CN114334067B - Label processing method and device for clinical data - Google Patents
Label processing method and device for clinical data Download PDFInfo
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Abstract
The application discloses a label processing method and a device of clinical data, the method responds to a first label generation instruction, determines a first data item in a clinical data record table, the first data item comprises a second data item corresponding to a target operation and a potential target data item, determines target data corresponding to a first label based on data generation time of the second data item and the potential target data item, generates a label database based on basic information of the first label and the target data corresponding to the first label, the basic information of the first label comprises a label name and a label weight, the label weight is used for representing confidence of the label, the label weight is dynamically updated based on update frequency of the target data corresponding to the label, responds to the data query instruction, determines the target label, displays a query result based on the current label weight of the target label, and can improve efficiency of labeling the clinical data and accuracy of the label, the accuracy of the clinical data query result is ensured.
Description
Technical Field
The application relates to the field of data processing, in particular to a label processing method and device for clinical data.
Background
In the big data era, the service mode of the traditional medical industry is changed while the data shows the quantitative, diversified and valuable changes. How to acquire and screen valuable information from massive clinical data of PB level and even EB level is a great challenge for hospital information department. By constructing patient labels, supporting accurate scientific research services is an effective solution to the above challenges.
Unlike internet tagging, however, hospital informatization generated clinical data includes unstructured data such as whether or not bleeding is occurring post-operatively, pre-operative jaundice patterns, secondary operations, and the like. For the labeling of the unstructured data with the time attribute, the existing technical scheme is to manually confirm the time generated by the data based on the clinical data of the hospital, and further distinguish the preoperative data from the postoperative data and mark (i.e. label printing), which is time-consuming and labor-consuming, and the accuracy of generating the label cannot be guaranteed, and correspondingly, the accuracy of the query result of the subsequent clinical data cannot be guaranteed.
Disclosure of Invention
In order to solve the above problems, the present application provides a method and an apparatus for processing a label of clinical data, so as to improve efficiency of labeling clinical data and accuracy of the label, and ensure accuracy of a query result of the clinical data.
In a first aspect, the present application provides a method for label processing of clinical data, the method comprising:
step S101, responding to a first label generation instruction, and determining a first data item in a clinical data record table, wherein the first data item comprises a second data item corresponding to a target operation and a potential target data item;
step S102, determining target data corresponding to the first label based on the data generation time of the second data item and the potential target data item;
step S103, generating a label database based on the basic information of the first label and the target data corresponding to the first label; the basic information of the first label comprises a label name and a label weight, wherein the label weight is used for representing the confidence coefficient of the label, and the label weight is dynamically updated based on the update frequency of target data corresponding to the label;
step S104, responding to a data query instruction, determining a target label in the label database, and displaying a query result based on the current label weight of the target label.
In an optional embodiment, the determining, based on the data generation time of the second data item and the potential target data item, the target data corresponding to the first tag specifically includes:
determining a target data item of the potential target data items based on the data generation times of the second data item and the potential target data items; the target data item meets the time screening condition in the data nanoarranging standard corresponding to the first label;
and taking the data corresponding to the target data item as the target data corresponding to the first label.
In an optional embodiment, the displaying of the query result based on the current tag weight of the target tag specifically includes:
determining the display priority of each target label based on the current label weight of each target label, and displaying a target label catalog based on the display priority of each target label;
and responding to the tag confirmation instruction, determining the selected second tag, and displaying the target data corresponding to the second tag.
In an alternative embodiment, the method further comprises:
detecting whether the data corresponding to the target data item is updated or not based on a preset frequency, and if yes, synchronously updating the target data corresponding to the first label;
and adjusting the label weight of the first label based on the update frequency of the target data corresponding to the first label.
In an optional implementation manner, the adjusting the tag weight of the first tag based on the update frequency of the target data corresponding to the first tag specifically includes:
when the first tag is a dynamic attribute tag, adjusting the tag weight of the first tag based on the update frequency of the target data corresponding to the first tag, the preset validity period of the first tag and the use frequency of the first tag;
the use frequency of the first label refers to the frequency of the first label being selected in a preset time period.
In an optional embodiment, the adjusting, based on the update frequency of the target data corresponding to the first tag, the preset validity period of the first tag, and the usage frequency of the first tag, the tag weight of the first tag specifically includes:
determining whether the first label is expired based on the generation time of the first label and a preset validity period of the first label;
and under the condition that the first label is expired, if the updating frequency of the target data corresponding to the first label is lower than a first preset threshold and the using frequency of the first label is lower than a second preset threshold, reducing the label weight of the first label according to a preset adjusting amplitude.
In an optional embodiment, after the tag weight of the first tag is decreased according to a preset adjustment amplitude, the method further includes:
judging whether the label weight of the first label is lower than a third preset threshold value, if so, pushing deletion confirmation information to a corresponding terminal;
responding to a confirmation instruction aiming at the deletion confirmation information, and performing corresponding operation on the first label.
In an alternative embodiment, before step S102, the method further comprises:
comparing the data storage standard corresponding to the first label with the storage standard corresponding to the historical label, and determining whether a third label matched with the first label exists; the third label is a label with the label weight higher than a third preset threshold;
if yes, determining target data corresponding to the first label based on the target data corresponding to the third label, and executing step 104; if not, go to step 102.
