Auxiliary diagnosis information processing method and auxiliary diagnosis system

Abstract

The embodiment of the invention provides an auxiliary diagnosis information processing and auxiliary diagnosis system, and the method employs an auxiliary diagnosis result to generate an auxiliary diagnosis report, and the auxiliary diagnosis report comprises an abnormal reason distribution diagram and / or table which is used for indicating at least one abnormal reason causing the abnormality of a test sample and the probability corresponding to each abnormal reason. Compared with an auxiliary diagnosis report of a character version, a doctor does not need to read characters line by line, but can intuitively know the abnormal reasons in a graph and / or table mode, and the doctor can be helped to distinguish the diagnosis probability and possibility of each kind of abnormity while the reliability of the abnormal reasons is increased by increasing the diagnosis probability of the abnormal reasons. On the basis, by providing an interactive response function based on the abnormal reason distribution diagram and / or table, the user can know the diagnosis basis of the abnormal reason diagnosis, so that the abnormal reason diagnosis is reasonable and evidence-based, and the confidence coefficient of the diagnosis is improved.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of medical technology. More specifically, embodiments of the present application relate to a method for processing auxiliary diagnosis information and an auxiliary diagnosis system. Background Art

[0002] With the development of laboratory medicine, the test items in clinical medicine are becoming more and more diverse, and higher requirements are put forward for the accuracy and efficiency of test results.

[0003] Currently, when conducting sample tests, first, a test instrument tests the sample to output test data, and then medical staff issue a test report based on the test data. However, this process depends to a large extent on the knowledge scope and clinical experience of medical staff, resulting in difficulty in guaranteeing the accuracy of the test report. At the same time, the content presented in the test report issued manually is limited, making it difficult for medical staff to make accurate and reliable diagnostic decisions based on the test report.

[0004] Therefore, how to guarantee the accuracy of the test report and improve the visualization degree of the test report are problems that need to be solved urgently at present. Summary of the Invention

[0005] In this context, embodiments of the present application provide a method for processing auxiliary diagnosis information and an auxiliary diagnosis system for guaranteeing the accuracy of a sample test report and improving the visualization degree of the test report.

[0006] In a first aspect, an embodiment of the present application provides a method for processing auxiliary diagnosis information, including:

[0007] Obtaining an auxiliary diagnosis report of a test sample, where the auxiliary diagnosis report is obtained based on the test data of the test sample and sample-related information; the auxiliary diagnosis report includes an abnormal cause distribution map and / or table; the abnormal cause distribution map and / or table is used to indicate at least one abnormal cause that causes the test sample to be abnormal and the diagnosis probability of each abnormal cause;

[0008] When a selection operation triggered by the abnormal cause distribution map / table is obtained, displaying a diagnosis description of the selected abnormal cause, where the diagnosis description includes at least one of a diagnosis basis, a test item, and an abnormal cause description of the test sample.

[0009] [In a second aspect, an embodiment of the present application further provides an auxiliary diagnosis system, including:

[0010] A sample analyzer for testing a test sample to obtain test data;

[0011] An auxiliary diagnosis information providing device for obtaining an auxiliary diagnosis report based on the test data of the test sample and sample-related information, and

[0012] A processing device for auxiliary diagnosis information, which implements the steps of the method for processing auxiliary diagnosis information as described above.

[0013] The method for processing auxiliary diagnosis information provided in the embodiments of the present application uses the auxiliary diagnosis result to generate an auxiliary diagnosis report. The auxiliary diagnosis report includes a distribution map and / or table of abnormal causes, which are used to indicate at least one abnormal cause leading to the abnormality of the test sample and the probability corresponding to each abnormal cause. Compared with the text version of the auxiliary diagnosis report, doctors do not need to read the text line by line, but can intuitively understand the abnormal causes through the map and / or table. Moreover, by adding the diagnosis probability to the abnormal causes, while increasing the credibility of the abnormal causes, it can help doctors distinguish the diagnosis probabilities and possibilities of each abnormality. On this basis, by providing an interactive response function based on the distribution map and / or table of abnormal causes, users can know the diagnostic basis for the diagnosis of the abnormal cause, making the diagnosis of the abnormal cause well-founded and improving the confidence of the diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0015] Figure 1 It is a structural block diagram of the auxiliary diagnosis system provided in the embodiments of the present application;

[0016] Figure 2 It is a schematic flowchart of the method for processing auxiliary diagnosis information provided in the embodiments of the present application;

[0017] Figure 3 It is a schematic interface diagram for displaying diagnostic explanations provided in the embodiments of the present application;

[0018] Figure 4 It is a schematic interface diagram of the auxiliary diagnosis report provided in the embodiments of the present application;

[0019] Figure 5 It is a schematic interface diagram for displaying diagnostic explanations provided in the embodiments of the present application;

[0020] Figure 6 It is a schematic interface diagram of the auxiliary diagnosis report provided in the embodiments of the present application;

[0021] Figure 7Schematic diagram of the interface of the auxiliary diagnosis report provided by the embodiment of the present application;

[0022] Figure 8 Schematic diagram of the abnormal cause distribution table provided by the embodiment of the present application;

[0023] Figure 9 Schematic diagram of the interface for supplementing abnormal causes provided by the embodiment of the present application;

[0024] Figure 10 Schematic diagram of the interface of the sample-related information provided by the embodiment of the present application;

[0025] Figure 11 Schematic diagram of the interface of the sample information provided by the embodiment of the present application;

[0026] Figure 12 Schematic diagram of the interface for clinical symptom treatment provided by the embodiment of the present application;

[0027] Figure 13 Schematic diagram of the interface of the auxiliary diagnosis report provided by the embodiment of the present application;

[0028] Figure 14 Schematic diagram of the structure of the auxiliary diagnosis information providing device provided by the embodiment of the present application;

[0029] Figure 15 Schematic diagram of the target knowledge graph provided by the embodiment of the present application;

[0030] Figure 16 Schematic diagram of the target knowledge graph corresponding to the purulent inflammatory disease provided by the embodiment of the present application;

[0031] Figure 17 Schematic diagram of the structuring of the data to be diagnosed provided by the embodiment of the present application;

[0032] Figure 18 Exemplary prevalence rate radar chart provided by the embodiment of the present application.

[0033] In the drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed implementation manners

[0034] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without making creative efforts shall fall within the protection scope of the present application.

[0035] In the description, claims, and above-mentioned drawings of the embodiments of the present application, terms such as "first" and "second" are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that comprises a series of steps or units does not necessarily limit to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0036] It should be understood that the term "and / or" used herein is only a relationship describing associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. " / " represents the relationship of "or".

[0037] With the development of laboratory medicine, the test items in clinical medicine are becoming more and more diverse, and higher requirements are put forward for the accuracy and efficiency of test results.

[0038] In the related art, when performing sample tests, first, the test instrument tests the sample to output test data, and then medical staff issue a diagnostic report based on the test data. However, the inventor found that the test report involves complex relationships among different parameters, biomarkers, and diseases. Manually analyzing these relationships is very challenging. It is difficult for medical staff to quickly extract key information from multiple parameters, and they are even less able to make full and effective use of this information. Moreover, the content presented in the diagnostic report issued manually is limited and has a low degree of visualization, making it difficult for medical staff to make accurate and reliable diagnostic decisions based on the diagnostic report.

[0039] At the same time, during the test process, medical staff often lack in-depth analysis and accurate judgment of the diagnostic results. When issuing a diagnostic report, they rely to a large extent on the knowledge scope and clinical experience of medical staff. However, the knowledge scope and clinical experience of medical staff may be limited, and they may not be able to deeply understand the clinical significance of each test item, nor comprehensively consider all possible factors and connections related to disease diagnosis. Moreover, due to differences in the educational levels of medical staff, the same test results may lead to different interpretations and conclusions. This subjectivity and difference will affect the accuracy of the diagnosis, and thus it is difficult to guarantee the accuracy of the diagnostic report.

[0040] In addition, from the perspective of scalability, medical staff undertake a large amount of work every day and are not sensitive to the update of medical knowledge. Therefore, when it comes to processing a large amount of data, different data sources, and constantly updated medical knowledge, manual inspection has great limitations.

[0041] In view of this, the embodiments of the present application provide a processing of auxiliary diagnosis information to solve at least one of the above problems. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0042] Figure 1 This is the auxiliary diagnosis system provided by the embodiments of the present application. As Figure 1 shown, the application scenarios provided by the embodiments of the present application include: a sample analyzer 101, an auxiliary diagnosis information processing device 102, and an auxiliary diagnosis information providing device 1023. The auxiliary diagnosis information processing device 102 and the auxiliary diagnosis information providing device 103 are computer program products based on computer program processes to implement the auxiliary diagnosis function, such as various application programs.

[0043] The auxiliary diagnosis information providing device 103 implements an auxiliary diagnosis information providing method to achieve the auxiliary diagnosis function. The auxiliary diagnosis information processing device 102 provides an auxiliary diagnosis information processing method to process the auxiliary diagnosis information to form an auxiliary diagnosis report.

[0044] In some embodiments, the auxiliary diagnosis information providing device 103 and the auxiliary diagnosis information processing device 102 can be integrated in a terminal device, and an auxiliary diagnosis information providing method and an auxiliary diagnosis information processing method are implemented on the terminal.

[0045] In some embodiments, the auxiliary diagnosis information providing device 103 and the auxiliary diagnosis information processing device 102 can also be integrated with the sample analyzer 101, such as a sample analyzer loaded with the corresponding computer program product.

[0046] In some embodiments, the auxiliary diagnosis information processing device 102 can be set to communicate with the output interface of the application system in the sample analyzer 101 that performs test analysis on the sample, and is used to obtain the test data obtained after the test analysis of the sample to be tested from the sample analyzer 101. Among them, the sample to be tested is a sample taken from the body of the sample provider and contains various biological cell information or other biological information, such as blood samples, urine samples, and other body fluid (pleural effusion, cerebrospinal fluid, serous cavity effusion, synovial fluid) samples.

