A method and system for managing medical diagnosis data

Abstract

The present invention provides a method and system for managing medical diagnostic data, the method comprising: step 1: collecting medical diagnostic data; step 2: building a medical diagnostic data recognition model; step 3: identifying the medical diagnostic data based on the medical diagnostic data recognition model, and adding medical field labels to key data based on the recognition results; step 4: improving the medical field labels in the medical field vocabulary. The comprehensiveness, accuracy and effectiveness of medical diagnostic data management are improved, and it is also convenient for patients and doctors to quickly and effectively extract effective information from medical diagnostic data.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for managing medical diagnosis data. Background Art

[0002] At present, medical diagnostic data is the core asset of the medical industry. It contains important information such as patient medical records, examination reports, and imaging data. It plays a vital role in doctors' diagnosis and treatment plan. Effective diagnostic data management can improve the treatment and efficiency of medical services, and can help doctors make diagnostic decisions more accurately and quickly, thereby improving patients' treatment experience.

[0003] However, nowadays, medical diagnostic data comes from different medical fields, with huge data volumes and inconsistent data classification. If not managed in a timely manner, it will lead to waste of medical diagnostic data. At the same time, without the identification of corresponding medical diagnostic data, it is impossible to accurately divide medical diagnostic data into medical fields, thus failing to accurately realize the division and management of medical diagnostic data, and failing to ensure the comprehensiveness, accuracy and effectiveness of medical diagnostic data management.

[0004] Therefore, in order to overcome the above technical problems, the present invention provides a method and system for managing medical diagnosis data. Summary of the invention

[0005] The present invention provides a method and system for managing medical diagnostic data, which can effectively identify the collected medical diagnostic data by constructing a medical diagnostic data recognition model, and then determine the medical field labels of key data in the medical diagnostic data based on the recognition results. By improving the medical field labels in the medical field vocabulary, the integrity and accuracy of the medical field vocabulary can be effectively guaranteed, the comprehensiveness, accuracy and effectiveness of medical diagnostic data management are further improved, and it is also convenient for patients and doctors to quickly and effectively extract effective information in the medical diagnostic data.

[0006] A method for managing medical diagnostic data, comprising:

[0007] Collect medical diagnostic data;

[0008] Build a medical diagnostic data recognition model;

[0009] Identify medical diagnostic data based on the medical diagnostic data recognition model, and add medical field labels to key data based on the recognition results;

[0010] Improve the medical field labels in the medical field vocabulary.

[0011] Preferably, a method for managing medical diagnostic data, collecting medical diagnostic data, comprises:

[0012] Establishing a physical connection between the data acquisition device and the medical diagnosis database;

[0013] sending a communication handshake protocol to the medical diagnosis database based on the actual connection between the data acquisition device and the medical diagnosis database, and establishing a communication connection between the data acquisition device and the medical diagnosis database based on the feedback information received by the data acquisition device;

[0014] The instructions of the data acquisition device are transmitted to the medical diagnosis database, and the corresponding medical diagnosis data are collected in the medical diagnosis database according to the instructions to complete the acquisition of the medical diagnosis data.

[0015] Preferably, a method for managing medical diagnosis data, establishing a practical connection between a data acquisition device and a medical diagnosis database, comprises:

[0016] Reading a connection interface of the medical diagnosis database in a document manager of the medical diagnosis database, and configuring an interface address of the connection interface of the medical diagnosis database;

[0017] Connect the medical diagnosis database and data collection device to the same domain network;

[0018] The actual connection with the data acquisition device is established in the same domain network based on the interface address of the connection interface of the medical diagnosis database.

[0019] Preferably, a method for managing medical diagnosis data, based on the actual connection between the data acquisition device and the medical diagnosis database, sends a communication handshake protocol to the medical diagnosis database, and establishes a communication connection between the data acquisition device and the medical diagnosis database based on the feedback information received by the data acquisition device, including:

[0020] Constructing the communication protocol between the data acquisition device and the medical diagnosis database;

[0021] Determine the communication handshake protocol code based on the data acquisition device according to the protocol requirements;

[0022] Based on the actual connection between the data acquisition device and the medical diagnosis database and according to the communication protocol, the communication handshake protocol code is sent to the medical diagnosis database;

[0023] Verify the communication handshake protocol code based on the medical diagnosis database and output feedback information;

[0024] The feedback information of the medical diagnosis database is monitored based on the data acquisition device, and the acquisition device is communicatively connected with the medical diagnosis database according to the monitoring result.