In an alternative embodiment, the tag name is determined based on a first tag name input by a user and a data inclusion criterion corresponding to the first tag.
In a second aspect, the present application also proposes a tag processing apparatus for clinical data, the apparatus comprising:
a first data item determination module, configured to determine, in response to a first tag generation instruction, a first data item in a clinical data record table, where the first data item includes a second data item corresponding to a target procedure and a potential target data item;
a target data determination module to determine target data corresponding to the first tag based on data generation times of the second data item and the potential target data item;
a tag database generation module, configured to generate a tag database based on the basic information of the first tag and target data corresponding to the first tag; the basic information of the first label comprises a label name and a label weight, wherein the label weight is used for representing the confidence coefficient of the label, and the label weight is dynamically updated based on the update frequency of target data corresponding to the label;
and the query result display module is used for responding to a data query instruction, determining a target label in the label database and displaying a query result based on the current label weight of the target label.
In a third aspect, the present application also proposes an electronic device comprising a processor, a memory and a program or instructions stored on the memory and executable on the processor, which when executed by the processor implements the steps of the method for signature processing of clinical data according to the first aspect.
In a fourth aspect, the present application also proposes a processor-readable storage medium on which a program or instructions are stored, which program or instructions, when executed by a processor, implement the steps of the method of signature processing of clinical data according to the first aspect.
The embodiment of the application can at least achieve the following beneficial effects: by responding to a first label generation instruction, determining a first data item in a clinical data record table, wherein the first data item comprises a second data item corresponding to a target operation and a potential target data item, determining target data corresponding to a first label based on the data generation time of the second data item and the potential target data item, generating a label database based on basic information of the first label and the target data corresponding to the first label, rapidly acquiring unstructured data corresponding to the label, and improving the efficiency of labeling clinical data, wherein the basic information of the first label comprises a label name and a label weight, the label weight is used for representing the confidence coefficient of the label, the label weight is dynamically updated based on the update frequency of the target data corresponding to the label, and responding to a data query instruction, determining the target label in the label database, and the query result is displayed based on the current label weight of the target label, so that the accuracy of the label can be ensured, and the accuracy of the query result of clinical data can be ensured.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly described below. It is appreciated that the following drawings depict only certain embodiments of the application and are not to be considered limiting of its scope.
FIG. 1 is a schematic flow diagram of a method of label processing of clinical data according to an embodiment of the present application;
FIG. 2 is a schematic block diagram of a tag processing apparatus for clinical data according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings of the embodiments of the present application. It should be understood, however, that the detailed description and specific examples, while indicating the preferred embodiment of the application, are intended for purposes of illustration only and are not intended to limit the scope of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and in the claims of this application are used for distinguishing between similar elements and not for describing a particular sequential or chronological order, nor should they be construed to indicate or imply relative importance.
As previously mentioned, clinical data generated by hospital informatization includes unstructured data such as whether bleeding occurred after surgery, preoperative ways of jaundice, etc. For the labeling of the unstructured data with the time attribute, as structured data (such as sex, age, name, etc.) cannot be directly extracted from hospital clinical data and aggregated, the existing technical scheme is based on the hospital clinical data, manually confirms the time generated by the data, and further distinguishes preoperative data and postoperative data and labels, not only is time and labor consumed, but also the accuracy of generating the labels cannot be guaranteed, and correspondingly, the accuracy of the query result of subsequent clinical data cannot be guaranteed. Therefore, the method and the device for processing the label of the clinical data are provided to improve the efficiency of labeling the clinical data and the accuracy of the label and ensure the accuracy of the query result of the clinical data.
Fig. 1 is a flow diagram illustrating a method for label processing of clinical data according to an embodiment of the present application. As shown in fig. 1, the method comprises the steps of:
step S101, responding to a first label generation instruction, and determining a first data item in a clinical data record table, wherein the first data item comprises a second data item corresponding to a target operation and a potential target data item;
specifically, a hospital usually stores diagnosis and treatment data generated by patient treatment in a clinical data record table, and manages the diagnosis and treatment data through a treatment number. That is, one visit corresponds to a unique visit number, and all the diagnosis and treatment data generated by the visit are stored in association with the visit number as a visit record. It will be appreciated that each visit record corresponds to at least one data item, such as patient gender, age, surgery, test, etc. Based on the storage mode of the clinical data record table, structured data such as gender, age and the like can be extracted quickly (only corresponding data items need to be matched and data corresponding to the data items needs to be extracted directly), aggregation and labeling are carried out, and therefore quick query can be achieved only based on labels when relevant data are searched subsequently. However, unstructured data with time attributes, such as bleeding after operation, preoperative jaundice reduction, preoperative and postoperative examination, cannot be directly extracted from corresponding data items, however, in medical research, relevant data before and after operation have important research values, and if relevant data can be rapidly and accurately acquired, great convenience is provided for subsequent medical research. The existing technical scheme is based on hospital clinical data, the time for generating the data is confirmed manually, preoperative data and postoperative data are distinguished and labeled, the mode is low in efficiency, and a great deal of inconvenience is brought to follow-up medical scientific research.
