A method and system for constructing an intelligent medical instrument knowledge base based on big data resources

Abstract

The application relates to the field of intelligent medical instruments, in particular to a method and system for constructing an intelligent medical instrument knowledge base based on big data resources; the method comprises the following steps: acquiring electronic medical record data and medical instrument data of a hospital information platform to obtain key data of medical records and instruments; constructing a medical instrument use graph according to the key data of medical records and instruments; constructing a department instrument interaction group model and a medical instrument set according to the key data of medical records and instruments; constructing a medical instrument knowledge base according to the medical instrument set and the medical instrument use graph; updating the medical instrument knowledge base to acquire updated medical record data and updated instrument data and obtain an update signal; and re-updating the medical instrument knowledge base through the update signal and the hospital information platform to obtain a dynamic medical instrument knowledge base. The application can improve the timeliness and accuracy of the intelligent medical instrument knowledge base.

Description

Technical Field

[0001] This invention relates to the field of intelligent medical devices, specifically to a method and system for constructing an intelligent medical device knowledge base based on big data resources. Background Technology

[0002] Modern medical institutions are increasingly reliant on various medical devices, which are diverse (such as various imaging equipment, wearable health sensors, in vitro diagnostic instruments, etc.) and involve multiple stages such as procurement, use, maintenance, and disposal throughout their entire life cycle.

[0003] Chinese invention patent CN116049326B discloses a method for constructing a medical device knowledge base, an electronic device, and a storage medium. The method includes: constructing an ER model based on a first operational behavior of a first entity; responding to an event corresponding to a second entity, triggering a second operational behavior of the first entity based on the event's level and the relationship between the first and second entities; and updating the ER model according to the second operational behavior. This invention constructs the relationship type between the first and second entities in the ER model based on the first operational behavior of the first entity, and then determines whether to send the event corresponding to the second entity to the first entity based on the event level and a corresponding push mechanism. This improves user experience, increases user stickiness to the platform, and ultimately maximizes revenue.

[0004] However, during the construction of the intelligent medical device knowledge base, the low timeliness of the knowledge base affects the accuracy of the use of intelligent medical devices, thereby reducing clinical trust and medical efficiency. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the background technology by proposing a method for constructing an intelligent medical device knowledge base based on big data resources.

[0006] The technical solution of this invention: a method for constructing an intelligent medical device knowledge base based on big data resources, comprising the following steps:

[0007] S1. Obtain electronic medical record data and medical device data from the hospital information platform; analyze the electronic medical record data to obtain key data on medical devices; and construct a medical device usage map based on the key data on medical devices.

[0008] S2. Analyze key medical device data in medical records, construct a departmental device interaction group model, and obtain a set of medical devices based on the departmental device interaction group model; construct a medical device knowledge base based on the medical device set and the medical device usage map.

[0009] S3. Update the medical device knowledge base through medical device data, and obtain updated medical record data and updated device data. Analyze the medical device set through updated medical record data and updated device data to obtain disease update values, device dynamic values, device comprehensive dynamic values ​​and update signals.

[0010] S4. By updating the signal and the hospital information platform, the medical device knowledge base is updated again to obtain a dynamic medical device knowledge base.

[0011] Preferably, the process of acquiring electronic medical record data and medical device data from the hospital information platform, analyzing the electronic medical record data to obtain key data on medical devices, and constructing a medical device usage map based on this key data includes:

[0012] Electronic medical record data includes clinical diagnosis and treatment data as well as examination and testing data; medical device data includes basic information, operation logs, and device output data; through medical terminology mapping technology, electronic medical record data and medical device data are analyzed to obtain key data of electronic medical records, key data of medical devices, and the mapping relationship between medical records and devices; the key data of electronic medical records, key data of medical devices, and the mapping relationship between medical records and devices are recorded as key data of medical records and devices.

[0013] Analyze key medical record and medical device data to obtain departmental nodes, medical device nodes, and departmental-medical device interaction relationships; use big data mining methods to obtain departmental and medical device relationships based on electronic medical record and medical device data; and obtain a medical device usage map based on departmental relationships, departmental nodes, medical device relationships, medical device nodes, and departmental-medical device interaction relationships.