[0025] Preferably, a method for managing medical diagnostic data, transmitting instructions of a data acquisition device to a medical diagnostic database, and collecting corresponding medical diagnostic data in the medical diagnostic database according to the instructions, to complete the acquisition of medical diagnostic data, includes:

[0026] Obtain user diagnostic information, and parse the user diagnostic information to determine diagnostic terms in the user diagnostic information;

[0027] generating instructions in a data acquisition device according to the diagnosis nouns in the user diagnosis information;

[0028] Transmitting the instruction of the data acquisition device to a medical diagnosis database for matching, and determining medical diagnosis data consistent with the instruction of the data acquisition device;

[0029] Parsing the medical diagnosis data, determining the subordinate relationship of the medical diagnosis data, and dividing the medical diagnosis data according to the subordinate relationship of the medical diagnosis data to obtain a master node and a slave node;

[0030] Packing the master node and the slave node based on the subordinate relationship to obtain a medical diagnosis data packet;

[0031] The medical diagnosis data packet is transmitted from the medical diagnosis database to the data acquisition device via the communication connection.

[0032] Preferably, a method for managing medical diagnostic data, identifying the medical diagnostic data based on a medical diagnostic data identification model, and adding medical field labels to key data based on the identification results, includes:

[0033] Inputting the medical diagnosis data into the medical diagnosis data recognition model for recognition, determining key data of the medical diagnosis data, and outputting medical field labels of the key data according to the medical diagnosis data recognition model;

[0034] Add medical domain labels to key data in medical diagnostic data.

[0035] Preferably, a method for managing medical diagnostic data, wherein the medical field labels are improved in the medical field vocabulary, comprises:

[0036] Determine the medical project library to which the current key data belongs based on medical field labels, and extract known medical terms in the medical project library;

[0037] Construct a text semantic extraction dictionary based on text processing requirements, and generate text type constraints and text content constraints based on the text semantic extraction dictionary;

[0038] Based on the text type constraint condition and the text content constraint condition, semantic recognition is performed on each known medical word in turn to obtain the semantic feature quantity of each known medical word;

[0039] Determine the representation degree of known medical vocabulary and current key data based on semantic feature quantities, and when the representation degree is less than a set threshold, determine that the medical project library needs to be improved;

[0040] Based on the determination results, the current key data and the corresponding medical field labels are encapsulated, and the medical vocabulary to be improved is obtained based on the encapsulation results;

[0041] Extracting the data record log of the medical project library, and determining the medical vocabulary level in the medical project library and the level rules corresponding to each medical vocabulary level based on the data record log;

[0042] Based on the preset scheduling engine, the medical vocabulary to be improved is distributedly added to the corresponding medical vocabulary level according to the hierarchical rules of each medical vocabulary level, and the improvement of the medical field vocabulary is completed based on the addition results.

[0043] Preferably, a method for managing medical diagnostic data, based on the encapsulation result, obtains the medical vocabulary to be improved, comprising:

[0044] Acquire the medical vocabulary to be improved, and perform structural decomposition on the medical vocabulary to be improved to obtain a set of byte elements contained in the medical vocabulary to be improved;

[0045] Based on the medical field terminology dictionary, the standardized term text of each byte element in the byte element set is determined respectively, and the standardized term text is byte-associated based on the source position of each byte element to obtain the standardized medical vocabulary corresponding to the medical vocabulary to be improved;

[0046] The validity of standardized medical vocabulary is verified based on the verification index system, and the standardized medical vocabulary is added to the medical field vocabulary after the validity verification is passed.

[0047] A management system for medical diagnosis data, comprising:

[0048] A collection module for collecting medical diagnosis data;

[0049] Model building module, used to build medical diagnosis data recognition model;

[0050] An identification module, used to identify medical diagnosis data based on a medical diagnosis data identification model, and to add medical field labels to key data based on the identification results;

[0051] The improvement module is used to improve the medical field labels in the medical field vocabulary.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] 1. By constructing a medical diagnostic data recognition model, the collected medical diagnostic data can be effectively identified, and then the medical field labels of key data in the medical diagnostic data can be determined based on the recognition results. By improving the medical field labels in the medical field vocabulary, the integrity and accuracy of the medical field vocabulary can be effectively guaranteed, further improving the comprehensiveness, accuracy and effectiveness of medical diagnostic data management, and also facilitating patients and doctors to quickly and effectively extract effective information from medical diagnostic data.

[0054] 2. By constructing different first medical field labels, second medical field labels, and third medical field labels, different network models can be constructed, which is conducive to ensuring the effectiveness and orderliness of the medical diagnosis data recognition model. By determining the data connection between the first medical field label, the second medical field label, and the third medical field label, the construction of the mixed initial diagnosis model can be effectively realized. By learning the mixed initial diagnosis model, the accuracy and effectiveness of the construction of the medical diagnosis data recognition model can be effectively guaranteed, further improving the comprehensiveness, accuracy and effectiveness of medical diagnosis data management, and also facilitating patients and doctors to quickly and effectively extract effective information from medical diagnosis data.