Based on this, the embodiment of the application provides a technical scheme for automatically extracting unstructured data and generating a label for the unstructured data. Specifically, the label processing apparatus for clinical data may receive a first label generation instruction issued by a first user, determine a nano-ranking criterion of corresponding target data based on the first label generation instruction, and filter the target data. It may be understood that the first user may be a doctor or other staff having a tagging authority, and this is not limited in this embodiment of the present application. The first tag generation instruction may be generated based on a tag name and/or a data filtering condition input by a user, that is, the user may directly input the tag name, and the tag processing apparatus for clinical data may determine the nano-ranking standard of the corresponding target data based on the tag name input by the user, which has a high requirement on the professional level of the user, and if the input tag name is not standardized, the nano-ranking standard of the target data may not be accurately determined. Of course, the user may also input the label name and the data filtering condition at the same time, so that the label processing apparatus of the clinical data accurately determines the nano-ranking criteria of the target data based on the contents of the two aspects.
The label processing device of the clinical data responds to a first label generation instruction of a first user, and after the nancing standard of corresponding target data is determined, a first data item in the clinical data record table can be determined, wherein the first data item comprises a second data item corresponding to a target operation and a potential target data item. For example, the first tag generation instruction instructs to screen the CA199 (Carbohydrate antigen 199) index for the first time after the pancreaticoduodenectomy, the corresponding nandina criterion may be determined as surgery = pancreaticoduodenectomy, and the test name = CA199, and based on the nandina criterion, the first data item in the clinical data record table may be determined, the first data item including the second data item corresponding to the target surgery (i.e., pancreaticoduodenectomy) and the potential target data item (i.e., the data item with the test name CA 199).
Step S102, determining target data corresponding to the first label based on the data generation time of the second data item and the potential target data item;
in particular, after the first data item is determined, the tag processing means of the clinical data may determine the target data based on the data generation time of the potential target data item and the second data item. In the foregoing example, if there are multiple CA199 tests before and after the operation, the post-operation test data may be determined based on the test data generation time and the operation data generation time, and then the post-operation first CA199 test data (i.e. the target data corresponding to the first tag) may be determined based on the generation time of each post-operation test data.
Step S103, generating a label database based on the basic information of the first label and the target data corresponding to the first label; the basic information of the first label comprises a label name and a label weight, wherein the label weight is used for representing the confidence coefficient of the label, and the label weight is dynamically updated based on the update frequency of target data corresponding to the label;
specifically, after the target data corresponding to the first label is determined, the label processing device of the clinical data may associate and store the basic information of the first label and the target data corresponding to the first label to generate a label database. It is understood that the tag database stores at least one first tag and its corresponding basic information and target data for subsequent data fast query. The basic information of the first tag includes a tag name and a tag weight, and it can be understood that the tag name is used to accurately represent content related to target data corresponding to the tag so as to perform accurate query subsequently, and the tag name may be obtained after normalization processing is performed on the basis of the tag name input by the first user, or may be generated by extracting key information and based on the key information on the basis of a data screening condition input by the first user, which is not specifically limited in this embodiment of the present application.
The label weight is used to characterize the confidence of the label, and in some cases, a label may appear in multiple scenarios, such as: the weight label, which may be generated at the time of admission (i.e., pre-operation) or during the care process (i.e., post-operation), is different for the same label for both scenarios. Admission is much less weighted than care because the data for care is more accurate. Of course, a corresponding weight may also be set for the tag based on the relevance between the target data corresponding to the tag and the subsequent scientific research, so as to accurately obtain the target data corresponding to the target tag in the data query process. The label weight may be manually set based on the relevance between the target data corresponding to the label and the subsequent scientific research and/or a scene corresponding to the target data when the first user generates the first label, or may be automatically set based on the above information by the label processing device for the clinical data, which is not specifically limited in this embodiment of the present application.
It is understood that the weight of the target data corresponding to the tag is not constant, and may be wider in application range during the first period, but be reduced in application range during the second period, and vice versa. Based on this, in order to ensure the accuracy of the subsequent data query result, the embodiment of the present application may adjust the tag weight of the first tag based on the actual situation. Specifically, in the embodiment of the present application, the state of the first tag is determined based on the update frequency of the target data corresponding to the first tag, in general, an active tag whose corresponding target data is continuously updated with the increase of the patient diagnosis and treatment data, and if the update frequency is lower than a normal level, it may be determined that the activity is decreased, and vice versa. Therefore, the label weight of the first label is adjusted based on the update frequency of the target data corresponding to the first label, and the accuracy of the subsequent data query result can be ensured.
Step S104, responding to a data query instruction, determining a target label in the label database, and displaying a query result based on the current label weight of the target label.
Specifically, after generating the tag database, the tag processing device of the clinical data may determine a target tag in the tag database in response to a data query instruction of a second user, and display a query result based on a current weight of the target tag. It is to be understood that, similar to the first tag generation instruction, the data query instruction may be generated based on a tag name and/or a query keyword input by a user, that is, the user may directly input the tag name, and the tag processing device of the clinical data may determine a matching target tag based on the tag name input by the user, which is more demanding on the professional level of the user, and may not accurately determine the target tag if the input tag name is not standardized, so that this embodiment of the present application also provides another instruction input mode with a lower threshold, that is, the user may directly input the query keyword, and the tag processing device of the clinical data may determine the corresponding target tag based on the query keyword input by the user. Of course, the user may also input the label name and the query keyword at the same time, so that the label processing device of the clinical data can accurately determine the target label based on the contents of the two aspects.
