CN109147883A - Original document mapping, management method and its system applied to clinical testing data - Google Patents
Original document mapping, management method and its system applied to clinical testing data Download PDFInfo
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- 238000012360 testing method Methods 0.000 title claims abstract description 300
- 238000013507 mapping Methods 0.000 title claims abstract description 85
- 238000007726 management method Methods 0.000 title claims abstract description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 46
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Abstract
The invention discloses the original document mappings for being applied to clinical testing data, management method and its system, pass through the mapping relations established between the structuring test data and the original document, corresponding original document can be transferred automatically according to mapping relations when obtaining structuring test data, when subsequent discovery data go wrong or clinical supervisor queries data, corresponding original document can be shown automatically, to which the risk searched the time of original document and original document loss can be effectively reduced be greatly saved, ensure the progress of clinical test.
Description
Technical Field
The invention relates to the field of clinical experiment data acquisition, in particular to a method and a system for mapping and managing an original file applied to clinical experiment data.
Background
Clinical trials refer to any systematic study of drugs in humans to confirm or reveal the effects, adverse effects and/or absorption, distribution, metabolism and excretion of experimental drugs in order to determine the efficacy and safety of experimental drugs. The clinical test is an important link for saving time and cost in the research and development of new drugs, the experimental structure in the clinical test is processed in the past by the following way, for paper-based clinical test data, such as laboratory sheet results and the like, a research nurse hand (CRC) copies and records the paper-based clinical test data into a case report form CRF (the case report form refers to a file specified and designed by a clinical test scheme and used for recording data of each subject in the test process), and then the case report form is sent to a data management center and is manually recorded into a data management system by a data logger. For EDC mode clinical trial data management, it was entered directly into the electronic clinical trial management system by the researcher. Wherein, electronic clinical data management system (EDC): that is, paperless clinical data management, researchers fill clinical trials directly in an electronic clinical data management system. The use of EDC improves the accuracy of data acquisition, shortens the time of data acquisition and management, and enhances the monitoring of the progress of the research project by the sponsor. In order to accelerate the development of clinical research of new drugs, paper-based clinical trial data management has been abandoned fundamentally abroad. At least 90% of clinical trial data management currently uses the EDC mode.
As can be seen, at present, for the collection of the original files of clinical experiment numbers, the data is generally manually copied into a case report form CRF by a research nurse CRC and then input into a data management system by an entry clerk. At this time, the accurate case report table CRF copied by the CRC of the research nurse and the correct input of the input member must be ensured, and since the clinical test takes a long time, when the input data is found to be problematic in the later stage, the original document of the test document needs to be found and checked, so that the original document must be completely and clearly stored, otherwise, the original document cannot be found or a large amount of time is spent on finding, and the progress of the clinical test is greatly influenced in the aspects of data acquisition and data monitoring.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide an original document mapping and managing method and system applied to clinical trial data, which can quickly refer to an original document of a clinical trial.
The technical scheme adopted by the invention for solving the problems is as follows:
the original file mapping and managing method applied to clinical test data comprises the following steps:
acquiring structured test data and an original file corresponding to the structured test data;
establishing a mapping relation between the structured test data and the original file;
storing the structured test data, the original file, the mapping relation between the structured test data and the original file in a clinical test data management system;
acquiring structured test data from a clinical test data management system;
and calling the corresponding original file according to the mapping relation between the current structured test data and the original file.
Further, the structured test data comprises a plurality of structured test parameters, and each structured test parameter establishes a mapping relation with an original file corresponding to the structured test data;
obtaining structured test data from a clinical test data management system includes: acquiring one structured test parameter in the structured test data;
the method for calling the corresponding original file according to the mapping relation between the current structured test data and the original file comprises the following steps: and calling the corresponding original file according to the mapping relation between the structured test parameters and the corresponding original file.
Further, still include:
and marking an original parameter position mark corresponding to the structural test parameter on the called original file according to the current structural test parameter.
Specifically, original parameter position marks corresponding to the structured test parameters are marked on the called original files through an artificial intelligence automatic learning algorithm.
Further, still include:
acquiring corrected original parameter position mark information of a user;
and taking the corrected original parameter position mark information as a self-learning parameter in an artificial intelligent automatic learning algorithm.