[0055] 3. By determining the medical project library to which the key data belongs according to the medical field label, and determining the known medical vocabulary in the medical project library, secondly, he determines the text type constraints and text content constraints according to the text requirements, and realizes the locking of the semantic feature quantities of the known medical vocabulary in the medical project library, so as to facilitate the determination of the representation attribution of the known medical vocabulary and the current key data, and when the representation attribution is less than the set threshold, it is determined that the medical project library needs to be improved. Finally, according to the judgment result, the current key data and the corresponding medical field label are encapsulated to determine the medical vocabulary to be improved. At the same time, according to the data record log of the medical project library, the medical vocabulary level in the medical project library and the hierarchical rules corresponding to each medical vocabulary level are analyzed, and finally the medical vocabulary to be improved is distributed and added to the corresponding medical vocabulary level, so as to realize the accurate and reliable improvement of the medical field vocabulary library, which is convenient for patients and doctors to quickly and effectively extract effective information from medical diagnosis data.

[0056] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0057] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0059] Figure 1 is a flow chart of a method for managing medical diagnosis data in an embodiment of the present invention;

[0060] Figure 2 This is a flowchart of step 1 in a method for managing medical diagnostic data in an embodiment of the present invention;

[0061] Figure 3 This is a structural diagram of a management system for medical diagnosis data in an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0063] Embodiment 1:

[0064] This embodiment provides a method for managing medical diagnosis data, such as Figure 1 As shown, including:

[0065] Step 1: Collect medical diagnostic data;

[0066] Step 2: Build a medical diagnosis data recognition model;

[0067] Step 3: Identify the medical diagnosis data based on the medical diagnosis data recognition model, and add medical field labels to the key data based on the recognition results;

[0068] Step 4: Complete the medical field labels in the medical field vocabulary.

[0069] In this embodiment, the medical diagnosis data may be data obtained after the data acquisition device collects data in the medical diagnosis database. The medical diagnosis data may be stored in the medical diagnosis database after the user's current diagnosis, and the medical diagnosis data may be obtained by retrieving it.

[0070] In this embodiment, the medical diagnosis data identification model may be used to identify the domain label of the medical diagnosis data. The domain to which the medical diagnosis data belongs may be effectively distinguished through the medical diagnosis data model.

[0071] In this embodiment, the medical field label may be a representation mark used to distinguish different medical types (such as hypertension, heart disease, diabetes, etc.).

[0072] In this embodiment, the medical field labels are improved in the medical field vocabulary to ensure the integrity and accuracy of the medical field vocabulary.

[0073] In this embodiment, the key data may be data representing the medical field in the medical diagnosis data.

[0074] The working principle and beneficial effects of the above technical solution are: by constructing a medical diagnosis data recognition model, the collected medical diagnosis data can be effectively identified, and then the medical field labels of key data in the medical diagnosis data can be determined based on the recognition results. By improving the medical field labels in the medical field vocabulary, the integrity and accuracy of the medical field vocabulary can be effectively guaranteed, further improving the comprehensiveness, accuracy and effectiveness of medical diagnosis data management, and also facilitating patients and doctors to quickly and effectively extract effective information from medical diagnosis data.

[0075] Embodiment 2:

[0076] Based on Example 1, this example provides a method for managing medical diagnosis data, such as Figure 2 As shown, collect medical diagnostic data, including:

[0077] S101: Establishing a practical connection between the data acquisition device and the medical diagnosis database;

[0078] S102: sending a communication handshake protocol to the medical diagnosis database according to the actual connection between the data acquisition device and the medical diagnosis database, and establishing a communication connection between the data acquisition device and the medical diagnosis database according to the feedback information received by the data acquisition device;

[0079] S103: Transmitting the instruction of the data acquisition device to the medical diagnosis database, and collecting corresponding medical diagnosis data in the medical diagnosis database according to the instruction, thereby completing the acquisition of the medical diagnosis data.

[0080] In this embodiment, the communication handshake protocol may be used to implement data communication and data transmission between the data acquisition device and the medical diagnosis database.

[0081] In this embodiment, the feedback information may include data parameters and connection model of the connection between the data acquisition device and the medical diagnosis database.

[0082] The working principle and beneficial effects of the above technical solution are: by establishing an actual connection between the data acquisition device and the medical diagnosis database, effective communication between the data acquisition device and the medical diagnosis database can be effectively guaranteed. By sending a communication handshake protocol to the medical diagnosis database, it is possible to effectively build a communication connection between the data acquisition device and the medical diagnosis database based on feedback information, thereby ensuring the security and effectiveness of medical diagnosis data collection.

[0083] Embodiment 3:

[0084] Based on Example 2, this example provides a method for managing medical diagnosis data, which establishes an actual connection between a data acquisition device and a medical diagnosis database, including:

[0085] Reading a connection interface of the medical diagnosis database in a document manager of the medical diagnosis database, and configuring an interface address of the connection interface of the medical diagnosis database;

[0086] Connect the medical diagnosis database and data collection device to the same domain network;

[0087] The actual connection with the data acquisition device is established in the same domain network based on the interface address of the connection interface of the medical diagnosis database.