[0047] Specifically, the processing device 102 of the auxiliary diagnosis information obtains the test data obtained by the sample analyzer 101 through testing and analyzing the sample to be tested, and sends the test data to the auxiliary diagnosis information providing device 103. The auxiliary diagnosis information providing device 103 preprocesses the test data to obtain the information to be diagnosed, where the information to be diagnosed includes at least one of the following: the item to be tested, the numerical information corresponding to the item to be tested, and the basic information corresponding to the sample to be tested. Then, based on the target knowledge graph corresponding to the current test item, the information to be diagnosed is matched, so as to obtain the abnormal information corresponding to the sample to be tested according to the matching result, and the auxiliary diagnosis information is obtained.

[0048] The auxiliary diagnosis information providing device 103 sends the auxiliary diagnosis information to the processing device 102 of the auxiliary diagnosis information. The processing device 102 of the auxiliary diagnosis information obtains the auxiliary diagnosis report of the test sample, and the auxiliary diagnosis report is obtained based on the test data of the test sample and the sample-related information; the auxiliary diagnosis report includes a distribution map and / or table of abnormal causes; the distribution map and / or table of abnormal causes is used to indicate at least one abnormal cause that causes the abnormality of the test sample and the diagnosis probability of each abnormal cause; when a selection operation triggered by the distribution map / table of abnormal causes is obtained, the diagnosis description of the selected abnormal cause is displayed, and the diagnosis description includes at least one of the diagnosis basis of the test sample, the test item, and the description of the abnormal cause.

[0049] In this way, the auxiliary diagnosis information providing device 103 in the embodiment of the present application uses the knowledge graph to match the information to be diagnosed, so as to obtain the abnormal information of the sample provider. Compared with manual analysis, the processing device 102 of the auxiliary diagnosis information outputs a diversified auxiliary diagnosis report, and its visualization degree is relatively high, which is convenient for users to more intuitively understand the current existing or potential disease conditions of the patient to whom the sample to be tested belongs by viewing the auxiliary diagnosis report. And when it is determined that there is an abnormality, the decision-making basis can be known through the diagnosis basis provided in the auxiliary diagnosis report, and an accurate auxiliary diagnosis result can be obtained without relying on the personal experience level of the test medical staff. On the one hand, the test efficiency can be improved and the test result is more accurate; on the other hand, the auxiliary diagnosis report includes a distribution map and / or table of abnormal causes, which is used to indicate at least one abnormal cause that causes the abnormality of the test sample and the corresponding probability of each abnormal cause. Doctors do not need to read the text line by line, but can intuitively understand the abnormal causes through the graph and / or table. And by adding the diagnosis probability to the abnormal causes, while increasing the credibility of the abnormal causes, it can help doctors distinguish the diagnosis probability and possibility of each abnormality. On this basis, the auxiliary diagnosis report not only provides users with abnormal causes, but also provides an interactive response function based on the distribution map and / or table of abnormal causes, so that users can obtain the diagnosis basis for knowing the diagnosis of the abnormal cause, making the diagnosis of the abnormal cause well-founded and improving the confidence of the diagnosis.

[0050] Optionally, during the process of determining the auxiliary diagnosis category information, the auxiliary diagnosis information providing device 103 may comprehensively consider various aspects of data of the sample provider, such as clinical information data that can reflect the individual differences of the sample provider, generally including gender, age, medical history, etc. The utilization of the clinical information data by the auxiliary diagnosis information providing device 103 can be reflected in multiple stages: One stage is during the process of the sample analyzer 101 performing test analysis on the test sample to obtain test data. The sample analyzer 101 calibrates the obtained sample test data by considering the clinical information data of the sample provider; Another stage is that the auxiliary diagnosis information providing device 103 directly obtains the clinical information data of the sample provider. During the process of matching the information to be diagnosed with the target knowledge graph and obtaining a matching result, the clinical information data of the sample provider is further comprehensively considered to calibrate the abnormal information corresponding to the test sample. In some embodiments, it is set that the utilization of the clinical information data of the sample provider by the auxiliary diagnosis information providing device 103 includes the situation of the above second stage. The auxiliary diagnosis information providing device 103 is communicatively connected to the laboratory information system (LIS). The laboratory information system generally includes application terminals set at different positions such as the hospital's information desk and the laboratory department, and can be used to receive test data, input and save patient test data, and assist the hospital in information management. The auxiliary diagnosis information providing device 103 can directly obtain the clinical information data of the specified category of the sample provider from the laboratory information system.

[0051] To facilitate the understanding of the technical implementation of the auxiliary diagnosis information providing device 103 provided in the embodiments of the present application, in the description of the present application, specific examples are mainly described in detail taking the test sample as a blood sample. Correspondingly, the sample analyzer 101 is illustrated by a blood cell analyzer, but in actual applications, this should not be used as a limitation. The sample analyzer 21 may also be a biochemical analyzer, an immunoassay analyzer, a coagulation analyzer, and so on.

[0052] In some other embodiments, the test data of the test sample may be from multiple different sample analyzers 101, such as a blood cell analyzer, a biochemical analyzer, and an immunoassay analyzer. Correspondingly, the processing of the auxiliary diagnosis information 102 and the sample test data obtained by the auxiliary diagnosis information providing device 103 may include one or more of blood cell analysis data, biochemical analysis data, and immunoassay analysis data.

[0053] The following uses specific embodiments to detail the technical solutions of the embodiments of the present application and how the technical solutions of the present application solve the above technical problems. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0054] Figure 2 This is a schematic flowchart of the method for processing auxiliary diagnosis information provided by an embodiment of the present application. As Figure 2 shown, the method for processing auxiliary diagnosis information provided by an embodiment of the present application includes:

[0055] Step 202, obtaining an auxiliary diagnosis report of a test sample, where the auxiliary diagnosis report is obtained based on the test data of the test sample and sample-related information; the auxiliary diagnosis report includes a distribution map and / or table of abnormal causes; the distribution map and / or table of abnormal causes is used to indicate at least one abnormal cause that causes the test sample to be abnormal and the diagnosis probability of each abnormal cause.

[0056] Specifically, an auxiliary diagnosis information providing device is configured to obtain the test data of a test sample to be tested, as well as sample-related information, process the test data and the sample-related information to obtain information to be diagnosed, obtain a target knowledge graph, match the information to be diagnosed with the target knowledge graph to obtain a matching result, and output an auxiliary diagnosis report according to the matching result. The auxiliary diagnosis information providing device sends the auxiliary diagnosis report to the auxiliary diagnosis information processing device for processing the auxiliary diagnosis report.

[0057] In this embodiment, by using the auxiliary diagnosis information providing device, compared with manual analysis, the knowledge scope covered by the knowledge graph involved in this device is relatively wide, so it can avoid the influence of subjective factors of medical staff, can quickly extract key information, and can also conduct in-depth analysis and accurate judgment, and both the efficiency and accuracy can be guaranteed.

[0058] The auxiliary diagnosis information processing device obtains the auxiliary diagnosis information of the test sample and processes it into an auxiliary diagnosis report. When a viewing instruction for the auxiliary diagnosis report of the test sample by a doctor is obtained, the auxiliary diagnosis report is displayed for the doctor to view.

[0059] The auxiliary diagnosis report may include a distribution map of abnormal causes, or may include a distribution table of abnormal causes, or may include a distribution map of abnormal causes and a distribution table of abnormal causes. Among them, the distribution map of abnormal causes represents the probability distribution of abnormal causes in the form of a graph. The distribution map of abnormal causes includes a representation area for representing abnormal causes, and the probability of different abnormal causes can be represented by at least one of the area, color, and shape of the abnormal cause representation area.

[0060] The distribution table of abnormal causes represents the probability distribution of abnormal causes in the form of a table. The distribution table of abnormal causes has at least two columns, namely abnormal causes and probabilities, and represents the probabilities of different abnormal causes by the numerical size of the probabilities.

[0061] In this embodiment, by using the distribution map and / or table of abnormal causes, compared with the text representation, doctors do not need to read the text line by line. Instead, through the map and / or table, they can intuitively understand the abnormal causes. Moreover, by increasing the diagnostic probability of abnormal causes, while increasing the credibility of abnormal causes, it can help doctors distinguish the possibilities of each abnormal cause.

[0062] Step 204, when a selection operation triggered by the distribution map / table of abnormal causes is obtained, display the diagnostic description of the selected abnormal cause, where the diagnostic description includes at least one of the diagnostic basis of the test sample, the test items, and the description of the abnormal cause.

[0063] In this embodiment, the distribution map and / or table of abnormal causes in the auxiliary diagnosis report can intuitively show the abnormal causes and the diagnostic probability of each abnormal cause. On this basis, the user can trigger a selection operation based on the distribution map / table of abnormal causes to display the diagnostic description of the indicated abnormal cause to be viewed. The diagnostic description includes at least one of the diagnostic basis, the test items, and the description of the abnormal cause.

[0064] The diagnostic basis refers to the basis for the auxiliary diagnosis information providing device to diagnose this abnormal cause, usually including the abnormal indicators in the test data and sample-related information used to analyze this abnormal cause, making the diagnosis of this abnormal cause reasonable and justifiable, and improving the confidence level of the auxiliary diagnosis.

[0065] The test items refer to the test items required to further verify this abnormal cause. By providing the test items, the user can understand the next inspection items to be done, and at the same time provide the next inspection plan for doctors.

[0066] The description of the abnormal cause includes the cause of the abnormality, abnormal symptoms, etc.

[0067] In this embodiment, by providing an interactive response function based on the distribution map and / or table of abnormal causes, the user can know the diagnostic description of the diagnosis of this abnormal cause, making the diagnosis of this abnormal cause reasonable and justifiable.