Further, still include:
calling a test item data collection form structure template;
acquiring structured patient information under the test item data collection form structure template;
associating the structured trial data with structured patient information;
storing the structured patient information in a clinical trial data management system;
obtaining corresponding structured test data based on the structured patient information, or,
and acquiring corresponding structured patient information according to the structured test data.
Further, the structured test data is obtained by converting an original file, and comprises:
extracting structural information in an original file to directly generate structural test data;
or,
the structured information in the original file forms structured test data through structured recognition;
or,
and inputting structured test data according to the content in the original file.
Specifically, the structured recognition is image recognition.
Further, the original file is obtained by photographing or uploading through a mobile phone.
Further, the step of forming the structured test data by the structured identification of the structured information in the original file comprises:
acquiring an original file;
and identifying the structured test data in the original file through an artificial intelligence automatic learning algorithm intelligent image.
Further, still include:
acquiring correction structured test data input by a user;
and taking the corrected structured test data as a self-learning parameter in an artificial intelligent automatic learning algorithm.
The original file mapping and managing system applied to clinical test data comprises:
the data acquisition module is used for acquiring the structured test data and the original file corresponding to the structured test data;
the mapping generation module is used for establishing a mapping relation between the structured test data and the original file;
the data storage module is used for storing the structural test data, the original file, the structural test data and the mapping relation between the structural test data and the original file in a clinical test data management system;
the data extraction module is used for acquiring structured test data from the clinical test data management system;
and the data calling module is used for calling the corresponding original file according to the mapping relation between the current structured test data and the original file.
In the data acquisition module, the structured test data comprise a plurality of structured test parameters, and in the mapping generation module, each structured test parameter establishes a mapping relation with an original file corresponding to the structured test data;
the data extraction module is used for acquiring one structured test parameter in the structured test data;
and in the data calling module, calling the corresponding original file according to the mapping relation between the structured test parameters and the corresponding original file.
Further, still include:
and the original parameter position marking module marks an original parameter position mark corresponding to the structural test parameter on the called original file according to the current structural test parameter.
Specifically, original parameter position marks corresponding to the structured test parameters are marked on the called original files through an artificial intelligence automatic learning algorithm.
Further, still include:
the correction marking module is used for acquiring the mark information of the corrected original parameter position of the user;
and the mark self-learning module is used as a self-learning parameter in the artificial intelligent automatic learning algorithm according to the corrected original parameter position mark information.
Further, still include:
the template calling module is used for calling a test project data collection form structure template;
the patient information acquisition module is used for acquiring the structured patient information under the test item data collection form structure template;
a patient information association module that associates the structured trial data with structured patient information;
a patient information storage module that stores the structured patient information in a clinical trial data management system;
and the patient information extraction module is used for acquiring corresponding structured test data according to the structured patient information.
Further, the structured test data is obtained by converting an original file, and comprises:
the original file extraction module is used for extracting the structured information in the original file to directly generate structured test data;
or,
the structured identification module is used for forming structured test data by structured identification of the structured information in the original file;
or,
and the structured data input module is used for inputting structured test data according to the content in the original file.
Specifically, the structured recognition is image recognition.
Preferably, the original file is obtained by taking a picture or uploading through a mobile phone.
Further, the structured recognition module comprises:
the original file acquisition module acquires an original file;
and the original file identification module is used for identifying the structured test data in the original file through an artificial intelligence automatic learning algorithm intelligent image.
Further, still include:
the correction structured test data acquisition module is used for acquiring correction structured test data input by a user;
and the image recognition self-learning module is used for taking the corrected structured test data as self-learning parameters in an artificial intelligent automatic learning algorithm.
The original file mapping and managing device applied to clinical test data comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the original file mapping, management method as described above.
A computer-readable storage medium storing computer-executable instructions for causing a computer to perform the original file mapping, managing method as described above.