[0088] The working principle and beneficial effects of the above technical solution are: by reading the connection interface of the medical diagnosis database in the document manager of the medical diagnosis database, and configuring the interface address of the medical diagnosis database connection interface according to the connection interface, and by connecting the medical diagnosis database and the data acquisition device to the same domain network, the effectiveness of the actual connection can be guaranteed.

[0089] Embodiment 4:

[0090] Based on Example 2, this example provides a method for managing medical diagnosis data, which sends a communication handshake protocol to the medical diagnosis database based on the actual connection between the data acquisition device and the medical diagnosis database, and establishes a communication connection between the data acquisition device and the medical diagnosis database based on the feedback information received by the data acquisition device, including:

[0091] Constructing the communication protocol between the data acquisition device and the medical diagnosis database;

[0092] Determine the communication handshake protocol code based on the data acquisition device according to the protocol requirements;

[0093] Based on the actual connection between the data acquisition device and the medical diagnosis database and according to the communication protocol, the communication handshake protocol code is sent to the medical diagnosis database;

[0094] Verify the communication handshake protocol code based on the medical diagnosis database and output feedback information;

[0095] The feedback information of the medical diagnosis database is monitored based on the data acquisition device, and the acquisition device is communicatively connected with the medical diagnosis database according to the monitoring result.

[0096] In this embodiment, verification of the communication handshake protocol code based on the medical diagnosis database may include security verification and authority verification of the communication handshake protocol code (it may be through matching the authorized code set and security format pre-stored in the medical diagnosis database with the communication handshake protocol code, so that when they match, the verification is passed, otherwise, the verification is not passed).

[0097] In this embodiment, the feedback information may be a feedback message after verification. When the verification is passed, the feedback information may output 1, and when the verification is not passed, the feedback information may output 0.

[0098] In this embodiment, the collection device and the medical diagnosis database are communicatively connected according to the monitoring results. When the monitored feedback information is 1, the communication connection between the collection device and the medical diagnosis database can be established. When the monitored feedback information is 0, the communication handshake protocol code is re-determined until the output feedback information is 1, and then the communication connection between the collection device and the medical diagnosis database is established.

[0099] The working principle and beneficial effect of the above technical solution are: by obtaining the communication handshake protocol code and verifying it, the effectiveness and security of the communication connection between the acquisition device and the medical diagnosis database can be effectively guaranteed.

[0100] Embodiment 5:

[0101] Based on Example 2, this example provides a method for managing medical diagnostic data, which transmits the instruction of the data acquisition device to the medical diagnostic database, and collects the corresponding medical diagnostic data according to the instruction in the medical diagnostic database to complete the acquisition of the medical diagnostic data, including:

[0102] Obtain user diagnostic information, and parse the user diagnostic information to determine diagnostic terms in the user diagnostic information;

[0103] generating instructions in a data acquisition device according to the diagnosis nouns in the user diagnosis information;

[0104] Transmitting the instruction of the data acquisition device to a medical diagnosis database for matching, and determining medical diagnosis data consistent with the instruction of the data acquisition device;

[0105] Parsing the medical diagnosis data, determining the subordinate relationship of the medical diagnosis data, and dividing the medical diagnosis data according to the subordinate relationship of the medical diagnosis data to obtain a master node and a slave node;

[0106] Packing the master node and the slave node based on the subordinate relationship to obtain a medical diagnosis data packet;

[0107] The medical diagnosis data packet is transmitted from the medical diagnosis database to the data acquisition device via the communication connection.

[0108] In this embodiment, the diagnosis noun may be a diagnosis term related to medical information in the user's diagnosis information.

[0109] In this embodiment, the instruction may be determined based on the diagnosis noun, and is used to perform an operation of matching with a medical diagnosis database, and output medical diagnosis data consistent with the instruction, wherein the format of the instruction is consistent with the format of the medical diagnosis data.

[0110] In this embodiment, the subordinate relationship can be the confirmation of the subordinate relationship of the medical diagnosis data according to the logical relationship of the medical diagnosis in the medical diagnosis data. For example, when the medical diagnosis data includes surgical medical diagnosis data and neurosurgery medical diagnosis data, the surgical medical diagnosis data is the main data and constitutes the main node, while the neurosurgery medical diagnosis data is the subordinate data and constitutes the slave node.

[0111] The working principle and beneficial effects of the above technical solution are: by determining the diagnostic noun in the user's diagnostic information, it is possible to effectively generate instructions in the data acquisition device, and then achieve matching in the medical diagnosis database through the instructions, so as to obtain medical diagnosis data. By dividing the medical diagnosis data into subordinate relationships, generating master nodes and slave nodes, and then medical diagnosis data packets, the validity and orderliness of the obtained medical diagnosis data packets can be effectively guaranteed, thereby improving the comprehensiveness of medical diagnosis data management.