[0014] Preferably, the process of analyzing key medical device data, constructing a departmental device interaction group model, and obtaining the medical device set based on the departmental device interaction group model includes:

[0015] By using knowledge extraction methods, key data of medical records and medical devices are analyzed to extract disease examination events and medical device examination events. Disease examination events include disease overview, examination items, and disease examination relationships; medical device examination events include examination instruments and examination relationships between instruments.

[0016] The study analyzes disease examination events and medical device examination events. Using medical relationship extraction technology, it constructs examination usage relationships between corresponding medical device nodes based on the examination relationships between devices, and constructs disease examination relationships between medical device nodes and department nodes based on the disease examination relationships. It obtains the medical examination order of medical device nodes and the total number of medical device nodes with the same examination usage relationship, and constructs a departmental device interaction model. Based on the departmental device interaction model of medical device nodes, it obtains a departmental device interaction group model, and based on the medical device interaction model, it obtains the medical device set of medical device nodes.

[0017] Preferably, the process of constructing a medical device knowledge base based on a medical device collection and a medical device usage map is as follows:

[0018] Based on the medical device set, examination and usage relationships, and pathological examination relationships, a diagnosis and treatment link is constructed between department nodes and medical device nodes. Based on the diagnosis and treatment link, department nodes, and medical device nodes, a medical device knowledge base is obtained.

[0019] Preferably, the process of updating the medical device knowledge base using medical device data, obtaining updated medical record data and updated device data, and analyzing the medical device set using the updated medical record data and updated device data to obtain disease update values, device dynamic values, comprehensive device dynamic values, and update signals includes:

[0020] The medical device knowledge base is updated using medical device data. The update process involves real-time monitoring of electronic medical record data and medical device data on the hospital information platform, obtaining updated medical record data and updated device data, and inserting update tags into the updated department nodes and medical device nodes. The medical device set is then analyzed using the updated medical record data and updated device data to obtain the department device interaction update model, code "a", and code "b".

[0021] If both the department node and the medical device node have update tags, obtain the disease update value; set the disease update threshold; when the disease update value is greater than or equal to the disease update threshold, generate update signal one;

[0022] If neither the department node nor the medical device node has an update tag, obtain device change value one, device change value two, or device change value three based on the number of "a" codes and the number of "b" codes in the department device interaction update model; then analyze device change value one, device change value two, or device change value three.

[0023] Preferably, the process of analyzing instrument variation value one, instrument variation value two, or instrument variation value three includes:

[0024] Set the device dynamic threshold, device weight 1, device weight 2, and device weight 3; obtain device dynamic value 1, device dynamic value 2, and device dynamic value 3 based on device weight 1 and device change value 1, device weight 2 and device change value 2, and device weight 3 and device change value 3; if the maximum value among device dynamic value 1, device dynamic value 2, and device dynamic value 3 is greater than or equal to the device change threshold, generate update signal 2.

[0025] If the maximum value among the device dynamic value one, device dynamic value two, and device dynamic value three is less than the device change threshold, the device comprehensive dynamic value is obtained based on device change value one, device change value two, device change value, device weight one, device weight two, and device weight three; if the device comprehensive dynamic value is greater than or equal to the device dynamic threshold, update signal three is generated; if the device comprehensive dynamic value is less than the device dynamic threshold, update signal four is generated.

[0026] Preferably, the process of updating the medical device knowledge base again through updating signals and the hospital information platform to obtain a dynamic medical device knowledge base includes:

[0027] When update signal one is received, the corresponding medical device nodes and department nodes are updated; when update signal two is received, the corresponding medical device nodes are updated; when update signal three is received, it is marked as a valid pending device for use; when update signal four is received, it is marked as a device misuse record; through the hospital information platform, a database update channel is established between the medical device knowledge base and the hospital information platform, and a dynamic medical device knowledge base is constructed based on the database update channel.

[0028] This invention also discloses an intelligent medical device knowledge base construction system based on big data resources, including a management center, which is communicatively connected to a data acquisition module, a database construction module, a database analysis module, and a database update module.