It is to be understood that the target tags may be one or more, and when there are multiple target tags, the tag processing device of the clinical data may display the query result based on the current weight of the target tags, for example, display a target tag list, with the higher weight of the tag being displayed or highlighted, so that the second user can quickly determine the target tag matching the needs of the second user. It can also be understood that only the target tags whose weights are higher than a certain preset threshold may be displayed in the query result, so as to ensure the accuracy of the query result and reduce the workload of the second user for screening the matched tags. In view of reducing the workload of screening the matching tags by the second user, the embodiment of the application further displays the nano-ranking standard and/or the target data example of each target tag in the interface for displaying the query result, so that the second user can rapidly screen the matching tags, and the query efficiency is improved.
The label processing method for clinical data provided by the embodiment of the application determines a first data item in a clinical data record table in response to a first label generation instruction, wherein the first data item comprises a second data item corresponding to a target operation and a potential target data item, determines target data corresponding to a first label based on data generation time of the second data item and the potential target data item, generates a label database based on basic information of the first label and the target data corresponding to the first label, can quickly acquire unstructured data corresponding to the label, and improves efficiency of labeling the clinical data, the basic information of the first label comprises a label name and a label weight, the label weight is used for representing the label, and the label weight is dynamically updated based on update frequency of the target data corresponding to the label, and responding to a data query instruction, determining a target label in the label database, and displaying a query result based on the current label weight of the target label, so that the accuracy of the label can be ensured, and the accuracy of the query result of clinical data can be ensured.
Optionally, the determining the target data corresponding to the first tag based on the data generation time of the second data item and the potential target data item specifically includes:
determining a target data item of the potential target data items based on the data generation times of the second data item and the potential target data items; the target data item meets the time screening condition in the data nanoarranging standard corresponding to the first label;
and taking the data corresponding to the target data item as the target data corresponding to the first label.
Specifically, following the example of the first CA199 after pancreaticoduodenectomy in the foregoing embodiment, the first tag generation instruction may instruct to screen the first CA199 after pancreaticoduodenectomy, the tag processing device of the clinical data may first determine, based on the nana criterion, a first data item in the clinical data record table, where the first data item includes a second data item corresponding to a target operation (i.e., pancreaticoduodenectomy) and a potential target data item (i.e., a data item with a check name of CA 199), determine, based on a time screening condition (i.e., check time > operation time, taken last time) in the data nana criterion corresponding to the first tag, a target data item in the potential target data item, and take data corresponding to the target data item as target data corresponding to the first tag.
According to the label processing method for clinical data provided by the embodiment of the application, the target data item in the potential target data item is determined based on the data generation time of the second data item and the potential target data item, wherein the target data item meets the time screening condition in the data nanoarranging standard corresponding to the first label, the data corresponding to the target data item is used as the target data corresponding to the first label, the target data corresponding to the first label can be quickly acquired, and the efficiency of labeling the clinical data is improved.
Optionally, the displaying of the query result based on the current tag weight of the target tag specifically includes:
determining the display priority of each target label based on the current label weight of each target label, and displaying a target label catalog based on the display priority of each target label;
and responding to the tag confirmation instruction, determining the selected second tag, and displaying the target data corresponding to the second tag.
Specifically, in consideration of both accuracy of query results and query efficiency, the tag processing apparatus of clinical data may determine a display priority of each target tag based on a current weight of each target tag, and preferably, the higher the current weight of the target tag is, the higher the display priority is, and the target tag directory is displayed based on the display priority of each target tag. Based on the foregoing embodiment, the target tag directory may only show target tags whose weights are higher than a certain preset threshold, so as to ensure accuracy of a query result, and meanwhile, in the embodiment of the present application, a nano-ranking standard and/or a target data example of each target tag may be shown at a corresponding position of the target tag directory, so that the second user can quickly filter matching tags, and the filtering workload of the second user is reduced. Correspondingly, after the target label list is displayed, the label processing device of the clinical data may detect whether a label confirmation instruction of the second user is received in real time, determine the selected second label (i.e., the target label matching with the second user requirement), and display the target data corresponding to the second label for subsequent application. It is to be understood that the second user may be the same as or different from the first user, and the "first" and "second" are only for convenience of description and do not constitute a specific limitation to the user. The tag confirmation instruction of the second user may be input based on an operation of the second user, such as clicking or sliding the interface target position, which is not specifically limited in this embodiment of the application.
According to the label processing method for the clinical data, the display priority of each target label is determined based on the current label weight of each target label, the target label list is displayed based on the display priority of each target label, the selected second label is determined in response to the label confirmation instruction, the target data corresponding to the second label is displayed, and the query efficiency can be improved while the accuracy of the clinical data query result is ensured.