[0112] Embodiment 6:

[0113] Based on Example 1, this example provides a method for managing medical diagnostic data, constructing a medical diagnostic data recognition model, and identifying the medical diagnostic data based on the medical diagnostic data recognition model, including:

[0114] Obtain the field type of the medical field, and construct a first medical field label according to the field type of the medical field, obtain the sub-field of each type of medical field, and use the sub-field of each type of medical field as the second medical field label, and at the same time, obtain multiple diagnostic methods corresponding to each sub-field, and use each diagnostic method as the third medical field label;

[0115] Constructing a first network model based on the first medical field label, constructing a second network model based on the second medical field label, and constructing a third network model based on the third medical field label;

[0116] Acquire the data connection between the first medical field label, the second medical field label, and the third medical field label, and combine the first network model, the second network model, and the third network model according to the data connection between the first medical field label, the second medical field label, and the third medical field label to obtain a hybrid initial diagnosis model;

[0117] Retrieving respectively a first medical diagnosis sample data set carrying a first medical field label, a second medical diagnosis sample data set carrying a second medical field label, and a third medical diagnosis sample data set carrying a third medical diagnosis sample data set;

[0118] Performing a first learning on a first network model in a mixed initial diagnosis model using a first medical diagnosis sample data set, performing a second learning on a second network model in a mixed initial diagnosis model using a second medical diagnosis sample data set, and performing a third learning on a third network model in a mixed initial diagnosis model using a third medical diagnosis sample data set;

[0119] obtaining a hybrid diagnostic model based on the first learning result, the second learning result, and the third learning result;

[0120] Retrieve medical diagnosis training data sets that do not carry medical field labels;

[0121] The medical diagnosis training data set is input into the hybrid diagnosis model for verification, and when the output result of the hybrid diagnosis model meets the constraint conditions, the construction of the medical diagnosis data recognition model is completed.

[0122] In this embodiment, the field types of the medical field may include but are not limited to: internal medicine, surgery, obstetrics and gynecology and other field types; the sub-fields of each type of medical field may be, for example: surgery includes but is not limited to: neurosurgery, thoracic surgery and other fields; the multiple diagnostic methods corresponding to each sub-field may be for the same neurosurgery such as surgery, different symptoms correspond to different diagnostic methods, therefore, one sub-field contains multiple diagnostic methods, wherein the diagnostic method is a pre-set data text.

[0123] In this embodiment, the first medical field label can be used as a characterization identifier to distinguish the field types of different medical fields; the second medical field label can be used as a characterization identifier to distinguish different sub-fields; the third medical field label can be used as a characterization identifier to distinguish different diagnostic methods. Thus, the first medical field label, the second medical field label, and the third medical field label are used to construct the first network model, the second network model, and the third network model, thereby achieving effective distinction between the models.

[0124] In this embodiment, the data connection can be achieved by associating the first medical field label, the second medical field label and the third medical field label through a subordinate relationship in medical treatment. The data connection is, for example: surgical data - neurosurgery data - diagnosis method text 1.

[0125] In this embodiment, the medical diagnosis training data set input into the hybrid diagnosis model for verification may be a type of known medical diagnosis training data set. By inputting the medical diagnosis training data set into the hybrid diagnosis model for identification, it is determined whether the output type is consistent with the type of the known medical diagnosis training data set. If they are consistent, the constraints are met. Otherwise, the hybrid diagnosis model continues to be learned until the constraints are met.

[0126] The working principle and beneficial effects of the above technical solution are: by constructing different first medical field labels, second medical field labels, and third medical field labels, different network models are constructed, which is conducive to ensuring the effectiveness and orderliness of the medical diagnosis data recognition model. By determining the data connection between the first medical field label, the second medical field label, and the third medical field label, the construction of a mixed initial diagnosis model is effectively realized. By learning the mixed initial diagnosis model, the accuracy and effectiveness of the construction of the medical diagnosis data recognition model are effectively guaranteed, which further improves the comprehensiveness, accuracy and effectiveness of medical diagnosis data management, and also facilitates patients and doctors to quickly and effectively extract effective information from medical diagnosis data.

[0127] Embodiment 7:

[0128] Based on Example 1, this example provides a method for managing medical diagnostic data, which identifies the medical diagnostic data based on a medical diagnostic data identification model, and adds medical field labels to key data based on the identification results, including:

[0129] Inputting the medical diagnosis data into the medical diagnosis data recognition model for recognition, determining key data of the medical diagnosis data, and outputting medical field labels of the key data according to the medical diagnosis data recognition model;

[0130] Add medical domain labels to key data in medical diagnostic data.

[0131] In this embodiment, the medical field label of the key data may be a marking symbol that can characterize the medical field described by the key data, wherein the medical field may be a medical field such as hypertension and heart disease.