[0029] The data acquisition module is used to acquire electronic medical record data and medical device data from the hospital information platform, analyze the electronic medical record data to obtain key data on medical record devices, and construct a medical device usage map based on the key data on medical record devices.

[0030] The library construction module is used to analyze key medical device data in medical records, build a departmental device interaction group model, and obtain a set of medical devices based on the departmental device interaction group model; and build a medical device knowledge base based on the medical device set and the medical device usage map.

[0031] The library analysis module is used to update the medical device knowledge base through medical device data, and to obtain updated medical record data and updated device data. By analyzing the updated medical record data and updated device data, the medical device set is obtained to obtain disease update values, device dynamic values, device comprehensive dynamic values ​​and update signals.

[0032] The knowledge base update module is used to update the medical device knowledge base again through update signals and the hospital information platform to obtain a dynamic medical device knowledge base.

[0033] Compared with existing technologies, the above-mentioned technical solutions of the present invention have the following beneficial technical effects: constructing a medical device usage map to enable queryable knowledge between medical devices and departments, thereby improving the completeness of the medical device knowledge system; constructing a medical device knowledge base through a departmental device interaction group model and a medical device set, enabling traceability and reasoning within the medical device knowledge base, and enhancing the correlation and interactivity between medical devices and departments; analyzing the medical device set by updating medical record data and updating device data to obtain disease update values, device dynamic values, device comprehensive dynamic values, and update signals; improving the timeliness and accuracy of the intelligent medical device knowledge base; and supporting dynamic knowledge updates and intelligent expansion through a dynamic medical device knowledge base, which helps to improve clinical trust and medical efficiency. Attached Figure Description

[0034] Figure 1 This is a flowchart of one embodiment of the present invention. Detailed Implementation

[0035] Example 1, as Figure 1 As shown, the present invention proposes a method for constructing an intelligent medical device knowledge base based on big data resources, which includes the following steps:

[0036] S1. Obtain electronic medical record data and medical device data from the hospital information platform; analyze the electronic medical record data to obtain key data on medical devices; and construct a medical device usage map based on the key data on medical devices.

[0037] S2. Analyze key medical device data in medical records, construct a departmental device interaction group model, and obtain a set of medical devices based on the departmental device interaction group model; construct a medical device knowledge base based on the medical device set and the medical device usage map.

[0038] S3. Update the medical device knowledge base through medical device data, and obtain updated medical record data and updated device data. Analyze the medical device set through updated medical record data and updated device data to obtain disease update values, device dynamic values, device comprehensive dynamic values ​​and update signals.

[0039] S4. By updating the signal and the hospital information platform, the medical device knowledge base is updated again to obtain a dynamic medical device knowledge base.

[0040] It should be further explained that, in the specific implementation process, the process of acquiring electronic medical record data and medical device data from the hospital information platform, analyzing the electronic medical record data to obtain key data on medical records and medical devices, and constructing a medical device usage map based on this key data is as follows:

[0041] The hospital information platform refers to a unified information system platform for various tasks such as clinical work, management, and scientific research, used to record and manage various types of data within the hospital;

[0042] The electronic medical record data includes clinical diagnosis and treatment data as well as examination and testing data; the clinical diagnosis and treatment data includes the department of diagnosis, diagnosis results, and surgical record data; the surgical record data includes the name of the surgery and data on the surgical instruments; the examination and testing data includes medical examination data and test results.

[0043] The medical device data includes basic information, operation logs, and device output data;

[0044] By using medical terminology mapping technology, electronic medical record data and medical device data are analyzed to obtain key data of electronic medical records, key data of medical devices, and the mapping relationship between medical records and devices. These key data of electronic medical records, key data of medical devices, and the mapping relationship between medical records and devices are denoted as key data of medical records and devices. The key data of electronic medical records refers to the terminology of clinical diagnosis and treatment data, nursing data, and examination and testing data. The key data of medical devices refers to the terminology of basic information, operation logs, and device output data.