Optionally, the method further includes:
detecting whether the data corresponding to the target data item is updated or not based on a preset frequency, and if yes, synchronously updating the target data corresponding to the first label;
and adjusting the label weight of the first label based on the update frequency of the target data corresponding to the first label.
Specifically, as the diagnosis and treatment data of the patient continuously increases, the data corresponding to the target data item is also updated, and in consideration of ensuring the accuracy of the target data, in the embodiment of the present application, the tag processing device of the clinical data detects whether the data corresponding to the target data item is updated based on the preset frequency, and if so, the target data corresponding to the first tag is synchronously updated. The specific value of the preset frequency may be freely set based on actual requirements, and of course, a real-time detection mode may also be adopted, which is not specifically limited in this embodiment of the present application. And analyzing the state of the first label based on the updating frequency of the target data corresponding to the first label, and adjusting the label weight of the first label.
According to the label processing method of the clinical data, whether the data corresponding to the target data item are updated or not is detected based on the preset frequency, if yes, the target data corresponding to the first label are synchronously updated, the label weight of the first label is adjusted based on the update frequency of the target data corresponding to the first label, the update timeliness of the target data corresponding to the first label can be guaranteed, meanwhile, the label weight of the first label is adjusted based on the update frequency of the target data, and the accuracy of a data query result can be guaranteed.
Optionally, the adjusting the tag weight of the first tag based on the update frequency of the target data corresponding to the first tag specifically includes:
when the first tag is a dynamic attribute tag, adjusting the tag weight of the first tag based on the update frequency of the target data corresponding to the first tag, the preset validity period of the first tag and the use frequency of the first tag;
the use frequency of the first label refers to the frequency of the first label being selected in a preset time period.
Specifically, for a dynamic attribute tag, a preset validity period usually exists, and for an expired tag, the dynamic attribute tag and associated target data are directly deleted conventionally to ensure the accuracy of the tag. However, the inventor of the present application finds that, for some dynamic attribute tags, application values still exist after the tags expire, and if the tags are only deleted based on the validity period, many valuable data are deleted, which affects the efficiency and accuracy of subsequent data query, based on this, in the embodiment of the present application, when the first tag is a dynamic attribute tag, the update frequency of the target data corresponding to the first tag, the preset validity period of the first tag, and the usage frequency of the first tag are comprehensively considered, the tag weight of the first tag is adjusted, and only when the tag weight of the first tag is lower than a certain threshold, the deletion operation is considered, so that the usage values of the tags are fully utilized, and the efficiency and accuracy of subsequent data query are ensured.
According to the label processing method of the clinical data, provided by the embodiment of the application, under the condition that the first label is the dynamic attribute label, the label weight of the first label is adjusted based on the update frequency of the target data corresponding to the first label, the preset validity period of the first label and the use frequency of the first label, wherein the use frequency of the first label refers to the frequency of the first label being selected within the preset time period, so that the use value of the label can be fully utilized, and the efficiency and the accuracy of subsequent data query are ensured.
Optionally, the adjusting the label weight of the first label based on the update frequency of the target data corresponding to the first label, the preset validity period of the first label, and the usage frequency of the first label specifically includes:
determining whether the first label is expired based on the generation time of the first label and the preset validity period of the first label;
and under the condition that the first label is expired, if the updating frequency of the target data corresponding to the first label is lower than a first preset threshold and the using frequency of the first label is lower than a second preset threshold, reducing the label weight of the first label according to a preset adjusting amplitude.
Specifically, in the case that the first tag is expired, the embodiment of the present application does not directly delete the first tag, but further determines whether the first tag has a use value based on the update frequency of the target data corresponding to the first tag and the use frequency of the first tag, and specifically, when the update frequency of the target data corresponding to the first tag is lower than a first preset threshold (for example, the target data corresponding to the first tag is not updated for a long time) and the use frequency of the first tag is lower than a second preset threshold (for example, the first tag is not retrieved and utilized for a long time), the tag weight of the first tag is reduced according to a preset adjustment amplitude. And then based on the label weight of the first label, the priority of label display in the data query process can be adjusted, and the accuracy of the data query result is ensured on the premise of fully utilizing the use value of the label. It can be understood that the first preset threshold, the second preset threshold, and the preset adjustment range may be set according to actual conditions, and values thereof are not specifically limited in the embodiments of the present application.
According to the label processing method for clinical data provided by the embodiment of the application, whether the first label is expired is determined based on the generation time of the first label and the preset validity period of the first label, and if the update frequency of the target data corresponding to the first label is lower than a first preset threshold and the use frequency of the first label is lower than a second preset threshold under the condition that the first label is expired, the label weight of the first label is reduced according to a preset adjustment range, so that the accuracy of a data query result can be ensured on the premise that the use value of the label is fully utilized.
Optionally, after the tag weight of the first tag is reduced according to a preset adjustment amplitude, the method further includes:
judging whether the label weight of the first label is lower than a third preset threshold value, if so, pushing deletion confirmation information to a corresponding terminal;
responding to a confirmation instruction aiming at the deletion confirmation information, and performing corresponding operation on the first label
Specifically, in this embodiment of the application, the tag processing device of the clinical data will push deletion confirmation information to the terminal corresponding to the first user only when determining that the tag weight of the first tag is lower than a third preset threshold, and will delete the first tag and the target data corresponding to the first tag only after receiving a deletion confirmation instruction of the first user. If the first user judges that the first label still has the application value, a deletion rejection instruction can be input, and the label weight of the first label is reset based on the actual situation. Based on the method, the use value of the first label can be further fully utilized, and the accuracy and comprehensiveness of the follow-up data query result are ensured. It can be understood that a specific value of the third preset threshold may be set according to an actual situation, and this is not specifically limited in this embodiment of the present application.