[0132] The working principle and beneficial effects of the above technical solution are: by inputting the medical diagnosis data into the medical diagnosis data recognition model for recognition, the key data of the medical diagnosis data and the medical field labels corresponding to the key data can be accurately and effectively determined. Finally, by adding the medical field labels to the key data in the medical diagnosis data, it is convenient to effectively improve the medical field vocabulary through the added results, and it is also convenient for patients and doctors to quickly and effectively extract effective information from the medical diagnosis data.

[0133] Embodiment 8:

[0134] Based on Example 1, this example provides a method for managing medical diagnosis data, which improves medical field labels in a medical field vocabulary, including:

[0135] Determine the medical project library to which the current key data belongs based on medical field labels, and extract known medical terms in the medical project library;

[0136] Construct a text semantic extraction dictionary based on text processing requirements, and generate text type constraints and text content constraints based on the text semantic extraction dictionary;

[0137] Based on the text type constraint condition and the text content constraint condition, semantic recognition is performed on each known medical word in turn to obtain the semantic feature quantity of each known medical word;

[0138] Determine the representation degree of known medical vocabulary and current key data based on semantic feature quantities, and when the representation degree is less than a set threshold, determine that the medical project library needs to be improved;

[0139] Based on the determination results, the current key data and the corresponding medical field labels are encapsulated, and the medical vocabulary to be improved is obtained based on the encapsulation results;

[0140] Extracting the data record log of the medical project library, and determining the medical vocabulary level in the medical project library and the level rules corresponding to each medical vocabulary level based on the data record log;

[0141] Based on the preset scheduling engine, the medical vocabulary to be improved is distributedly added to the corresponding medical vocabulary level according to the hierarchical rules of each medical vocabulary level, and the improvement of the medical field vocabulary is completed based on the addition results.

[0142] In this embodiment, the medical project library is a data storage space in the medical field vocabulary library, which is used to represent the smallest medical field unit described by different medical diagnosis data.

[0143] In this embodiment, the known medical vocabulary may be the medical vocabulary currently available in the medical project library.

[0144] In this embodiment, the text processing requirements are known in advance and are used to characterize the standards for processing medical diagnostic data.

[0145] In this embodiment, the text semantic extraction dictionary is formulated according to text processing requirements and is a reference for determining the specific meaning of known medical terms.

[0146] In this embodiment, the text type constraint condition may be a standard for defining the type of medical vocabulary.

[0147] In this embodiment, the text content constraint condition may be a standard that represents the limitation of medical vocabulary content.

[0148] In this embodiment, the semantic feature quantity may be a specific textual meaning that represents a known medical word, and is determined from two aspects: the word type and the word content.

[0149] In this embodiment, the characterization attribute degree is used to characterize the consistency between the known medical vocabulary and the current key data, and the greater the value of the characterization attribute degree is, the more consistent the two are.

[0150] In this embodiment, the set threshold is known in advance and is used to represent the minimum standard for improving the medical project library, and can be adjusted.

[0151] In this embodiment, the medical vocabulary to be improved may be an element obtained by bundling the current key data with the corresponding medical field label and can be directly stored in the corresponding medical project library.

[0152] In this embodiment, the medical vocabulary hierarchy may be different types of medical vocabulary included in the medical project library and different attributes corresponding to different medical vocabulary. For example, the professionalism and generality of the vocabulary may be classified to form a hierarchical structure.

[0153] In this embodiment, the hierarchical rules may be the characteristics, related words, applicable scope, etc. of the medical vocabulary in each medical vocabulary level, so as to ensure that the hierarchical division of the vocabulary is clear and consistent.

[0154] In this embodiment, the preset scheduling engine is set in advance.

[0155] The working principle and beneficial effects of the above technical solution are: by determining the medical project library to which the key data belongs according to the medical field label, and determining the known medical vocabulary in the medical project library, secondly, he determines the text type constraint conditions and the text content constraint conditions according to the text requirements, and realizes the locking of the semantic feature quantity of the known medical vocabulary in the medical project library, so as to facilitate the determination of the representation attribution degree of the known medical vocabulary and the current key data, and when the representation attribution degree is less than the set threshold, it is determined that the medical project library needs to be improved, and finally, according to the determination result, the current key data and the corresponding medical field label are encapsulated to realize the determination of the medical vocabulary to be improved, and at the same time, according to the data record log of the medical project library, the medical vocabulary level in the medical project library and the hierarchical rules corresponding to each medical vocabulary level are analyzed, and finally the medical vocabulary to be improved is distributedly added to the corresponding medical vocabulary level, so as to realize the accurate and reliable improvement of the medical field vocabulary library, so as to facilitate patients and doctors to quickly and effectively extract effective information from medical diagnosis data.

