detection result by the anomaly detection algorithm and statistical information regarding the reliability as indicators regarding the reliability of the detected anomaly; The statistical information includes a histogram of multiple reliability levels, each of which indicates multiple reliabilities related to past cases similar to the abnormality or multiple reliabilities related to multiple past medical images similar to the abnormality.

Images