[0068] The above method for processing auxiliary diagnosis information generates an auxiliary diagnosis report by using the auxiliary diagnosis result. The auxiliary diagnosis report includes a distribution map and / or table of abnormal causes, which is used to indicate at least one abnormal cause leading to the abnormality of the test sample and the probability corresponding to each abnormal cause. Compared with the text version of the auxiliary diagnosis report, doctors do not need to read the text line by line, but can intuitively understand the abnormal causes through the map and / or table. Moreover, by adding the diagnosis probability to the abnormal causes, while increasing the credibility of the abnormal causes, it can help doctors distinguish the diagnosis probabilities and possibilities of each abnormality. On this basis, by providing an interactive response function based on the distribution map and / or table of abnormal causes, users can know the diagnostic basis for the diagnosis of the abnormal cause, making the diagnosis of the abnormal cause well-founded and improving the confidence of the diagnosis.

[0069] In one embodiment, the auxiliary diagnosis report may only include a distribution map of abnormal causes to display the auxiliary diagnosis result. In this embodiment, the distribution map of abnormal causes includes representation regions corresponding to each abnormal cause. Each representation region is used to represent an abnormal cause. In one embodiment, in order to enable users to intuitively observe the relationship of the probabilities of each abnormal cause, the representation regions corresponding to each abnormal cause in the distribution map of abnormal causes are arranged in order of probability from high to low.

[0070] In another embodiment, in order to enable users to understand the probability level through the graph, the representation region can display the probability level of the abnormal cause through at least one of area, color, and shape. For example, the greater the probability, the larger the area occupied by its representation region. Among them, the shape of the representation region is different according to the form of the graph adopted by the distribution map of abnormal causes.

[0071] In one embodiment, the auxiliary diagnosis result provided by the auxiliary diagnosis information providing device may include multiple abnormal causes. In the case of more abnormal causes, the reference significance of some abnormal causes with lower probabilities is not great. Then, the processing device of the auxiliary diagnosis information can generate a distribution map and / or table of abnormal causes according to the top N abnormal causes with the highest probabilities. In one embodiment, a distribution map and / or table of abnormal causes is generated according to the top 10 abnormal causes with the highest probabilities, and the top 10 abnormal causes with the highest probabilities are displayed in the distribution map of abnormal causes. It can be understood that if the number of abnormal causes provided by the processing device of the auxiliary diagnosis information is less than N, then the abnormal causes are generated according to all the abnormal causes. Therefore, it can be understood that the sum of the diagnosis probabilities of all the abnormal causes in the distribution map and / or table of abnormal causes is not greater than 1.

[0072] In one embodiment, the abnormal cause distribution diagram is used to indicate the diagnostic probability of the abnormal cause. Therefore, the abnormal cause distribution diagram is more suitable for the visualization graph reflecting the proportion. In some embodiments, the abnormal cause distribution diagram includes any one of a pie chart, a radar chart, and a chord diagram. The abnormal cause distribution diagram shows the probability level of the abnormal cause, the number of directed edges, and the occurrence frequency of the abnormal cause through at least one of area, angle, color, and shape.

[0073] Among them, a pie chart and its deformed graphs can be adopted, such as a standard pie chart, a ring chart, a nested pie chart, a rose chart, a ring chart, and a pie chart with a time axis chart.

[0074] Among them, a radar chart and its deformed graphs can also be adopted, such as a standard radar chart, a filled radar chart, and a wormhole radar chart.

[0075] Among them, a chord chart and its deformed graphs can also be adopted, such as a standard chord chart, a multi-list chord chart, and a non-bandage chord chart.

[0076] Taking the pie chart as an example, the pie chart includes multiple sector areas, and each sector area is a representation area of an abnormal cause. The sector area and color represent the probability level of the abnormal cause. The sector area can be adjusted according to the central angle and color.

[0077] Taking the rose chart as an example, the rose chart includes multiple sector areas, and each sector area is a representation area of an abnormal cause. The sector area and color represent the probability level of the abnormal cause. The sector area can be adjusted according to the radius length, central angle, and color.

[0078] In one embodiment, the abnormal cause distribution diagram is also used to indicate the number of directed edges corresponding to the sample to be tested and the occurrence frequency corresponding to the abnormal cause; the number of directed edges is used to indicate the number of clinical findings corresponding to each abnormal cause in the target knowledge graph; the occurrence frequency of the abnormal cause is used to indicate the number of times the correspondence relationship between the clinical findings of the abnormal cause and the abnormal information appears in the literature corresponding to the target knowledge graph.

[0079] Specifically, the target knowledge graph includes nodes and directed edges connecting the nodes.

[0080] Among them, there are two types of nodes. One type represents the abnormal information nodes obtained from various medical guidelines, and the abnormal information nodes contain information such as subsequent examinations and treatment plans for each abnormal item; the other type of node represents the clinical finding nodes, and the clinical finding nodes are the increase / decrease of various test indicators, such as an increase in white blood cells, etc.

[0081] In practical applications, the clinical finding nodes and the abnormal information nodes are connected by directed edges, and the direction of the directed edge is used to indicate the relationship between the clinical finding and the abnormal information, that is, the direction of the directed edge is used to indicate the hint of the clinical finding to the abnormal information.

[0082] To enable users to more intuitively understand the probability distribution relationship of abnormal causes, the representation areas corresponding to each abnormal cause in the probability distribution diagram of abnormal causes are arranged in order of probability from high to low.

[0083] On this basis, the user's selection operation in the representation area of the abnormal cause triggers the display of the diagnostic description of the abnormal cause. When a selection operation triggered by the representation area on the abnormal cause distribution diagram is obtained, according to the trigger position, the diagnostic description of the abnormal cause corresponding to the representation area is displayed in the form of a pop-up window. The selection operation includes at least one of moving the cursor to the representation area, clicking on the representation area, the cursor staying in the representation area for more than a predetermined time, clicking on the selection control, and right-clicking to trigger the selection option.

[0084] In this embodiment, the diagnostic description is displayed in the form of a floating pop-up window, which pops up in response to the user's selection operation. In some implementation examples, the popped-up floating window adaptively adjusts its position and size according to the position of the mouse. Exemplarily, when the mouse is on the left side of the center of the auxiliary diagnostic radar chart, the pop-up window is displayed on the left side, and the right border of the pop-up window is close to the position of the mouse cursor; otherwise, the pop-up window is on the right side.

[0085] In another embodiment, to more intuitively display the interaction relationship of the trigger operation of the representation area in the diagnostic description, the floating window of the diagnostic description adaptively adjusts according to the position of the interaction operation. For example, when the mouse is on the left side of the abnormal cause distribution diagram, the floating pop-up window is also displayed on the right side, and the representation area in the abnormal cause distribution diagram is highlighted. When the mouse trigger is on the right side of the abnormal cause distribution diagram, the floating pop-up window is also displayed on the left side, and the representation area in the abnormal cause distribution diagram is highlighted. Thus, the user can intuitively understand the selected abnormal cause and the diagnosis corresponding to the abnormal cause. The display effect is as Figure 3 shown.

[0086] In another embodiment, the size of the floating pop-up window is fixed. However, when the content of the diagnostic description of some abnormal causes is too much to be fully displayed, truncation processing can be performed on the content of the diagnostic description, and an ellipsis is added to the truncated text. Further, the user can display the complete diagnostic description by continuing to trigger the floating pop-up window.

[0087] In summary, there are five ways to trigger the diagnostic description of the abnormal cause through the abnormal cause distribution diagram:

[0088] The first way: When it is obtained that the cursor moves to the representation area of the abnormal cause, the diagnostic description of the abnormal cause corresponding to the representation area is displayed.

[0089] The second way: When it is obtained that a click operation is performed on the representation area of the abnormal cause, the diagnostic description of the abnormal cause corresponding to the representation area is displayed.

[0090] The third method: when the cursor stays in the representation area for more than a predetermined time, a diagnostic description of the abnormal cause corresponding to the representation area is displayed.

[0091] The fourth method: when the selection control is clicked, a diagnostic description of the abnormal cause corresponding to the representation area is displayed. In this embodiment, a selection control can be set on each representation area of the abnormal cause distribution map.

[0092] The fifth method: when the right mouse button triggers a selection option, a diagnostic description of the abnormal cause corresponding to the representation area is displayed. In this embodiment, selection options can be added, and the selection options pop up by clicking the right mouse button for the user to select.

[0093] Through any one of the above methods, the user can intuitively know the diagnostic description of the abnormal cause through the display interface.

[0094] In another embodiment, when a selection operation triggered by a representation area on the abnormal cause distribution map is obtained, a diagnostic description of the abnormal cause is displayed in the diagnostic description area of the auxiliary diagnostic report.

[0095] As Figure 4 shown, the auxiliary diagnostic report includes an abnormal cause distribution map and a diagnostic description area. The diagnostic description area is below the abnormal cause distribution map. When no representation area is selected, the diagnostic description area is blank. When a representation area is selected on the abnormal cause distribution map, a diagnostic description of the selected abnormal cause is displayed in the diagnostic description area.

[0096] Specifically, when it is obtained that the cursor moves to the representation area, or a click operation on the representation area is obtained, or the cursor stays in the representation area for more than a predetermined time, or the selection control is clicked, or the right mouse button triggers a selection option, the representation area is selected. At the same time, a diagnostic description of the selected abnormal cause is displayed in the auxiliary diagnostic description area. It can be understood that as the number of selected representation areas increases, the diagnostic descriptions in the diagnostic description area also increase.