[0045] Analyze key medical device data to obtain department nodes, medical device nodes, and department-device interaction relationships;

[0046] It needs further explanation that, in the specific implementation process, the analysis of key data on medical records and medical devices is as follows: Using key data from electronic medical records, the clinical diagnosis and treatment terminology, diagnostic terminology, and surgical names are obtained and recorded as the department name, diagnosed disease, and surgical name. All diagnosed diseases and surgical names corresponding to the department are then counted, department nodes are constructed, the department name is marked on the department node, and all diagnosed diseases and surgical names corresponding to the department are stored in the corresponding department node. Using key data from medical devices, basic information terminology and operational log terminology are obtained and recorded as the medical device name and device purpose. All device purposes corresponding to the medical device are then counted, medical device nodes are constructed, the medical device name is marked on the medical device node, and all device purposes corresponding to the medical device are stored in the corresponding medical device node. Through the medical record-device mapping relationship, the diagnosed diseases within the department nodes and the device purposes within the medical device nodes are analyzed to construct the department-device interaction relationship between department nodes and medical device nodes.

[0047] By using big data mining methods, we analyze the electronic medical record data and medical device data of the hospital information platform to obtain the relationships between treatment departments and between medical devices, which are denoted as departmental relationships and device relationships. Through departmental relationships, we link departmental nodes together, and through device relationships, we link medical device nodes together. Through departmental-device interaction relationships, we link departmental nodes and medical device nodes together to obtain a medical device usage map.

[0048] It should be further explained that, in the specific implementation process, the key data of medical records and instruments are analyzed to construct a departmental instrument interaction group model, and a set of medical devices is obtained based on the departmental instrument interaction group model; the process of constructing a medical device knowledge base based on the medical device set and the medical device usage map is as follows:

[0049] Using knowledge extraction methods, key medical record and instrument data are analyzed to extract disease examination events and instrument examination events. The disease examination events include disease summaries, examination items, and disease-examination relationships. The disease summary refers to the disease name or surgical procedure name. The instrument examination events include examination instruments and the examination relationships between instruments. A disease examination event refers to an event involving examination items from medical examination data related to the surgical procedure name and the disease diagnosis result in the surgical record data. Instrument examination relationships refer to events between surgical instruments within the surgical instrument data and between medical instruments involved in the medical examination data.

[0050] This paper analyzes disease examination events and medical device examination events. Using medical relationship extraction technology, it maps the examination items of disease examination events to the examination devices of medical device examination events, storing the examination items in the corresponding medical device nodes. Based on the inter-device examination relationships, it constructs the examination usage relationships between corresponding medical device nodes, and based on the disease examination relationships, it constructs the disease examination relationships between medical device nodes and department nodes. Department nodes are numbered as i, where i = 1, 2, ..., m, m > 0 and m is an integer; medical device nodes are numbered as j, where j = 1, 2, ..., n, n > 0 and n is an integer. The paper obtains the medical examination order of medical device nodes and the total number of medical device nodes with the same examination usage relationship, and constructs a departmental device interaction model (department node number, medical device examination order, total number of medical device nodes). The departmental device interaction models of medical device nodes are summarized, and those with the same department node number are grouped together to obtain the departmental device interaction group model A. ji Furthermore, the medical device interaction models obtained from the same medical device node are statistically analyzed and organized to obtain the medical device set {A} of the medical device node. j1 A j2 ,……,A ji};

[0051] It should be further clarified that, in the specific implementation process, the specific medical device node refers to the set of medical devices {A}. j1 A j2 ,……,A ji} refers to the participation of medical device nodes in examinations across different departments, and the medical device set {A} j1 A j2 ,……,A ji The departmental nodes involved may be some departmental nodes, not necessarily all departmental nodes;

[0052] Based on the medical device set, examination and usage relationships, and pathological examination relationships, a diagnosis and treatment link is constructed between department nodes and medical device nodes. The diagnosis and treatment link connects the department nodes and medical device nodes, and the medical device set is stored in the corresponding medical device node within the medical device usage graph to obtain a medical device knowledge base.