[0156] Embodiment 9:

[0157] Based on Example 8, this example provides a method for managing medical diagnosis data, which obtains a medical vocabulary to be improved based on the encapsulation result, including:

[0158] Acquire the medical vocabulary to be improved, and perform structural decomposition on the medical vocabulary to be improved to obtain a set of byte elements contained in the medical vocabulary to be improved;

[0159] Based on the medical field terminology dictionary, the standardized term text of each byte element in the byte element set is determined respectively, and the standardized term text is byte-associated based on the source position of each byte element to obtain the standardized medical vocabulary corresponding to the medical vocabulary to be improved;

[0160] The validity of standardized medical vocabulary is verified based on the verification index system, and the standardized medical vocabulary is added to the medical field vocabulary after the validity verification is passed.

[0161] In this embodiment, the byte element set may be a result obtained after structural decomposition of the medical vocabulary to be improved, and specifically may be a character code contained in the medical vocabulary to be improved, wherein the structural decomposition may be performed according to the constituent features of the medical vocabulary to be improved.

[0162] In this embodiment, the medical field term dictionary is known in advance.

[0163] In this embodiment, the standardized terminology text may be the result of determining the standard terms of the byte element set according to a medical field terminology dictionary.

[0164] In this embodiment, the byte association may be to concatenate the obtained standard terminology texts according to the source positions of the byte elements.

[0165] In this embodiment, the standardized medical vocabulary may be the result obtained by concatenating the standardized terminology texts of the determined byte elements.

[0166] In this embodiment, the verification index system is set in advance and is used to verify the validity of standardized medical vocabulary.

[0167] The working principle and beneficial effects of the above technical solution are: by structurally splitting the medical vocabulary to be improved, the set of byte elements contained in the medical vocabulary to be improved is locked; secondly, the standardized terminology text of each byte element is determined through the medical field terminology dictionary, and the obtained standardized terminology text is associated according to the source position of each byte element, so as to achieve accurate and effective acquisition of the standardized medical vocabulary corresponding to the medical vocabulary to be improved; finally, the validity of the standardized medical vocabulary is verified through the verification indicator system, and the standardized medical vocabulary is added to the medical field vocabulary after the validity verification is passed, thereby ensuring the accuracy and reliability of the medical vocabulary in the medical database.

[0168] Embodiment 10:

[0169] This embodiment provides a management system for medical diagnosis data, such as Figure 3 As shown, including:

[0170] A collection module for collecting medical diagnosis data;

[0171] Model building module, used to build medical diagnosis data recognition model;

[0172] An identification module, used to identify medical diagnosis data based on a medical diagnosis data identification model, and to add medical field labels to key data based on the identification results;

[0173] The improvement module is used to improve the medical field labels in the medical field vocabulary.

[0174] The working principle and beneficial effects of the above technical solution are: by constructing a medical diagnosis data recognition model, the collected medical diagnosis data can be effectively identified, and then the medical field labels of key data in the medical diagnosis data can be determined based on the recognition results. By improving the medical field labels in the medical field vocabulary, the integrity and accuracy of the medical field vocabulary can be effectively guaranteed, further improving the comprehensiveness, accuracy and effectiveness of medical diagnosis data management, and also facilitating patients and doctors to quickly and effectively extract effective information from medical diagnosis data.

[0175] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for managing medical diagnostic data, characterized in that: include: Collect medical diagnostic data; Build a medical diagnostic data recognition model; Identify medical diagnostic data based on the medical diagnostic data recognition model, and add medical field labels to key data based on the recognition results; Improve the medical field labels in the medical field vocabulary, including: Determine the medical project library to which the current key data belongs based on medical field labels, and extract known medical terms in the medical project library; Construct a text semantic extraction dictionary based on text processing requirements, and generate text type constraints and text content constraints based on the text semantic extraction dictionary; Based on the text type constraint condition and the text content constraint condition, semantic recognition is performed on each known medical word in turn to obtain the semantic feature quantity of each known medical word; Determine the representation degree of known medical vocabulary and current key data based on semantic feature quantities, and when the representation degree is less than a set threshold, determine that the medical project library needs to be improved; Based on the determination results, the current key data and the corresponding medical field labels are encapsulated, and the medical vocabulary to be improved is obtained based on the encapsulation results; Extracting the data record log of the medical project library, and determining the medical vocabulary level in the medical project library and the level rules corresponding to each medical vocabulary level based on the data record log; Based on the preset scheduling engine, the medical vocabulary to be improved is distributedly added to the corresponding medical vocabulary level according to the hierarchical rules of each medical vocabulary level, and the improvement of the medical field vocabulary is completed based on the addition results.

2. A method for managing medical diagnostic data according to claim 1, characterized in that: Collect medical diagnostic data, including: Establishing a physical connection between the data acquisition device and the medical diagnosis database; sending a communication handshake protocol to the medical diagnosis database based on the actual connection between the data acquisition device and the medical diagnosis database, and establishing a communication connection between the data acquisition device and the medical diagnosis database based on the feedback information received by the data acquisition device; The instructions of the data acquisition device are transmitted to the medical diagnosis database, and the corresponding medical diagnosis data are collected in the medical diagnosis database according to the instructions to complete the acquisition of the medical diagnosis data.