[0097] In this embodiment, a diagnostic explanation area is provided to display the diagnostic explanations corresponding to the selected representation areas for the abnormal causes. As a result, the content displayed in the diagnostic explanation area can have a visual linkage with the selection operation on the abnormal cause distribution map, and the diagnostic explanations for the selected abnormal causes can be continuously presented in the diagnostic explanation area. For doctors, they only need to select which abnormal cause to collect based on experience and perform the selection operation on the abnormal cause distribution map, and then output the diagnostic explanations for the abnormal cause as an interpretation for auxiliary diagnosis, which improves the operation convenience. At the same time, it is convenient to organize the interpretation instructions for the abnormal causes used in the diagnostic explanation area and present them to the patients. To make the result of the selection operation more intuitive, in one embodiment, when a selection operation triggered by a representation area on the abnormal cause distribution map is obtained, the selected representation area is switched from the original state to a highlighted state; the highlighting methods include any one of increasing the representation area, highlighting the representation area, adding a border to the representation area, and popping the representation area outwards by a preset distance.

[0098] In the original state, the representation areas are all displayed with initial display parameters. When a selection operation triggered by a representation area on the abnormal cause distribution map is obtained, the selected representation area is switched from the original state to a highlighted state. The role of highlighting is to distinguish the selected representation area from the unselected representation areas, enabling the user to intuitively observe the selected representation area.

[0099] An example of highlighting can be to increase the selected representation area. By presenting the enlarged effect of the representation area from the unselected state to the selected state, the display area can be highlighted.

[0100] An example of highlighting can also be to add a border to the representation area. Since a border is added compared to other unselected representation areas, the selected representation area is highlighted compared to the unselected representation areas.

[0101] An example of highlighting can also be to pop the representation area outwards by a preset distance. By presenting the moving effect of the representation area from the unselected state to the selected state, the display area can be highlighted.

[0102] An example of highlighting can also be to highlight the representation area. Compared with highlighting other unselected representation areas, the selected representation area is highlighted compared to the unselected representation areas.

[0103] In this embodiment, by highlighting the selected representation area, the representation area of the selection operation is made more intuitive, and the user can operate the abnormal cause they want to select through the abnormal cause distribution map.

[0104] In another embodiment, when an operation to cancel the selected representation area is obtained, the representation area is restored to its original state; the cancel selection operation includes at least one of: moving the cursor away from the representation area, clicking on the selected representation area, clicking on the cancel control, and right-click triggering operation; the diagnostic description of the abnormal cause corresponding to the representation area is cancelled from display.

[0105] In some embodiments, if the user has viewed the diagnostic description of the abnormal cause corresponding to the representation area, the diagnostic description of the abnormal cause can be cancelled from display through a cancel selection operation. In other embodiments, if the user views the abnormal cause corresponding to the representation area and chooses not to adopt the abnormal cause, the abnormal cause can be deselected and the diagnostic description of the abnormal cause can be cancelled from display through a cancel selection operation.

[0106] When an operation to cancel the selected representation area is obtained, the representation area is restored to its original state, and the representation area is no longer highlighted, that is, it can be observed from the appearance of the representation area that it is in an unselected state. At the same time, the diagnostic description is cancelled from display.

[0107] Specifically, an example of the cancel selection operation can be moving the cursor away from the representation area. When the cursor is moved away from the display area, the representation area is restored to its original state, and the floating pop-up window is closed to cancel the display of the diagnostic description of the abnormal cause, or the diagnostic description of the abnormal cause in the diagnostic description area is deleted.

[0108] Another example of the cancel selection operation can also be clicking on the selected representation area. When clicking on the selected representation area, the representation area is restored to its original state, and the floating pop-up window is closed to cancel the display of the diagnostic description of the abnormal cause, or the diagnostic description of the abnormal cause in the diagnostic description area is deleted.

[0109] Another example of the cancel selection operation can also be clicking on the cancel control. By setting a cancel control in each selected representation area, when an operation on the cancel control is obtained, the representation area is restored to its original state, and the floating pop-up window is closed to cancel the display of the diagnostic description of the abnormal cause, or the diagnostic description of the abnormal cause in the diagnostic description area is deleted.

[0110] Another example of the cancel selection operation can also be a right-click triggered cancel operation. By right-clicking to trigger an option list, the option list includes a cancel option. When the right-click triggered cancel operation is obtained, the representation area is restored to its original state, the floating pop-up window is closed to cancel the display of the diagnostic description of the abnormal cause, or the diagnostic description of the abnormal cause in the diagnostic description area is deleted.

[0111] In this embodiment, by canceling the selected representation area, the diagnostic description of the abnormal cause corresponding to the displayed representation area is canceled, which facilitates the doctor to adopt and cancel the auxiliary diagnosis conclusion.

[0112] In another embodiment, the auxiliary diagnosis report may only include an abnormal cause distribution table, which is in the form of a table. The table may include at least two examples, namely, abnormal cause and diagnosis probability. Thus, the user can know the diagnosis conclusion provided by the auxiliary diagnosis through the abnormal cause distribution table.

[0113] In one embodiment, in order to enable the user to intuitively observe the probability relationship of each abnormal cause, each abnormal cause in the abnormal cause distribution table is arranged in order of probability.

[0114] In one embodiment, the auxiliary diagnosis results provided by the auxiliary diagnosis information providing device may include multiple abnormal causes. When there are many abnormal causes, some abnormal causes with lower probabilities are not of great reference significance. Then, the auxiliary diagnosis information processing device may generate an abnormal cause distribution map and / or table based on the top N abnormal causes with the highest probabilities. In one embodiment, an abnormal cause distribution map and / or table is generated based on the top 10 abnormal causes with the highest probabilities, and the top 10 abnormal causes with the highest probabilities are displayed in the abnormal cause distribution map. It is understandable that if the abnormal causes provided by the auxiliary diagnosis information processing device are less than N, an abnormal cause probability distribution map and / or table is generated based on all abnormal causes. Therefore, it is understandable that the sum of the diagnostic probabilities of all abnormal causes in the abnormal cause distribution map and / or table is not greater than 1.

[0115] In one embodiment, when a selection operation on a cell is obtained based on the abnormal cause distribution table, a diagnostic description of the abnormal cause corresponding to the cell is displayed in a pop-up window according to the triggering position.

[0116] The specific method of the selection operation is similar to the selection operation method based on the abnormal cause distribution map. For example, the selection operation includes moving the cursor to the cell of the abnormal cause, clicking the cell of the abnormal cause, the cursor staying in the cell of the abnormal cause for more than a predetermined time, clicking the selection control of the abnormal cause, and right-clicking to trigger at least one of the selection options. The specific selection process will not be repeated here.

[0117] The process of displaying the diagnosis description of the abnormal cause corresponding to the cell in the form of a pop-up window is similar to the process of displaying the diagnosis description of the abnormal cause in the abnormal cause distribution diagram in the form of a pop-up window, and will not be repeated here. Figure 5In this embodiment, when the user passes through a cell in the abnormal cause distribution table, the diagnosis description of the abnormal cause corresponding to the cell is displayed through a pop-up window, and the user can intuitively know the diagnosis description of the abnormal cause through the display interface.

[0118] Optionally, in some embodiments, the selection operation includes a first type of selection operation and a second type of selection operation, and the first type of selection operation and the second type of selection operation have different corresponding operation modes. When a selection operation triggered by a cell in the abnormal cause distribution table is obtained, a diagnosis description of the abnormal cause corresponding to the cell can be displayed in a pop-up window according to the triggering position; when a second selection operation triggered by a cell in the abnormal cause distribution table is obtained, the diagnosis description of the abnormal cause is displayed in the diagnosis description area of ​​the auxiliary diagnosis report.

[0119] The first selection operation and the second selection operation can be set according to actual application requirements and are not limited here. For example, the first selection operation can be one or more of moving the cursor to the cell, clicking the cell, and the cursor staying in the cell for more than a predetermined time, and the second selection operation can be one or more of clicking a selection control, right-clicking to trigger a selection option, etc.

[0120] Optionally, the selection operation also includes a third type of selection operation. When a third selection operation triggered by a cell on the abnormal cause distribution table is obtained, the diagnostic description of the abnormal cause corresponding to the cell can be displayed in a pop-up window according to the trigger position and the diagnostic description of the abnormal cause can be displayed in the diagnostic description area of ​​the auxiliary diagnostic report.

[0121] In another embodiment, when a selection operation on a cell triggered by an abnormal cause distribution table is obtained, a diagnostic description of the abnormal cause corresponding to the cell is displayed in a diagnostic description area, and the selection operation includes moving the cursor to the cell of the abnormal cause, clicking the cell of the abnormal cause, the cursor staying in the cell of the abnormal cause for more than a predetermined time, clicking the selection control of the abnormal cause, and right-clicking to trigger at least one of the selection options, and the diagnostic description area is below the abnormal cause distribution table.

[0122] The specific method of displaying the diagnosis description in the diagnosis description area based on the selection operation in the abnormal cause distribution table is similar to the specific method of displaying the diagnosis description in the diagnosis description area based on the selection operation in the abnormal cause distribution graph, and will not be repeated here. Figure 6 shown.

[0123] In this embodiment, a diagnosis description area is provided to display the diagnosis description corresponding to the selected representation area for the abnormal cause, so that the content displayed in the diagnosis description area can have a visual linkage with the selection operation of the abnormal cause distribution table, and the diagnosis description of the selected abnormal cause can be continuously presented in the diagnosis description area. For doctors, they only need to select which abnormal cause to collect according to experience and perform the selection operation on the abnormal cause distribution table, and output the diagnosis description of the abnormal cause as an interpretation of the auxiliary diagnosis description, which improves the operation convenience. At the same time, it is convenient to use the diagnosis description area to regularize the interpretation description of the abnormal cause adopted and present it to the patient.

[0124] In another embodiment, the auxiliary diagnosis report includes an abnormal cause distribution map, an abnormal cause distribution table, and a diagnosis description area. Among them, the abnormal cause distribution map can be located above or to the left of the abnormal cause distribution map, and the diagnosis description area can be located below the abnormal cause distribution table. As Figure 7 shown, the abnormal cause distribution map can be located above the abnormal cause distribution map, and the diagnosis description area can be located below the abnormal cause distribution table.