The invention has the beneficial effects that: according to the original file mapping and managing method and system applied to clinical test data, the mapping relation between the structured test data and the original file is established, the corresponding original file can be automatically called according to the mapping relation when the structured test data is obtained, and the corresponding original file can be automatically displayed when the data is found to be in problem or a clinical inspector asks for the data, so that the time for searching the original file is greatly saved, the risk of losing the original file can be effectively reduced, and the progress of clinical tests is ensured.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a method flow diagram of the original file mapping and management method of the present invention;
FIG. 2 is a system schematic of the clinical trial system of the present invention;
FIG. 3 is a flowchart of another method of the original file mapping and management method of the present invention;
FIG. 4 is a diagram of an original file mapping and managing apparatus according to the present invention.
Detailed Description
Referring to fig. 1, the method for mapping and managing an original file applied to clinical trial data of the present invention includes:
101. acquiring structured test data and an original file corresponding to the structured test data, wherein the structured test data refers to clearly-expressed and unified character format data, such as a project code number and a project name of each test project of a test list and a corresponding test result numerical value;
102. establishing a mapping relation between the structured test data and the original files, so that the current structured test data corresponds to at least one original file;
103. storing the structured test data, the original file, the mapping relation between the structured test data and the original file in a clinical test data management system;
104. acquiring structured test data from a clinical test data management system;
105. calling a corresponding original file according to a mapping relation between the current structured test data and the original file;
that is, when the user consults or counts the structured test data in the clinical test data management system, the corresponding original file is found through the mapping relation of the corresponding original file. The original file can be automatically called when the structured test data is obtained, or the original file can be found out through a mapping relation after a command for obtaining the original file is sent out.
Further, the structured test data comprises a plurality of structured test parameters, each structured test parameter establishes a mapping relation with the original file corresponding to the structured test data,
obtaining structured test data from a clinical test data management system includes: acquiring one structured test parameter in the structured test data;
the method for calling the corresponding original file according to the mapping relation between the current structured test data and the original file comprises the following steps: and calling the corresponding original file according to the mapping relation between the structured test parameters and the corresponding original file.
Taking a laboratory test report as an example, the laboratory test report comprises a plurality of items and test numerical results corresponding to the items, the laboratory test report is the structured test data, the specific items of the laboratory test report and the test results thereof are a structured test parameter, when the data is saved, each structured test parameter is stored as a unit so as to perform statistical analysis on sample data of a plurality of patients, and each structured test parameter of the laboratory test report corresponds to an original file of the laboratory test report to establish a mapping relation, such as a picture of the laboratory test report. When the researcher counts data, each specific structured test parameter can be checked independently, or the structured test parameters can be selected from a screened statistical data list, and the researcher can call the original file mapped with each structured test parameter, for example, can see the laboratory sheet original image corresponding to each specific test result.
Besides the test picture list, the original file can be in various data formats, such as txt, doc, pdf and other conventional documents, and can also be in a professional medical document format.
Further, after the corresponding original file is called according to the mapping relation between the structured test parameters and the corresponding original file, the method further comprises the following steps:
and marking an original parameter position mark corresponding to the structural test parameter on the called original file according to the current structural test parameter. By marking the positions of the original parameters on the original file, researchers can conveniently and quickly position the positions of the original parameters corresponding to the structured test parameters, and the searching efficiency is improved. For example, as described above for the laboratory test report picture, after a researcher calls the original file mapped to the laboratory test report picture through the structured test parameters, the positions of the original parameters corresponding to the structured test parameters on the original file are marked on the original file, for example, the corresponding parts in the laboratory test report picture corresponding to a certain test parameter are highlighted, labeled or framed, so that the researcher can quickly check the relevant parts of the original file, and the work efficiency is greatly improved.
Specifically, original parameter position marks corresponding to the structured test parameters can be marked on the called original file through an artificial intelligence automatic learning algorithm. The artificial intelligent automatic learning algorithm can adopt a neural network algorithm or a random forest algorithm, the prior art is adopted, a specific algorithm formula is not repeated, the neural network algorithm is taken as an example, a sample set and a test set are constructed by using a large number of structured test parameters and original files which determine corresponding marking positions, the neural network algorithm is used for self-learning, the test set is used for testing to judge whether the self-learned algorithm can pass the test, and if the self-learned algorithm cannot pass the test, the learning is continued until the test set can be accurately identified. At this time, the position of the original parameter corresponding to the structured test parameter in the original file can be obtained only by inputting the structured test parameter and the corresponding original file, and the position is marked.