[0053] It should be further explained that, in the specific implementation process, the medical device knowledge base is updated using medical device data, and updated medical record data and updated device data are obtained. The medical device set is then analyzed using the updated medical record data and updated device data to obtain disease update values, device dynamic values, comprehensive device dynamic values, and update signals. The process is as follows:

[0054] The medical device knowledge base is updated using medical device data. The update process refers to real-time monitoring of electronic medical record data and medical device data on the hospital information platform to obtain updated medical record data and updated device data. If updated medical record data and updated device data are detected, the department nodes of the medical device knowledge base are updated using the updated medical record data, and the medical device nodes of the medical device knowledge base are updated using the updated device data. Update tags are then inserted into the updated department nodes and medical device nodes.

[0055] It should be further explained that, in the specific implementation process, during the update of the medical device knowledge base, the monitored updated medical record data refers to the relevant data of the updated clinical diagnosis and treatment data of the electronic medical record data, and the monitored updated device data specifically refers to the relevant data of the updated medical device model, and the data in the medical device node corresponding to the original medical device is synchronously updated to the updated medical device.

[0056] By analyzing the updated medical record data and updated device data, a departmental device interaction update model is obtained (departmental node number, medical device examination interaction order, and total number of medical device node interactions). If the medical device examination interaction order in the departmental device interaction update model is the update order, then the update order code "a" is inserted after the medical device examination interaction order. If the total number of medical device node interactions is the total number of updates, then the total number of updates code "b" is inserted after the total number of medical device node interactions.

[0057] It should be further explained that, in the specific implementation process, the specific process of analyzing the medical device set by updating medical record data and updating device data is the same as the specific process of building the departmental device interaction model.

[0058] If both the department node corresponding to the department node number and the medical device node corresponding to the department device interaction update model have update tags, then the total number of updates in the same department device interaction update model is counted and recorded as the disease update value; a disease update threshold is set; when the disease update value is greater than or equal to the disease update threshold, update signal one is generated; when the disease update value is less than the disease update threshold, no update signal is generated.

[0059] If the department node corresponding to the department node number and the medical device node corresponding to the department device interaction update model do not both have update tags, the number of department device interaction update models that only have the same code quantity "a", only have the same code quantity "b", or have the same code quantity "a" and "b" will be counted and recorded as device change value one, device change value two, or device change value three, respectively.

[0060] Set the device dynamic threshold, device weight one, device weight two, and device weight three; calculate the device dynamic value one by multiplying device weight one with device change value one, device weight two by device change value two, and device weight three by device change value three, respectively.

[0061] If the maximum value among the device dynamic value one, device dynamic value two, and device dynamic value three is greater than or equal to the device change threshold, update signal two is generated.

[0062] If the maximum value among the device dynamic value 1, device dynamic value 2, and device dynamic value 3 is less than the device change threshold, the comprehensive device dynamic value B is obtained based on device change value 1, device change value 2, device change value, device weight 1, device weight 2, and device weight 3. j ;

[0063] B j =α1*jx1+α2*jx2+α3*jx3;

[0064] If the overall dynamic value of the device is greater than or equal to the dynamic threshold of the device, update signal three is generated; if the overall dynamic value of the device is less than the dynamic threshold of the device, update signal four is generated.

[0065] It should be further explained that, in the specific implementation process, the instrument weight one, instrument weight two, and instrument weight three are related to the average level of patient treatment effect in the departmental instrument interaction update model (departmental node number, medical device examination interaction order, and total number of medical device node interactions) under different coding conditions.

[0066] It should be further explained that, in the specific implementation process, the medical device knowledge base is updated again through updating signals and the hospital information platform to obtain a dynamic medical device knowledge base. The process is as follows:

[0067] When update signal one is received, the corresponding medical device nodes and department nodes are updated; when update signal two is received, the corresponding medical device nodes are updated; when update signal three is received, the corresponding medical device nodes are updated and marked as valid pending device use; when update signal four is received, the corresponding medical device nodes are recorded and marked as device misoperation record.

[0068] It should be further explained that, in the specific implementation process, updating between medical device nodes specifically refers to updating the departmental device interaction update model corresponding to the update signal in the medical device knowledge base for the examination and use relationship between the corresponding medical device nodes. Updating departmental nodes specifically refers to updating the pathological examination relationship between departmental nodes and medical device nodes. Recording the corresponding medical device nodes specifically refers to only recording the examination and use relationship, without updating it between medical device nodes.