According to the label processing method for the clinical data, whether the label weight of the first label is lower than a third preset threshold value or not is judged, if yes, the deleting confirmation information is pushed to the corresponding terminal, the confirmation instruction aiming at the deleting confirmation information is responded, the first label is correspondingly operated, the use value of the first label can be further fully utilized, and meanwhile the accuracy and the comprehensiveness of the follow-up data query result are guaranteed.
Optionally, before step S102, the method further includes:
comparing the data storage standard corresponding to the first label with the storage standard corresponding to the historical label, and determining whether a third label matched with the first label exists; the third label is a label with the label weight higher than a third preset threshold value;
if yes, determining target data corresponding to the first label based on the target data corresponding to the third label, and executing step 104; if not, go to step 102.
Specifically, after the label processing device of the clinical data responds to a first label generation instruction of a first user and determines the data storage and arrangement standard corresponding to the first label, the data storage and arrangement standard corresponding to the first label can be directly compared with the storage and arrangement standard corresponding to the historical label, so that a process of screening target data from a clinical data record table is avoided, the target data corresponding to the historical label can be directly used for screening the target data corresponding to the first label, and the labeling efficiency is further improved. Following the first CA199 example after the pancreaticoduodenum operation in the foregoing embodiment, the first tag generating instruction indicates to screen the first CA199 index after the pancreaticoduodenum operation, and the tag processing device of the clinical data determines that the data nano-scale corresponding to the first tag is: surgery = pancreaticoduodenectomy, test name = CA199, test time > time of surgery and taken once most recently, if there is a third tag in the history tag, the corresponding data inclusion criteria is: surgery = pancreaticoduodenectomy, exam name = CA199, exam time > surgery time and the most recent two times (i.e., the first two times CA199 after pancreaticoduodenectomy), based on the comparison, the third tag may be used as the tag matching the first tag, and based on the target data corresponding to the third tag, the target data corresponding to the first tag is determined (only the second time CA199 data after surgery needs to be excluded).
Of course, the number of the third labels may also be multiple, for example, the first label generation instruction indicates to screen the first two CA199 indexes after the pancreaticoduodenum operation, and the label processing device of the clinical data determines that the data inclusion criterion corresponding to the first label is: surgery = pancreaticoduodenectomy, exam name = CA199, exam time > time of surgery and the last two times, if there are two third tags in the history tag, labeled as tag a and tag B, respectively, the data rearrangement criteria for tag a is: surgery = pancreaticoduodenectomy, test name = CA199, test time > time of surgery and taken the most recent (i.e. first CA199 after pancreaticoduodenectomy), the data rearrangement criteria for tag B were: surgery = pancreaticoduodenectomy, exam name = CA199, exam time > surgery time and the second most recent time (i.e., second CA199 after pancreaticoduodenectomy), based on the comparison, tag a and tag B may be regarded as matching tags with the first tag, and target data corresponding to the first tag may be determined based on the target data corresponding to tag a and tag B (it is only necessary to merge the data of tag a and tag B).
It may be understood that a plurality of third tags matched with the first tag may also be provided, and meanwhile, in addition to performing the target data screening of the first tag based on the target data of one third tag and performing the merging based on the target data of two third tags to obtain the target data of the first tag, the target data corresponding to the first tag may also be obtained in a manner of performing the screening or intersection taking, union taking, and the like based on the target data of a plurality of third tags in the embodiment of the present application, which is not specifically limited in the embodiment of the present application.
Meanwhile, if a third label matched with the first label is not obtained based on the comparison result of the data storage standard corresponding to the first label and the storage standard corresponding to the historical label, the step 102 is continuously executed, and the target data is screened from the clinical data record table, so that the efficiency of labeling can be improved as much as possible on the basis of ensuring the accuracy of the label.
It should be noted that the third label is a label with a label weight higher than a third preset threshold (i.e., a label with a higher confidence), so as to ensure the accuracy of the finally obtained target data corresponding to the first label, and further ensure the accuracy of the label.
According to the label processing method for the clinical data, whether a third label matched with the first label exists or not is determined by comparing the data admittance standard corresponding to the first label with the admittance standard corresponding to the historical label; and if not, executing the step 102, and improving the labeling efficiency as much as possible on the basis of ensuring the accuracy of the label.
Optionally, the tag name is determined based on a first tag name input by a user and a data nanoarray standard corresponding to the first tag.
Specifically, in the foregoing embodiment, it is mentioned that the tag name is used to accurately represent content related to target data corresponding to a tag, so as to perform accurate query subsequently, and the tag name may be obtained after being normalized based on the tag name input by the first user, or may be generated based on the key information by extracting key information (that is, a data inclusion criterion corresponding to the first tag) based on a data filtering condition input by the first user And further, more accurate and standard label names are determined, and the efficiency and accuracy of subsequent data query are conveniently improved. Meanwhile, the label processing device of the clinical data can also determine whether the same label exists in the historical labels or not based on the data nano-arrangement standard corresponding to the first label, so that the repeated generation of the labels is avoided, and unnecessary redundancy is avoided.