Further, in order to continuously perfect the artificial intelligent automatic learning algorithm in the using process, the method also comprises the following steps:
acquiring corrected original parameter position mark information of a user;
and taking the corrected original parameter position mark information as a self-learning parameter in an artificial intelligent automatic learning algorithm.
When finding that the initial parameter position mark is inconsistent with the structured test parameter, the user can immediately correct the initial parameter position mark, and the corrected initial parameter position mark information of the user is obtained and is used as a new test set or a sample set to be added into the artificial intelligent automatic learning algorithm, so that the recognition capability of the artificial intelligent automatic learning algorithm can be improved. For example, currently, the mark is implemented by framing, and when the user finds that the mark position is incorrect, the user only needs to drag the mark frame to the correct position, so as to generate the mark information of the corrected original parameter position.
Further, in addition to acquiring structured test data, the present disclosure also collects and manages patient information by:
calling a test item data collection form structure template; the structure template is set according to the requirement of the current test task, generally consistent with the item setting of a case report table CRF, and the required test items are embodied by the structure template, so that the corresponding items are more convenient to select.
Acquiring structured patient information under the test item data collection form structure template; the patient information is pre-stored in a test item data collection form structure template, the structured patient information can be selected only by calling the test item data collection form structure template of a corresponding item, the structuring of the patient information is formed by online desensitization after CRC registration and acquisition of a research nurse, the desensitization refers to that information such as the name, the address, the telephone and the like of a patient are removed so that the patient cannot be identified, the online desensitization refers to that the research nurse CRC registers real patient information, and the system automatically deletes or hides relevant sensitive information in the patient information to realize desensitization.
Thus, the patient information is structured when the test item data collection form structure template is created, and the structuring operation does not need to be repeated in the test process.
Associating the structured trial data with structured patient information; specifically, after the corresponding structured patient information is selected, the structured test data is input or imported, and the association between the structured patient information and the structured test data can be realized.
Storing the structured patient information in a clinical trial data management system.
Acquiring corresponding structured test data according to the structured patient information, namely acquiring all structured test data of the patient by inquiring the structured patient information, inquiring an original file corresponding to each structured test data, and finding a corresponding original file according to the structured test parameters;
similarly, through the structured test data, the corresponding structured patient information may also be obtained, for example, when counting that a certain parameter is abnormal, a researcher may obtain the patient information of the parameter in addition to the original file of the parameter, and then check and verify other structured test data of the patient.
Further, the structured test data is obtained by converting an original file, including,
extracting the structured information in the original file to directly generate structured test data, for example, the original file is an excel document, and each item of character data in the excel can be directly extracted to produce the structured test data.
In another mode, the structured information in the original file forms structured test data through structured recognition; for example, the original file is picture data: the two-dimensional table type laboratory test report can identify each inspection item and the corresponding inspection result in the laboratory test report by dividing the image data by the two-dimensional table in an image identification mode and automatically form structured data, such as a certain inspection item and the corresponding inspection result.
Alternatively, structured test data is entered based on the content in the original document. For an original file (for example, partial information in a large text such as a large case) which cannot be identified by structuring, relevant information can be extracted and input into the structured test data after the research nurse CRC reads the file, and the research nurse CRC can also input the file into a clinical test data management system after uploading the original file.
Further, the step of forming the structured test data by the structured identification of the structured information in the original file comprises:
acquiring an original file;
and identifying the structured test data in the original file through an artificial intelligence automatic learning algorithm intelligent image. The structured test data in the original file can be quickly and accurately identified through the automatic learning algorithm intelligent image identification.
The artificial intelligent automatic learning algorithm can adopt a neural network algorithm or a random forest algorithm, the prior art is adopted, a specific algorithm formula is not repeated, the neural network algorithm is taken as an example, a sample set and a test set are constructed by using a large number of original files and well-determined corresponding structured test data, self-learning is carried out through the neural network algorithm, testing is carried out through the test set, whether the algorithm after self-learning can pass the test or not is judged, and if not, learning is continued until the test set can be accurately identified. At the moment, structured test data can be obtained only by inputting an original file.