[0069] By establishing a database update channel between the medical device knowledge base and the hospital information platform through the above steps and the database update channel, the medical device knowledge base is updated to build a dynamic medical device knowledge base.

[0070] Example 2: The intelligent medical device knowledge base construction system based on big data resources proposed in this invention is applied to the intelligent medical device knowledge base construction method based on big data resources described in Example 1. Specifically, it includes a management center, which is communicatively connected to a data acquisition module, a database construction module, a database analysis module, and a database update module.

[0071] The data acquisition module is used to acquire electronic medical record data and medical device data from the hospital information platform, analyze the electronic medical record data to obtain key data on medical record devices, and construct a medical device usage map based on the key data on medical record devices.

[0072] The library construction module is used to analyze key medical device data in medical records, build a departmental device interaction group model, and obtain a set of medical devices based on the departmental device interaction group model; and build a medical device knowledge base based on the medical device set and the medical device usage map.

[0073] The library analysis module is used to update the medical device knowledge base through medical device data, and to obtain updated medical record data and updated device data. By analyzing the updated medical record data and updated device data, the medical device set is obtained to obtain disease update values, device dynamic values, device comprehensive dynamic values ​​and update signals.

[0074] The knowledge base update module is used to update the medical device knowledge base again through update signals and the hospital information platform to obtain a dynamic medical device knowledge base.

[0075] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A method for constructing an intelligent medical device knowledge base based on big data resources, characterized in that, Includes the following steps: S1. Obtain electronic medical record data and medical device data from the hospital information platform; analyze the electronic medical record data to obtain key data on medical devices; and construct a medical device usage map based on the key data on medical devices. S2. Analyze key medical device data in medical records, construct a departmental device interaction group model, and obtain a set of medical devices based on the departmental device interaction group model; construct a medical device knowledge base based on the medical device set and the medical device usage map. S3. Update the medical device knowledge base through medical device data, and obtain updated medical record data and updated device data. Analyze the medical device set through updated medical record data and updated device data to obtain disease update value, device dynamic value, device comprehensive dynamic value and update signal. S4. By updating the signal and the hospital information platform, the medical device knowledge base is updated again to obtain a dynamic medical device knowledge base. The medical device knowledge base is updated using medical device data. The update process involves real-time monitoring of electronic medical record data and medical device data on the hospital information platform, obtaining updated medical record data and updated device data, and inserting update tags into the updated department nodes and medical device nodes. The medical device set is then analyzed using the updated medical record data and updated device data to obtain the department device interaction update model, code "a", and code "b". If both the department node and the medical device node have update tags, then the total number of updates in the same department device interaction update model is counted and recorded as the disease update value. Set a disease update threshold; when the disease update value is greater than or equal to the disease update threshold, generate update signal one; when the disease update value is less than the disease update threshold, do not generate update signal. If there are not update tags in both the department node and the medical device node, obtain device change value one, device change value two, or device change value three based on the number of "a" codes and the number of "b" codes in the department device interaction update model. The following analysis is performed on instrument variation value one, instrument variation value two, or instrument variation value three: Set the device dynamic threshold, device weight one, device weight two, and device weight three; calculate the device weight one by multiplying it with device change value one, device weight two by device change value two, and device weight three by device change value three to obtain device dynamic value one, device dynamic value two, and device dynamic value three respectively; if the maximum value among device dynamic value one, device dynamic value two, and device dynamic value three is greater than or equal to the device change threshold, generate update signal two. If the maximum value among the device dynamic value one, device dynamic value two, and device dynamic value three is less than the device change threshold, the device comprehensive dynamic value is obtained based on device change value one, device change value two, device change value, device weight one, device weight two, and device weight three; if the device comprehensive dynamic value is greater than or equal to the device dynamic threshold, update signal three is generated; if the device comprehensive dynamic value is less than the device dynamic threshold, update signal four is generated.