[0125] The abnormal cause distribution map can visually and intuitively know the abnormal cause distribution from the graph. When a trigger operation based on the abnormal cause distribution map is obtained, according to the trigger position, the diagnosis description of the abnormal cause corresponding to the representation area is displayed in the form of a pop-up window. Among them, the selection operation includes at least one of moving the cursor to the representation area, clicking on the representation area, the cursor staying in the representation area for more than a predetermined time, clicking on the selection control, and right-clicking to trigger the selection option.

[0126] When a selection operation triggered by a representation area on the abnormal cause distribution map is obtained, the selected representation area is switched from the original state to a highlighted state; the highlighting methods include: enlarging the representation area, highlighting the representation area, adding a border to the representation area, and popping the representation area outwards by a preset distance.

[0127] When a cancellation operation for the selected representation area is obtained, the representation area is restored to the original state; the cancellation selection operation includes at least one of moving the cursor away from the representation area, clicking on the selected representation area, clicking on the cancellation control, and right-clicking to trigger the cancellation operation; closing the floating pop-up window for displaying the diagnosis description.

[0128] Optionally, in some embodiments, the selection operation includes a first type of selection operation and a second type of selection operation, and the operation methods corresponding to the first type of selection operation and the second selection operation are different. When a selection operation triggered by a representation area on the abnormal cause distribution map is obtained, a diagnosis description of the abnormal cause corresponding to the representation area can be displayed in the form of a pop-up window according to the trigger position; when a second selection operation triggered by a representation area on the abnormal cause distribution map is obtained, the diagnosis description of the abnormal cause is displayed in the diagnosis description area of the auxiliary diagnosis report.

[0129] The first selection operation and the second selection operation can be set according to actual application requirements and are not limited here. For example, the first selection operation can be one or more of moving the cursor to the representation area, clicking on the representation area, and the cursor staying in the representation area for more than a predetermined time, and the second selection operation can be one or more of clicking on a selection control, triggering a right-click selection option, etc.

[0130] Optionally, the selection operation further includes a third type of selection operation. When a third selection operation triggered by a representation area on the abnormal cause distribution map is obtained, a diagnosis description of the abnormal cause corresponding to the representation area can be displayed in the form of a pop-up window according to the trigger position and the diagnosis description of the abnormal cause is displayed in the diagnosis description area of the auxiliary diagnosis report. In summary, through the abnormal cause distribution map, the user can select the diagnosis description of the abnormal cause to be viewed by operating the cursor.

[0131] The abnormal cause distribution table shows each abnormal cause and its diagnosis probability in the form of a table. The user can select the abnormal cause to be adopted based on the abnormal cause distribution table. When a selection operation triggered by the abnormal cause distribution table is obtained, the diagnosis description of the abnormal cause is displayed in the diagnosis description area of the auxiliary diagnosis report. That is to say, the diagnosis description area is used to display the diagnosis description of the adopted abnormal cause.

[0132] When a deselected operation on the selected abnormal cause is obtained in the diagnosis description area, the diagnosis description of the abnormal cause in the diagnosis description area is deleted.

[0133] In summary, through the abnormal cause distribution table, the user can select the abnormal cause to be adopted by operating on the cells of the abnormal cause, and the diagnosis description of the abnormal cause is displayed in the diagnosis description area. Among them, the diagnosis descriptions of the abnormal causes are displayed in sequence according to the time when the abnormal causes are selected.

[0134] Considering that the abnormal causes provided by the possible auxiliary diagnosis may be imperfect. For example, the doctor determines that the possible abnormal cause is A based on his own experience, but the abnormal causes provided by the auxiliary diagnosis do not include A. In view of this situation, in this embodiment, a supplementary function for abnormal causes can also be provided, so that manual supplementation of abnormal causes can be performed.

[0135] In one embodiment, the method for processing auxiliary diagnosis information further includes: when a supplementary operation for the abnormal cause is obtained, obtaining the supplementary abnormal cause and the diagnosis description of the supplementary abnormal cause; adding the supplementary abnormal cause to the abnormal cause distribution map and / or table, and storing the diagnosis description of the supplementary abnormal cause, and the diagnosis description of the supplementary abnormal cause is displayed when triggered to view.

[0136] For auxiliary diagnosis information, if the user needs to supplement the abnormal cause based on experience, it can be supplemented through a supplementary operation. Among them, the supplementary operation can be triggered based on the abnormal cause distribution map or the abnormal cause distribution table.

[0137] In one embodiment, a supplementary control can be set in the abnormal cause distribution map. When the user triggers the control, the supplementary abnormal cause is displayed in the abnormal cause distribution map and / or the abnormal cause distribution table.

[0138] In one embodiment, a supplementary control can be set in the abnormal cause distribution table. When the user triggers the control, the supplementary abnormal cause is displayed in the abnormal cause distribution map and / or the abnormal cause distribution table. As Figure 8 shown, the supplementary control is the "Add" control in the figure. After triggering the addition, a Figure 9 shown custom pop-up window appears, and this custom pop-up window guides the user to fill in the abnormal cause and the diagnosis description. After the user fills it out, the supplementary abnormal cause is displayed in the Figure 8 shown abnormal cause distribution table.

[0139] The diagnosis description of the supplementary abnormal cause is displayed when the supplementary abnormal cause is selected. The display method of the diagnosis description of the abnormal cause and the selection method of the supplementary abnormal cause are the same as the processing methods of other abnormal causes, which will not be elaborated here.

[0140] As mentioned above, the auxiliary diagnosis system is obtained based on the test data of the test sample and the sample-related information, and the doctor can also supplement the abnormal cause and its diagnosis description according to experience. Both of these methods require accurate test data and sample-related information as the basis. Among them, the sample-related information can include sample information, clinical information of the sample provider, and custom parameters. When any one of the sample information, clinical information of the sample provider, and custom parameters changes, the provision of auxiliary diagnosis information can be triggered again.

[0141] In one embodiment, a sample information interface, a custom parameter interface, and a clinical information selection interface are provided. For the convenience of user operation, the three interfaces can be set on one page, as Figure 10 shown.

[0142] In another embodiment, the sample information interface, the custom parameter interface, and the clinical information selection interface can also be set separately. Among them, a sample information interface is provided. As Figure 11 shown, in the sample information interface, the user can view and edit. The sample information may include basic information of the sample provider, such as age, gender, etc. The input of clinical symptoms can be triggered in the sample information interface. Clinical symptoms are more important for auxiliary diagnosis. Different diseases may have different clinical manifestations, and different clinical manifestations will correspond to different diagnostic results. Doctors can select and input clinical information according to the clinical manifestations of the sample provider. The clinical information selection interface of one embodiment is as Figure 12 shown. The selected clinical symptoms will be displayed in the selected symptoms box below. If it is found that the selection is incorrect, the selection can be cancelled by clicking the red cross in the upper right corner of the corresponding symptom. Among them, the selected state represents the selected state of abnormal information, including all the currently selected abnormal information.

[0143] The custom parameter is a supplementary method provided by the system for parameters outside the system. For custom parameters, they can also be recorded as necessary conditions for diseases in the data storage module. It can specify the edges of the knowledge graph. As long as the knowledge graph records the relevant custom parameters, the custom parameters can be used as one of the inputs. For example, some parameters required for auxiliary diagnosis are not processed by the sample analyzer but by other instruments. At this time, they can be entered in the form of custom parameters. In one embodiment, a custom parameter interface is also provided to facilitate doctors to enter custom parameters according to actual needs.

[0144] In one embodiment, in response to an edit operation on at least one of the sample information, clinical information, and custom information triggered by the sample-related information interface, the sample information, clinical information, and custom information are updated; in response to a report update operation, the auxiliary diagnosis information providing device is instructed to update the auxiliary diagnosis report according to at least one of the updated sample information, clinical information, and / or custom information; wherein, the report update operation includes at least one of a confirmation operation of the edit operation and an update operation of the auxiliary diagnosis report.

[0145] For example, obtain an edit and confirmation operation on at least one of the sample information, clinical information, and custom information triggered by the sample-related information interface; update the auxiliary diagnosis report according to the updated sample information, clinical information, and / or custom information indicated by the edit and confirmation operation. In this embodiment, when the user confirms the edit operation, such as saving the edited information, the auxiliary diagnosis report is updated.

[0146] Among them, the sample-related information interface is the sample information interface, the clinical information selection interface, and the custom parameter interface mentioned above. When the user triggers an edit and confirmation operation based on any one of the above three interfaces, the auxiliary diagnosis report is updated according to the sample information, clinical information, and / or custom information indicated by the edit and confirmation operation, that is, it is updated immediately after the information is saved.

[0147] For another example, obtain an edit and confirmation operation on at least one of the sample information, clinical information, and custom information triggered based on the sample-related information interface; trigger an information update prompt according to the sample information, clinical information, and / or custom information indicated by the edit and confirmation operation; in response to a diagnosis update instruction triggered based on the information update prompt, instruct the auxiliary diagnosis information providing device to update the auxiliary diagnosis report according to the updated sample information, clinical information, and / or custom information.

[0148] In this embodiment, when the user triggers an edit and confirmation operation based on any one of the above three interfaces, an information update prompt is performed on the auxiliary diagnosis report interface. The information update prompt is used to prompt the user that the sample-related information has been modified and the auxiliary diagnosis may also change. Options to update or not update can be provided for the user to choose. When the user triggers the update option, an update instruction is generated, and the update instruction is used to instruct the auxiliary diagnosis information providing device to update the auxiliary diagnosis report according to the updated sample information, clinical information, and / or custom information. That is, in this embodiment, after the sample-related information is updated, the user is prompted to update the information, and the user can choose whether to update the auxiliary diagnosis report.

[0149] Some existing auxiliary diagnosis systems do not support the entry of custom information, as well as the modification of clinical information and sample information. In this embodiment, by performing update operations on the sample-related interface for sample information, clinical information, and custom information, it is ensured that accurate and complete information can be entered. And after the above information is updated, the update of the auxiliary diagnosis report is correspondingly triggered, so that the auxiliary diagnosis report is updated in a timely manner, ensuring the accuracy of the auxiliary diagnosis report.