As for a specific generation manner of the label name, the label processing device of the clinical data may automatically generate the label name based on the first label name input by the first user and the data inclusion and exclusion standard corresponding to the first label, or during the process that the user inputs the information, the label processing device of the clinical data determines an alternative label name based on the input information of the user and pushes the alternative label name to the first user, so as to help the user to quickly generate an accurate and normative label name in an interactive manner, which is not specifically limited in the embodiment of the present application.
According to the label processing method of the clinical data, the label name is determined based on the first label name input by the user and the data storage and discharge standard corresponding to the first label, so that the more accurate and standard label name can be determined, and the efficiency and accuracy of subsequent data query are conveniently improved.
Fig. 2 is a schematic structural diagram of a tag processing apparatus for clinical data according to an embodiment of the present application. As shown in fig. 2, the apparatus includes the following modules:
a first data item determination module 201, configured to determine, in response to a first tag generation instruction, a first data item in a clinical data record table, where the first data item includes a second data item corresponding to a target procedure and a potential target data item;
a target data determination module 202, configured to determine target data corresponding to the first tag based on data generation times of the second data item and the potential target data item;
a tag database generation module 203, configured to generate a tag database based on the basic information of the first tag and the target data corresponding to the first tag; the basic information of the first label comprises a label name and a label weight, wherein the label weight is used for representing the confidence coefficient of the label, and the label weight is dynamically updated based on the update frequency of target data corresponding to the label;
and the query result display module 204 is configured to determine a target tag in the tag database in response to a data query instruction, and display a query result based on the current tag weight of the target tag.
Optionally, the target data determining module 202 is specifically configured to:
determining a target data item of the potential target data items based on the data generation times of the second data item and the potential target data items; the target data item meets the time screening condition in the data nano-arrangement standard corresponding to the first label;
and taking the data corresponding to the target data item as the target data corresponding to the first label.
Optionally, the query result displaying module 204 specifically includes:
the target label catalogue display submodule is used for determining the display priority of each target label based on the current label weight of each target label and displaying the target label catalogue based on the display priority of each target label;
and the target data display submodule is used for responding to the tag confirmation instruction, determining the selected second tag and displaying the target data corresponding to the second tag.
Optionally, the apparatus further comprises:
the target data updating module is used for detecting whether the data corresponding to the target data item is updated or not based on a preset frequency, and if yes, the target data corresponding to the first label is synchronously updated;
and the weight updating module is used for adjusting the label weight of the first label based on the updating frequency of the target data corresponding to the first label.
Optionally, the weight updating module is specifically configured to:
when the first tag is a dynamic attribute tag, adjusting the tag weight of the first tag based on the update frequency of the target data corresponding to the first tag, the preset validity period of the first tag and the use frequency of the first tag;
the use frequency of the first label refers to the frequency of the first label being selected in a preset time period.
Optionally, the weight updating module specifically includes:
the expiration judging submodule is used for determining whether the first label is expired or not based on the generation time of the first label and the preset validity period of the first label;
the weight adjusting submodule is configured to, when the first tag is expired, reduce the tag weight of the first tag according to a preset adjustment range if the update frequency of the target data corresponding to the first tag is lower than a first preset threshold and the usage frequency of the first tag is lower than a second preset threshold.
Optionally, the weight updating module further includes:
the deletion confirmation information sending submodule is used for judging whether the label weight of the first label is lower than a third preset threshold value or not, and if so, pushing deletion confirmation information to the corresponding terminal;
and the tag processing submodule is used for responding to the confirmation instruction aiming at the deletion confirmation information and carrying out corresponding operation on the first tag.
Optionally, the apparatus further comprises:
a third tag determination module, configured to compare the data inclusion and exclusion standard corresponding to the first tag with the inclusion and exclusion standard corresponding to the historical tag, and determine whether a third tag matching the first tag exists; the third label is a label with the label weight higher than a third preset threshold;
and the first target data determining module is used for determining target data corresponding to the first label based on the target data corresponding to the third label.
Optionally, the tag name is determined based on a first tag name input by a user and a data admittance standard corresponding to the first tag.
It should be noted that, those skilled in the art can understand that different embodiments described in the method embodiment of the present application, and descriptions thereof, and technical effects achieved are also applicable to the apparatus embodiment of the present application, and are not described herein again.
The embodiments of the present application may be implemented by software, hardware, or a combination of software and hardware. When implemented as a computer software program, the computer software program can be installed in various electronic devices such as mobile terminals, computers, servers, etc. and executed by one or more processors to implement the corresponding functions.
Fig. 3 illustrates a schematic physical structure diagram of an electronic device, and as shown in fig. 3, the electronic device may include: a processor (processor)301, a communication Interface (communication Interface)302, a memory (memory)303 and a communication bus 304, wherein the processor 301, the communication Interface 302 and the memory 303 complete communication with each other through the communication bus 304. The processor 301 uses logic instructions in the memory 303 to perform the tagging of clinical data provided by the various embodiments described above.