2. The method for constructing an intelligent medical device knowledge base based on big data resources according to claim 1, characterized in that, The process of acquiring electronic medical record data and medical device data from the hospital information platform, analyzing the electronic medical record data to obtain key data on medical devices, and constructing a medical device usage map based on this key data includes: Electronic medical record data includes clinical diagnosis and treatment data as well as examination and testing data; medical device data includes basic information, operation logs, and device output data; through medical terminology mapping technology, electronic medical record data and medical device data are analyzed to obtain key data of electronic medical records, key data of medical devices, and the mapping relationship between medical records and devices; the key data of electronic medical records, key data of medical devices, and the mapping relationship between medical records and devices are recorded as key data of medical records and devices. Analyze key medical record and medical device data to obtain departmental nodes, medical device nodes, and departmental-medical device interaction relationships; use big data mining methods to obtain departmental and medical device relationships based on electronic medical record and medical device data; and obtain a medical device usage map based on departmental relationships, departmental nodes, medical device relationships, medical device nodes, and departmental-medical device interaction relationships.

3. The method for constructing an intelligent medical device knowledge base based on big data resources according to claim 2, characterized in that, The process of analyzing key medical device data in medical records, constructing a departmental device interaction group model, and obtaining the medical device set based on the departmental device interaction group model includes: By using knowledge extraction methods, key data of medical records and medical devices are analyzed to extract disease examination events and medical device examination events. Disease examination events include disease overview, examination items, and disease examination relationships; medical device examination events include examination instruments and examination relationships between instruments. The study analyzes disease examination events and medical device examination events. Using medical relationship extraction technology, it constructs examination usage relationships between corresponding medical device nodes based on the examination relationships between devices, and constructs disease examination relationships between medical device nodes and department nodes based on the disease examination relationships. It obtains the medical examination order of medical device nodes and the total number of medical device nodes with the same examination usage relationship, and constructs a departmental device interaction model. Based on the departmental device interaction model of medical device nodes, it obtains a departmental device interaction group model, and based on the medical device interaction model, it obtains the medical device set of medical device nodes.

4. The method for constructing an intelligent medical device knowledge base based on big data resources according to claim 3, characterized in that, The process of constructing a medical device knowledge base based on a collection of medical devices and a medical device usage map is as follows: Based on the medical device set, examination and usage relationships, and pathological examination relationships, a diagnosis and treatment link is constructed between department nodes and medical device nodes. Based on the diagnosis and treatment link, department nodes, and medical device nodes, a medical device knowledge base is obtained.

5. The method for constructing an intelligent medical device knowledge base based on big data resources according to claim 4, characterized in that, The process of updating the medical device knowledge base again by updating signals and the hospital information platform to obtain a dynamic medical device knowledge base includes: When update signal one is received, the corresponding medical device nodes and department nodes are updated; when update signal two is received, the corresponding medical device nodes are updated; when update signal three is received, it is marked as a valid pending device for use; when update signal four is received, it is marked as a device misuse record; through the hospital information platform, a database update channel is established between the medical device knowledge base and the hospital information platform, and a dynamic medical device knowledge base is constructed based on the database update channel.

6. A system for constructing an intelligent medical device knowledge base based on big data resources, specifically applied to the method for constructing an intelligent medical device knowledge base based on big data resources as described in any one of claims 1 to 5, comprising a management center, characterized in that, The management center communication connection includes a data acquisition module, a database construction module, a database analysis module, and a database update module. The data acquisition module is used to acquire electronic medical record data and medical device data from the hospital information platform, analyze the electronic medical record data to obtain key data on medical record devices, and construct a medical device usage map based on the key data on medical record devices. The library construction module is used to analyze key medical device data in medical records, build a departmental device interaction group model, and obtain a set of medical devices based on the departmental device interaction group model; and build a medical device knowledge base based on the medical device set and the medical device usage map. The library analysis module is used to update the medical device knowledge base through medical device data, and to obtain updated medical record data and updated device data. By analyzing the updated medical record data and updated device data, the medical device set is obtained to obtain disease update values, device dynamic values, device comprehensive dynamic values ​​and update signals. The library update module is used to update the medical device knowledge base again through update signals and the hospital information platform to obtain a dynamic medical device knowledge base.

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