[0150] In one embodiment, the auxiliary diagnosis report includes a distribution map and / or table of abnormal causes, and a diagnosis description area. As described above, the diagnosis description area is used to display the diagnosis description of the abnormal causes adopted. When a print operation of the auxiliary diagnosis report is received, the auxiliary diagnosis report is printed, so that the user can know the content of the auxiliary diagnosis, the abnormal causes adopted by the doctor, and the abnormal descriptions of the abnormal causes according to the auxiliary diagnosis report.

[0151] In one embodiment, the display priority of the selected abnormal causes is determined according to at least one of the order in which the abnormal causes are selected, the diagnostic probability of the abnormal causes, and the supplementary abnormal causes; the diagnostic explanations of the selected abnormal causes are sorted and displayed according to the display priority; when a print operation of the auxiliary diagnostic report is received, the auxiliary diagnostic report is printed, and the auxiliary diagnostic report includes a distribution map and / or table of abnormal causes, and a diagnostic explanation area sorted according to the display priority.

[0152] Among them, the display priority is used to determine the display order of the diagnostic explanations of the abnormal causes in the diagnostic explanation area. From the perspective of the user's viewing habit, the higher the display priority, the greater the possibility that the abnormal cause causes the sample to be abnormal. Therefore, by displaying the diagnostic explanations of the abnormal causes in the diagnostic explanation area according to the display priority, the user can be given a hint of the degree of possibility of the abnormal cause.

[0153] In one embodiment, the display priority of the selected abnormal causes can be determined according to at least one of the order in which the abnormal causes are selected, the diagnostic probability of the abnormal causes, and the supplementary abnormal causes.

[0154] When the user performs actual business operations, the user usually selects according to the degree of possibility of the abnormal causes. For example, the user first selects the abnormal cause that is considered to be the most likely, and then selects some abnormal causes with lower possibility. Therefore, considering the order in which the abnormal causes are selected can conform to the user's actual business operation habits.

[0155] In one embodiment, the diagnostic explanations of the selected abnormal causes are displayed in the diagnostic explanation area according to the order in which the abnormal causes are selected; when a print operation of the auxiliary diagnostic report is received, the auxiliary diagnostic report is printed, and the auxiliary diagnostic report includes a distribution map and / or table of abnormal causes, and the diagnostic explanation area. In this embodiment, the diagnostic explanations of the abnormal causes in the auxiliary diagnostic report are printed in the order in which the abnormal causes are selected. When performing actual business operations, the user can determine the order of selecting the abnormal causes according to the importance of the abnormal causes.

[0156] In one embodiment, the diagnostic probability of the abnormal cause can indicate the degree of possibility of the abnormal cause. Therefore, considering the diagnostic probability of the abnormal cause can reflect the degree of possibility of the abnormal cause.

[0157] In one embodiment, when the abnormal cause is selected, the display priority is determined according to the diagnostic probability of the abnormal cause. The higher the diagnostic probability, the greater the display priority. The diagnostic explanations of the selected abnormal causes are sorted and displayed according to the display priority. When a print operation of the auxiliary diagnostic report is received, the auxiliary diagnostic report is printed. The auxiliary diagnostic report includes a distribution map and / or table of abnormal causes, and the diagnostic explanation area. In this embodiment, the diagnostic explanations of the selected abnormal causes are sorted and displayed according to the descending order of the diagnostic probabilities of the selected abnormal causes, so that the diagnostic explanations of the abnormal causes in the auxiliary diagnostic report are printed according to the diagnostic probabilities of the selected abnormal causes.

[0158] In another embodiment, when the user adds a supplementary abnormal cause and the supplementary abnormal cause is selected, the degree of possibility of the supplementary abnormal cause is the highest. Therefore, when the selected supplementary abnormal cause is selected, the supplementary abnormal cause is determined as the highest display priority, and the diagnostic explanations of the selected abnormal causes are sorted and displayed according to the display priority. When a print operation of the auxiliary diagnostic report is received, the auxiliary diagnostic report is printed. The auxiliary diagnostic report includes a distribution map and / or table of abnormal causes, and the diagnostic explanation area. In this embodiment, the selected supplementary abnormal cause has the highest display priority, and the other selected abnormal causes can be sorted and displayed in the order of selection time or in the order of diagnostic probability. In another embodiment, the auxiliary diagnostic report can be printed together with the analysis report of the sample analyzer.

[0159] In another embodiment, the interface of the auxiliary diagnostic report is as Figure 13 shown, including a distribution map of abnormal causes, a distribution table of abnormal causes, an operation area, a diagnostic explanation area, other abnormal areas, and a prompt information area.

[0160] Among them, the distribution map of abnormal causes is used to display the auxiliary diagnostic results of the corresponding sample. In one embodiment, it is used to display the top N abnormal causes with the highest diagnostic probability. The distribution map is presented in the form of a polar area diagram. The center is a blank circle, and the surrounding is fan-shaped areas of different colors with equal radian. Each fan-shaped outer arc has a lead line, and the other end of the lead line is the abnormal cause and the diagnostic probability. The diagnostic probability is in the form of a percentage in the square brackets after the abnormal cause. The radius size of the fan is related to the diagnostic probability. The larger the probability, the longer the radius, and vice versa.

[0161] The distribution table of abnormal causes is divided into two tables on the left and right. Each table has three columns: Print, Abnormal Cause, and Diagnostic Probability. Except for the table headers, each table has six rows. The parsed diagnostic results will first fill the left list, and after filling the left, they will fill the right list. The content of the first column of the table is a checkbox, the content of the second column is the abnormal cause, and the third column is the probability of the diagnosed disease. The probability is a percentage data with two decimal places.

[0162] The diagnostic description area is used to display the diagnostic description of the abnormal cause selected in the abnormal cause distribution table. It can automatically display a scroll bar according to the amount of content. When the content exceeds the lower boundary of the area, a scroll bar will automatically appear on the right side. Clicking on the scroll bar and moving the mouse or using the mouse wheel to scroll will display the content up and down. The content in the diagnostic description area cannot be edited or modified, and can only be added or removed through the selection operation in the abnormal cause distribution table.

[0163] The operation area has three buttons: Add, Modify, and Delete.

[0164] When there is abnormal cause information in the abnormal cause distribution table, at any time only one abnormal cause is in the selected state in the two tables on the left and right. When the abnormal cause parsed by the assisted diagnosis system is selected, the Modify and Delete operation buttons are disabled, and it is not allowed to modify the abnormal cause diagnosed by the system. When the abnormal cause supplemented by the doctor is selected, the Modify and Delete operation buttons are enabled, and the doctor is allowed to modify or delete the supplemented abnormal cause.

[0165] When the number of abnormal causes is less than 12, the Add button is in the active state, and the doctor can supplement abnormal causes. When the number of abnormal causes reaches 12, the Add button will be disabled, and it is prohibited to continue supplementing abnormal causes. When the number of abnormal causes has reached 12 and additional abnormal causes need to be added, one of the supplemented abnormal causes must be deleted first, and then addition is allowed.

[0166] In the area of other possible abnormal causes, for the diagnostic results parsed by the assisted diagnosis, in addition to the first N abnormal causes, there are other abnormal causes with relatively small probabilities. These abnormal causes will be displayed in the area of possible abnormal causes.

[0167] In another embodiment, the assisted diagnosis information providing device, such as Figure 14 shown, includes a data processing module 1301, an assisted diagnosis analysis module 1302, and an assisted diagnosis report output module 1303.

[0168] Specifically, the data processing module 1301 is used to obtain the test data of the sample to be tested and preprocess the test data to obtain the information to be diagnosed.

[0169] It should be noted that the sample to be tested is a sample taken from the body of the sample provider and containing various biological cell information or other biological information; correspondingly, the test data refers to the corresponding analysis data obtained by performing a counting test on various biological samples containing biological cell information or other biological information. For example, the test data can be blood routine test information, such as the abnormal cell types, cell quantity characteristics, cell size characteristics, cell composition ratio characteristics, cell content characteristics, nucleic acid content characteristics, etc. contained in the blood.

[0170] Among them, the information to be diagnosed includes at least one of the following: the item to be tested, the numerical information corresponding to the item to be tested, and the basic information corresponding to the sample to be tested.

[0171] Exemplarily, taking the cell quantity characteristic as the test data, the items to be tested can be: the number of neutrophils, the percentage of neutrophils, the number of eosinophils, the percentage of eosinophils, the number of monocytes, the percentage of monocytes, the number of white blood cells, the percentage of red blood cells, etc. The basic information corresponding to the sample to be tested is the age, species, gender, etc. of the sample provider to which the sample to be tested belongs.

[0172] Among them, obtaining the test data of the sample to be tested may refer to importing, through communication connection with a sample analyzer, the test data obtained by the sample analyzer through testing and analyzing the sample to be tested.

[0173] In some alternative embodiments, the numerical information corresponding to the item to be tested can be converted into an increase or decrease in its index according to the normal range of the corresponding item of the corresponding species.

[0174] In the embodiment of the present application, the data processing module 1301 converts the structured test data into the information to be diagnosed, as the input of the auxiliary diagnosis and analysis module 1302. Specifically, after the data processing module 301 converts all the test items, the program outputs all the knowledge as a temporary intermediate file. Among them, each line in the temporary intermediate file is the result of a single converted test item. Among them, the content of the test item result includes the sample number, species name, test package name, Chinese name of the test item, English name of the test item, floating situation of the test index, floating percentage, test item value, etc.

[0175] It should be noted that the test package names, Chinese names of the test items, and English names of the test items obtained by different instruments and hospitals may be different, and the embodiments of the present application are not limited thereto.