In addition, the logic instructions in the memory 303 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present application further provides a non-transitory computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the label processing method for clinical data provided by the above embodiments.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (6)
1. A method of label processing of clinical data, the method comprising:
step S101, responding to a first label generation instruction, and determining a first data item in a clinical data record table, wherein the first data item comprises a second data item corresponding to a target operation and a potential target data item;
step S102, determining target data corresponding to the first label based on the data generation time of the second data item and the potential target data item; the target data is unstructured data with a time attribute;
step S103, generating a label database based on the basic information of the first label and the target data corresponding to the first label; the basic information of the first label comprises a label name and a label weight, wherein the label weight is used for representing the confidence degree of the label, the label weight is set based on the relevance between target data corresponding to the first label and subsequent scientific research and/or a scene corresponding to the target data when the first label is generated, and the label weight is dynamically updated based on the updating frequency of the target data corresponding to the label;
step S104, responding to a data query instruction, determining a target label in the label database, and displaying a query result based on the current label weight of the target label; the query result comprises a nano-ranking standard and/or a target data example of each target label;
the method further comprises the following steps:
detecting whether the data corresponding to the target data item is updated or not based on a preset frequency, and if yes, synchronously updating the target data corresponding to the first label;
determining whether the first label is expired or not based on the generation time of the first label and the preset validity period of the first label under the condition that the first label is a dynamic attribute label;
under the condition that the first tag is expired, if the updating frequency of the target data corresponding to the first tag is lower than a first preset threshold and the using frequency of the first tag is lower than a second preset threshold, reducing the tag weight of the first tag according to a preset adjusting amplitude;
judging whether the label weight of the first label is lower than a third preset threshold value or not, if so, pushing deletion confirmation information to the corresponding terminal;
resetting a tag weight of the first tag in response to a delete rejection instruction for the delete confirmation information;
the use frequency of the first label refers to the frequency of the first label being selected in a preset time period.
2. The method for processing the label of the clinical data according to claim 1, wherein the determining the target data corresponding to the first label based on the data generation time of the second data item and the potential target data item specifically comprises:
determining a target data item of the potential target data items based on the data generation times of the second data item and the potential target data items; the target data item meets the time screening condition in the data nano-arrangement standard corresponding to the first label;
and taking the data corresponding to the target data item as the target data corresponding to the first label.
3. The method for processing labels of clinical data according to claim 2, wherein the presenting query results based on the current label weight of the target label specifically comprises:
determining the display priority of each target label based on the current label weight of each target label, and displaying a target label catalog based on the display priority of each target label;
and responding to the tag confirmation instruction, determining the selected second tag, and displaying the target data corresponding to the second tag.
4. The method of label processing of clinical data according to claim 1, wherein prior to step S102, the method further comprises:
comparing the data storage standard corresponding to the first label with the storage standard corresponding to the historical label, and determining whether a third label matched with the first label exists; the third label is a label with the label weight higher than a third preset threshold;
if yes, determining target data corresponding to the first label based on the target data corresponding to the third label, and executing step 104; if not, go to step 102.
5. The method for processing the label of the clinical data according to claim 1, wherein the label name is determined based on a first label name input by a user and a data nanoarray standard corresponding to the first label.
6. An apparatus for label processing of clinical data, the apparatus comprising:
a first data item determination module, configured to determine, in response to a first tag generation instruction, a first data item in a clinical data record table, where the first data item includes a second data item corresponding to a target procedure and a potential target data item;
a target data determination module for determining target data corresponding to the first tag based on data generation times of the second data item and the potential target data item; the target data is unstructured data with a time attribute;
a tag database generation module, configured to generate a tag database based on the basic information of the first tag and target data corresponding to the first tag; the basic information of the first label comprises a label name and a label weight, wherein the label weight is used for representing the confidence degree of the label, the label weight is set based on the relevance between target data corresponding to the first label and subsequent scientific research and/or a scene corresponding to the target data when the first label is generated, and the label weight is dynamically updated based on the updating frequency of the target data corresponding to the label;
the query result display module is used for responding to a data query instruction, determining a target label in the label database and displaying a query result based on the current label weight of the target label; the query result comprises a nanoranking criterion and/or a target data example of each target label;
the device further comprises a tag processing module, wherein the tag processing module is specifically configured to:
detecting whether the data corresponding to the target data item is updated or not based on a preset frequency, and if yes, synchronously updating the target data corresponding to the first label;
determining whether the first label is expired or not based on the generation time of the first label and the preset validity period of the first label under the condition that the first label is a dynamic attribute label;
under the condition that the first label is expired, if the updating frequency of the target data corresponding to the first label is lower than a first preset threshold and the using frequency of the first label is lower than a second preset threshold, reducing the label weight of the first label according to a preset adjusting amplitude;
judging whether the label weight of the first label is lower than a third preset threshold value or not, if so, pushing deletion confirmation information to the corresponding terminal;
resetting a tag weight of the first tag in response to a delete rejection instruction for the delete confirmation information;
the use frequency of the first label refers to the frequency of the first label being selected in a preset time period.
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