3. A method for managing medical diagnostic data according to claim 2, characterized in that: Establishing a physical connection between the data collection device and the medical diagnostic database, including: Reading a connection interface of the medical diagnosis database in a document manager of the medical diagnosis database, and configuring an interface address of the connection interface of the medical diagnosis database; Connect the medical diagnosis database and data collection device to the same domain network; The actual connection with the data acquisition device is established in the same domain network based on the interface address of the connection interface of the medical diagnosis database.

4. A method for managing medical diagnostic data according to claim 2, characterized in that: According to the actual connection between the data acquisition device and the medical diagnosis database, a communication handshake protocol is sent to the medical diagnosis database, and according to the feedback information received by the data acquisition device, a communication connection between the data acquisition device and the medical diagnosis database is established, including: Constructing the communication protocol between the data acquisition device and the medical diagnosis database; Determine the communication handshake protocol code based on the data acquisition device according to the protocol requirements; Based on the actual connection between the data acquisition device and the medical diagnosis database and according to the communication protocol, the communication handshake protocol code is sent to the medical diagnosis database; Verify the communication handshake protocol code based on the medical diagnosis database and output feedback information; The feedback information of the medical diagnosis database is monitored based on the data acquisition device, and the acquisition device is communicatively connected with the medical diagnosis database according to the monitoring result.

5. A method for managing medical diagnostic data according to claim 2, characterized in that: The instructions of the data acquisition device are transmitted to the medical diagnosis database, and the corresponding medical diagnosis data are collected in the medical diagnosis database according to the instructions to complete the acquisition of the medical diagnosis data, including: Obtain user diagnostic information, and parse the user diagnostic information to determine diagnostic terms in the user diagnostic information; generating instructions in a data acquisition device according to the diagnosis nouns in the user diagnosis information; Transmitting the instruction of the data acquisition device to a medical diagnosis database for matching, and determining medical diagnosis data consistent with the instruction of the data acquisition device; Parsing the medical diagnosis data, determining the subordinate relationship of the medical diagnosis data, and dividing the medical diagnosis data according to the subordinate relationship of the medical diagnosis data to obtain a master node and a slave node; Packing the master node and the slave node based on the subordinate relationship to obtain a medical diagnosis data packet; The medical diagnosis data packet is transmitted from the medical diagnosis database to the data acquisition device via the communication connection.

6. A method for managing medical diagnostic data according to claim 1, characterized in that: Identify medical diagnostic data based on the medical diagnostic data recognition model, and add medical field labels to key data based on the recognition results, including: Inputting the medical diagnosis data into the medical diagnosis data recognition model for recognition, determining key data of the medical diagnosis data, and outputting medical field labels of the key data according to the medical diagnosis data recognition model; Add medical domain labels to key data in medical diagnostic data.

7. A method for managing medical diagnosis data according to claim 1, characterized in that: Based on the encapsulation results, the medical vocabulary to be improved is obtained, including: Acquire the medical vocabulary to be improved, and perform structural decomposition on the medical vocabulary to be improved to obtain a set of byte elements contained in the medical vocabulary to be improved; Based on the medical field terminology dictionary, the standardized term text of each byte element in the byte element set is determined respectively, and the standardized term text is byte-associated based on the source position of each byte element to obtain the standardized medical vocabulary corresponding to the medical vocabulary to be improved; The validity of standardized medical vocabulary is verified based on the verification index system, and the standardized medical vocabulary is added to the medical field vocabulary after the validity verification is passed.

8. A management system for medical diagnosis data, characterized in that: include: A collection module for collecting medical diagnosis data; Model building module, used to build medical diagnosis data recognition model; An identification module, used to identify medical diagnosis data based on a medical diagnosis data identification model, and to add medical field labels to key data based on the identification results; The improvement module is used to improve the medical field labels in the medical field vocabulary, including: Determine the medical project library to which the current key data belongs based on medical field labels, and extract known medical terms in the medical project library; Construct a text semantic extraction dictionary based on text processing requirements, and generate text type constraints and text content constraints based on the text semantic extraction dictionary; Based on the text type constraint condition and the text content constraint condition, semantic recognition is performed on each known medical word in turn to obtain the semantic feature quantity of each known medical word; Determine the representation degree of known medical vocabulary and current key data based on semantic feature quantities, and when the representation degree is less than a set threshold, determine that the medical project library needs to be improved; Based on the determination results, the current key data and the corresponding medical field labels are encapsulated, and the medical vocabulary to be improved is obtained based on the encapsulation results; Extracting the data record log of the medical project library, and determining the medical vocabulary level in the medical project library and the level rules corresponding to each medical vocabulary level based on the data record log; Based on the preset scheduling engine, the medical vocabulary to be improved is distributedly added to the corresponding medical vocabulary level according to the hierarchical rules of each medical vocabulary level, and the improvement of the medical field vocabulary is completed based on the addition results.

Images