[0176] The auxiliary diagnosis and analysis module 1302 is used to obtain the information to be diagnosed obtained by the data processing module 1301, and obtain the target knowledge graph, so as to match the information to be diagnosed with the target knowledge graph to obtain a matching result.

[0177] Specifically, during the matching process, the auxiliary diagnosis and analysis module 1302 matches the to-be-diagnosed information from the data processing module 1301 with the target knowledge graph according to the direction indicated by the edges in the target knowledge graph, so as to count the frequencies of various abnormal causes, and then determine a candidate list of abnormal causes based on the frequencies of various abnormal causes, and determine the next inspection and treatment information based on the candidate list of abnormal causes.

[0178] Among them, the target knowledge graph can be a knowledge graph composed of information such as the test items of the sample provider and the subsequent inspections and treatment plans for abnormal causes. Different test categories can correspond to different knowledge graphs.

[0179] In an optional implementation manner, after obtaining the to-be-diagnosed information of the data processing module 301, the auxiliary diagnosis and analysis module 302 obtains the target knowledge graph corresponding to the test item according to the test category corresponding to the to-be-diagnosed information. Exemplarily, taking the current test item as the diagnosis of animal blood routine as an example, the sources of the target knowledge graph include various disease differential diagnosis guidelines and medical guide literatures, such as "Small Animal Medical Differential Diagnosis", "Color Atlas of Laboratory Tests and Diagnosis of Pet Diseases with Case Analysis", etc.

[0180] Figure 15 It is a schematic diagram of the target knowledge graph provided by the embodiments of the present application. As Figure 15 shown, the target knowledge graph includes nodes and directed edges connecting the nodes.

[0181] Among them, there are two types of nodes in total. One type represents abnormal information nodes obtained from various medical guidelines, and the abnormal information nodes contain information such as subsequent inspections and treatment plans for various abnormal causes; the other type of node represents clinical findings nodes, and the clinical findings nodes are the increase / decrease of various indicators in the test, such as the increase of white blood cells, etc.

[0182] In practical applications, the clinical findings nodes and the abnormal information nodes are connected by directed edges, and the direction of the directed edges is used to indicate the relationship between the clinical findings and the abnormal information, that is, the direction of the directed edges is used to indicate the hint of the clinical findings to the abnormal information.

[0183] It should be noted that the names of the nodes in the target knowledge graph are all unique, and the name of the edge is result hint, which represents the relationship between different types of nodes. The direction of the edge represents the sequence between the two connected nodes (that is, the clinical findings node and the abnormal information node), and the edge contains the number of times the current clinical findings and abnormal information appear in how many literatures and the connection weight of the nodes (for example, the initial connection weight can be set to 1).

[0184] Figure 16Schematic diagram of the target knowledge graph corresponding to the abnormal cause being a suppurative inflammatory disease provided by the embodiments of the present application. As Figure 16 shown, the clinical findings corresponding to suppurative inflammatory diseases include: an increase in the number of neutrophils, an increase in the percentage of neutrophils, an increase in the number of eosinophils, an increase in the percentage of eosinophils, an increase in the number of monocytes, an increase in the percentage of monocytes, an increase in the number of white blood cells, and an increase in the percentage of red blood cells, etc.

[0185] During the matching process, when any one or more of the above clinical findings appear in the data to be diagnosed, the abnormal cause it points to is "suppurative inflammation".

[0186] The auxiliary diagnosis information providing device in the embodiments of the present application uses a knowledge graph to match the information to be diagnosed, obtains a matching result, and then outputs an auxiliary diagnosis report based on the matching result. Compared with manual analysis, the knowledge graph involved in this device covers a wider range of knowledge, so it can avoid the influence of subjective factors of medical staff, can quickly extract key information, and can also conduct in-depth analysis and accurate judgment, ensuring both efficiency and accuracy.

[0187] In addition, it should be noted that this knowledge graph can be dynamically expanded according to actual needs to update nodes and relationships. For example, when there is new blood routine knowledge about suppurative inflammation, the new knowledge is added to the knowledge graph or the original knowledge is modified, so that medical staff can obtain new blood routine knowledge in a timely manner during clinical work and provide standardized examinations and treatments to patients with suppurative inflammation according to the latest diagnosis and treatment plan according to the actual situation.

[0188] Furthermore, after obtaining the information to be diagnosed, the auxiliary diagnosis analysis module 1302 can perform matching in the target knowledge graph according to methods such as the similarity between texts and the Euclidean distance between text vectors, so as to obtain the relationship between the clinical findings and abnormal information in the knowledge graph.

[0189] In a specific implementation, the following formula can be used to find all abnormalities corresponding to this knowledge in the target knowledge graph:

[0190]

[0191] where K is the edge between abnormal information and test items, and S = {a 1 , a 2 ,... a n} is the set of test items.

[0192] Specifically, the auxiliary diagnosis and analysis module 1302 obtains the information to be diagnosed based on the temporary intermediate file of the data processing module 1301, and matches the abnormal causes corresponding to the information to be diagnosed in the target knowledge graph from the items to be tested and / or the numerical information corresponding to the items to be tested indicated in the information to be diagnosed, and obtains the first occurrence frequency of at least one abnormal cause corresponding to the sample to be tested according to the matching result. The first occurrence frequency is used to indicate the number of occurrences of the corresponding relationship between the clinical findings of the abnormal cause and the abnormal information in the literature corresponding to the target knowledge graph.

[0193] The auxiliary diagnosis and analysis module 1302 will repeat the above steps until the combination of the test item names and the floating conditions of the test items in the target knowledge graph is completely traversed, and finally count the first occurrence frequency of at least one abnormal cause corresponding to the sample to be tested in the target knowledge graph.

[0194] It should be added that after obtaining the first occurrence frequency of each abnormal cause, there may be a situation where the frequencies of multiple abnormal causes are the same. And the more guide literatures a relationship between a clinical finding and abnormal information appears in, the greater the weight of this knowledge. Therefore, when the frequencies of the abnormal causes corresponding to the clinical findings are the same, the frequencies of the clinical findings and abnormal information in different literatures can also be used for sorting.

[0195] Specifically, the auxiliary diagnosis and analysis module 1302 is further configured to: when the first occurrence frequencies of at least two abnormal causes corresponding to the sample to be tested are the same, obtain the second occurrence frequency of the abnormal causes with the same frequency in the preset literature, and calculate the probability of the first abnormal cause and each first abnormal cause according to the first occurrence frequency and the second occurrence frequency.

[0196] Regarding the preset literature, the embodiments of the present application do not make special limitations. For example, different information to be diagnosed corresponds to different preset literature sets, and the preset literature to be searched can be determined according to the information to be diagnosed.

[0197] Exemplarily, after matching through the target knowledge graph, the first occurrence frequencies of abnormal cause A, abnormal cause B, and abnormal cause C are all X times. The preset literature corresponding to the information to be diagnosed can be found to be Literature 1, Literature 2, and Literature 3. At this time, the total number of occurrences of abnormal cause A, abnormal cause B, and abnormal cause C in the 3 literatures is respectively searched and counted as the second occurrence frequency. If the second occurrence frequency of abnormal cause A is greater than the second occurrence frequency of abnormal cause B, and the second occurrence frequency of abnormal cause C is greater than the second occurrence frequency of abnormal cause A, then the target abnormal information is obtained: the probability of abnormal cause C is higher than that of abnormal cause A, and the probability of abnormal cause A is higher than that of abnormal cause B.

[0198] In some alternative embodiments, after obtaining the first occurrence frequency of each abnormal cause, the auxiliary diagnosis analysis module 1302 may further sort at least one abnormal cause according to the first occurrence frequency of at least one abnormal cause corresponding to the sample to be tested, so as to quickly determine the abnormal causes with the same occurrence frequency in the sample to be tested according to the sorting result, thereby improving the efficiency of determining the abnormal causes with the same frequency.

[0199] In some alternative embodiments, the auxiliary diagnosis analysis module 1302 is further configured to: determine the probability corresponding to the first abnormal cause whose occurrence frequency meets the first preset requirement.

[0200] Specifically, the present application embodiments do not limit the specific content of the first abnormal cause that meets the first preset requirement. Exemplarily, it may be set that the abnormal cause with "the first occurrence frequency is greater than N" 1 is the first abnormal cause; or, it may also be set that the abnormal cause with "the first occurrence frequency ranks top M" 1 is the first abnormal cause.

[0201] Further, the auxiliary diagnosis analysis module 1302 is further configured to determine the second abnormal cause whose probability in the first abnormal cause meets the second preset requirement according to the probability.

[0202] Similarly, the present application embodiments do not limit the specific content of the second abnormal cause that meets the second preset requirement. Exemplarily, it may be set that the abnormal cause with "the second occurrence frequency is greater than N" 2 is the second abnormal cause; or, it may also be set that the abnormal cause with "the second occurrence frequency ranks top M" 2 is the second abnormal cause.

[0203] Furthermore, after obtaining the probability corresponding to the second abnormal cause, the auxiliary diagnosis report output module 303 is further configured to: obtain an auxiliary diagnosis rose diagram according to the probability corresponding to the second abnormal cause, and the auxiliary diagnosis rose diagram includes sector regions respectively corresponding to each abnormal cause.

[0204] Wherein, the sector region shows the first occurrence frequency, probability level, number of directed edges, etc. of the abnormal cause through at least one of the radius length, central angle, and region color. The specific content of the auxiliary diagnosis rose diagram will be shown in the subsequent embodiments.

[0205] Figure 17 It is a structured schematic diagram of the data to be diagnosed provided by the embodiments of the present application. It should be noted that after receiving the test data, the data processing module 1301 will convert the test data into the knowledge display mode as shown in Figure 17 and in the auxiliary diagnosis report output module, this content will also be used as the "findings" part and embedded in the visual auxiliary diagnosis report.

[0206] In some embodiments, the auxiliary diagnosis report includes at least one of the following: abnormal information corresponding to the sample to be tested, an auxiliary diagnosis radar chart, a distribution map of abnormal groups, and historical abnormal information of the sample provider. The auxiliary diagnosis radar chart is used to indicate the abnormal reasons corresponding to the sample provider and the probabilities corresponding to each abnormal reason.

[0207] Figure 18 This is an exemplary auxiliary diagnosis rose chart provided by an embodiment of the present application. As Figure 18 shown in FIG. (a) therein, the auxiliary diagnosis rose chart includes sector regions corresponding one by one to each abnormal reason, and the user can clearly see the abnormal reasons corresponding to the sample to be tested in the auxiliary diagnosis radar chart.

[0208] In a specific implementation, the sector region displays the first occurrence frequency, probability level, and number of directed edges of the abnormal reason through at least one of the radius length, central angle, and region color.

[0209] Exemplarily, as Figure 18 shown, the first occurrence frequency corresponding to the abnormal reason type can be indicated by the radius of the sector region, that is, the relationship between the clinical findings and abnormal information corresponding to each abnormal reason appears in how many documents; the probability level of each abnormal reason is indicated by the color of the sector region; the number of central angle degrees of the sector region indicates the number of directed edges of each abnormal reason in the target knowledge graph, where the number of directed edges is used to indicate the number of clinical findings corresponding to each abnormal reason in the target knowledge graph.

[0210] Furthermore, when a triggered selection operation is based, a diagnosis description of the selected abnormal reason is displayed. Please refer to Figure 18 FIG. (a) and FIG. (b) therein. When the cursor of the mouse hovers over the sector region of "blood / bone marrow abnormality or tumor", a diagnosis description of the abnormal reason corresponding to this sector region will pop up. It should be noted that Figure 18 this is only shown exemplarily and is not limited thereto in actual applications.

[0211] It should be noted that the terminal to which the processing device of the auxiliary diagnosis information is applied should have a display function. For example, a smart phone, a personal computer, a medical diagnostic instrument, etc.; or, when the sample analyzer integrated with the auxiliary diagnosis information providing device has a display function, the auxiliary diagnosis report can be displayed through this sample analyzer.

[0212] In this embodiment, the diagnostic information providing system is a medical auxiliary diagnostic device that integrates the detection and analysis of biological samples to obtain test data, and the diagnostic data to be obtained by processing the test data, and performs biological sample analysis and outputs a visual diagnostic test report. The diagnostic information providing system can be, for example, a blood analysis system, which can be obtained by upgrading a blood analyzer, and includes a sampling component, a reaction component, a driving component, and a detection component for detecting and analyzing a blood sample to obtain sample detection data. The auxiliary diagnostic information providing device, as a computer program product that realizes the auxiliary diagnostic function based on a computer program process, can be stored in the memory of the blood analysis system and implemented by the processor to realize the auxiliary diagnostic function of the auxiliary diagnostic information providing device in the embodiments of the present application. The processing device of the auxiliary diagnostic information, as a computer program product that realizes the auxiliary diagnostic function based on a computer program process, can be stored in the memory of the blood analysis system and implemented by the processor to realize the steps of the method for processing the auxiliary diagnostic information in the embodiments of the present application.

[0213] In the above embodiment, it should be understood that the disclosed device and its implementation can be realized in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0214] Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of devices or modules can be in electrical, mechanical or other forms. In addition, in each embodiment of the present application, the functional modules can be integrated in a processing unit, or each module can exist physically alone, or two or more modules can be integrated in a unit. The unit formed by the above modules can be implemented in the form of hardware or in the form of a hardware plus software functional unit.

[0215] The above integrated modules implemented in the form of software functional modules can be stored in a computer-readable storage medium. The above software functional modules are stored in a storage medium and include several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute some steps of the methods in the embodiments of the present application.

[0216] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk, etc. The storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

Claims

1. A method for processing auxiliary diagnosis information, characterized in that, it includes: Obtain an auxiliary diagnosis report of a test sample, where the auxiliary diagnosis report is obtained based on the test data of the test sample and sample-related information; The auxiliary diagnosis report includes an abnormal cause distribution diagram and / or table; the abnormal cause distribution diagram and / or table is used to indicate at least one abnormal cause that causes the test sample to be abnormal and the diagnosis probability of each abnormal cause; When a selection operation triggered by the abnormal cause distribution diagram / table is obtained, display a diagnosis description of the selected abnormal cause, where the diagnosis description includes at least one of the diagnosis basis, test items, and abnormal cause description of the test sample.

2. The method according to claim 1, characterized in that, The abnormal cause distribution diagram includes representation areas corresponding to each abnormal cause; When a selection operation triggered by the abnormal cause distribution diagram / table is obtained, displaying a diagnosis description of the selected abnormal cause includes at least one of the following methods: The first method: When a selection operation triggered by a representation area on the abnormal cause distribution diagram is obtained, according to the trigger position, display a diagnosis description of the abnormal cause corresponding to the representation area in the form of a pop-up window; the selection operation includes at least one of moving the cursor to the representation area, clicking on the representation area, the cursor staying in the representation area for more than a predetermined time, clicking on a selection control, and right-clicking to trigger a selection option; The second method: When a selection operation triggered by a representation area on the abnormal cause distribution diagram is obtained, display a diagnosis description of the abnormal cause in the diagnosis description area of the auxiliary diagnosis report; the diagnosis description area is below the abnormal cause distribution diagram; the selection operation includes at least one of moving the cursor to the representation area, clicking on the representation area, the cursor staying in the representation area for more than a predetermined time, clicking on a selection control, and right-clicking to trigger a selection option.

3. The method according to claim 2, characterized in that, The method further includes: When a selection operation triggered by a representation area on the abnormal cause distribution diagram is obtained, switch the selected representation area from the original state to a highlighted state; the highlighting method includes any one of increasing the representation area, highlighting the representation area, adding a border to the representation area, and popping the representation area outwards by a preset distance.

4. The method according to claim 3, characterized in that, The method further includes: When a cancellation operation on the selected representation area is obtained, restore the representation area to the original state; the cancellation selection operation includes at least one of moving the cursor away from the representation area, clicking on the selected representation area, clicking on a cancellation control, and right-clicking to trigger a cancellation selection option; Cancel displaying the diagnosis description of the abnormal cause corresponding to the representation area.

5. The method according to claim 1 or 2, characterized in that, The abnormal causes in the abnormal cause distribution table are arranged in descending order of probability; When a selection operation triggered by the abnormal cause distribution map / table is obtained, a diagnostic description of the selected abnormal cause is displayed, including at least one of the following methods: The first method: when a selection operation on a cell triggered by the abnormal cause distribution table is obtained, a diagnostic description of the abnormal cause corresponding to the cell is displayed in the form of a pop-up window according to the trigger position; the selection operation includes at least one of moving the cursor to the cell of the abnormal cause, clicking on the cell of the abnormal cause, the cursor staying in the cell of the abnormal cause for more than a predetermined time, clicking on the selection control of the abnormal cause, and right-clicking to trigger a selection option; The second method: when a selection operation on a cell triggered by the abnormal cause distribution table is obtained, a diagnostic description of the abnormal cause corresponding to the cell is displayed in the diagnostic description area, the selection operation includes at least one of moving the cursor to the cell of the abnormal cause, clicking on the cell of the abnormal cause, the cursor staying in the cell of the abnormal cause for more than a predetermined time, clicking on the selection control of the abnormal cause, and right-clicking to trigger a selection option, and the diagnostic description area is below the abnormal cause distribution table.

6. The method according to claim 2, wherein, The abnormal cause distribution map is further used to indicate the number of directed edges corresponding to the sample to be tested and the occurrence frequency corresponding to the abnormal cause; The number of directed edges is used to indicate the number of clinical findings corresponding to each abnormal cause in the target knowledge graph; the occurrence frequency of the abnormal cause is used to indicate the number of times the corresponding relationship between the clinical findings of the abnormal cause and the abnormal information appears in the literature corresponding to the target knowledge graph; The abnormal cause distribution map includes any one of a pie chart, a radar chart, and a chord chart, and the abnormal cause distribution map displays the probability level, the number of directed edges, and the occurrence frequency of the abnormal cause through at least one of area, angle, color, and shape.

7. The method according to claim 1, wherein, The method further includes: When a supplementary operation on the abnormal cause is obtained, the supplementary abnormal cause and the diagnostic description of the supplementary abnormal cause are obtained; The supplementary abnormal cause is added to the abnormal cause distribution map and / or table, and the diagnostic description of the supplementary abnormal cause is stored and displayed when the supplementary abnormal cause is selected.

8. The method according to claim 2, 5, or 7, wherein, The method: Determines the display priority of the selected abnormal causes according to at least one of the order in which the abnormal causes are selected, the diagnostic probability of the abnormal causes, and the supplementary abnormal causes; Sorts and displays the diagnostic descriptions of the selected abnormal causes according to the display priority; When a print operation of the auxiliary diagnosis report is received, the auxiliary diagnosis report is printed, and the auxiliary diagnosis report includes an abnormal cause distribution map and / or table, and the diagnostic description area sorted according to the display priority.

9. The method according to claim 1, wherein, the method further comprises: updating the sample information, clinical information, and custom information in response to an editing operation on at least one of the sample information, clinical information, and custom information triggered by a sample-related information interface; in response to a report update operation, instructing an auxiliary diagnosis information providing device to update the auxiliary diagnosis report according to at least one of the updated sample information, clinical information, and / or custom information; wherein the report update operation includes at least one of a confirmation operation for the editing operation and an update operation for the auxiliary diagnosis report.

10. An auxiliary diagnosis system, wherein, it comprises: a sample analyzer for examining a test sample to obtain test data; an auxiliary diagnosis information providing device for obtaining an auxiliary diagnosis report based on the test data of the test sample and sample-related information, and a processing device for auxiliary diagnosis information, which implements the steps of the method for processing auxiliary diagnosis information according to any one of claims 1-9.

Images