Further, in order to continuously perfect the artificial intelligent automatic learning algorithm in the using process, the method also comprises the following steps:
acquiring correction structured test data input by a user;
and taking the corrected structured test data as a self-learning parameter in an artificial intelligent automatic learning algorithm.
When finding that the structured test data identified by the image do not accord with the original file, the user can immediately correct the original file, correct structured test data is input, and the correct structured test data input by the user is obtained and is used as a new test set or a sample set to be added into the artificial intelligent automatic learning algorithm, so that the image identification capability of the artificial intelligent automatic learning algorithm can be improved.
Specifically, a test item data collection form structure template is called through the mobile terminal, structured patient information under the test item data collection form structure template is obtained through operation, an original file is photographed and uploaded, and the original file is converted into structured test data and then is associated with the structured patient information.
Further, the clinical trial data management system further comprises an EDC system, and the structured patient information, the structured trial data, the raw file and the mapping relationship thereof are stored in the EDC system.
An original file mapping and managing system for clinical test data corresponding to the original file mapping and managing method for clinical test data, comprising:
the data acquisition module is used for acquiring the structured test data and the original file corresponding to the structured test data;
the mapping generation module is used for establishing a mapping relation between the structured test data and the original file;
the data storage module is used for storing the structural test data, the original file, the structural test data and the mapping relation between the structural test data and the original file in a clinical test data management system;
the data extraction module is used for acquiring structured test data from the clinical test data management system;
and the data calling module is used for calling the corresponding original file according to the mapping relation between the current structured test data and the original file.
Further, still include:
and the original parameter position marking module marks an original parameter position mark corresponding to the structural test parameter on the called original file according to the current structural test parameter.
Specifically, original parameter position marks corresponding to the structured test parameters are marked on the called original files through an artificial intelligence automatic learning algorithm.
Further, still include:
the correction marking module is used for acquiring the mark information of the corrected original parameter position of the user;
and the mark self-learning module is used as a self-learning parameter in the artificial intelligent automatic learning algorithm according to the corrected original parameter position mark information.
In the data acquisition module, the structured test data comprise a plurality of structured test parameters, and in the mapping generation module, each structured test parameter establishes a mapping relation with an original file corresponding to the structured test data;
the data extraction module is used for acquiring one structured test parameter in the structured test data;
and in the data calling module, calling the corresponding original file according to the mapping relation between the structured test parameters and the corresponding original file.
Further, still include:
the template calling module is used for calling a test project data collection form structure template;
the patient information acquisition module is used for acquiring the structured patient information under the test item data collection form structure template;
a patient information association module that associates the structured trial data with structured patient information;
a patient information storage module that stores the structured patient information in a clinical trial data management system;
and the patient information extraction module is used for acquiring corresponding structured test data according to the structured patient information.
Further, the structured test data is obtained by converting an original file, and comprises:
the original file extraction module is used for extracting the structured information in the original file to directly generate structured test data;
or,
the structured identification module is used for forming structured test data by structured identification of the structured information in the original file;
or,
and the structured data input module is used for inputting structured test data according to the content in the original file.
Specifically, the structured recognition is image recognition.
Preferably, the original file is obtained by taking a picture or uploading through a mobile phone.
Further, the structured recognition module comprises:
the original file acquisition module acquires an original file;
and the original file identification module is used for identifying the structured test data in the original file through an artificial intelligence automatic learning algorithm intelligent image.
Further, still include:
the correction structured test data acquisition module is used for acquiring correction structured test data input by a user;
and the image recognition self-learning module is used for taking the corrected structured test data as self-learning parameters in an artificial intelligent automatic learning algorithm.
Referring to fig. 2, a system schematic diagram of the clinical trial system of the present invention is shown, and the following description is made in conjunction with the system and the flow of clinical trials.
The clinical test system comprises a clinical test data management system and a mobile terminal, the clinical test data management system comprises a data management module, a data warehouse and an EDC system, the data management module comprises a data input end for the research nurse to input CRC data, the mobile terminal is connected with the data management module through the data input end, the data management module comprises a structured data output connected to a data warehouse, the data warehouse interfaces the structured data to the EDC system, the data management module further includes an unstructured data output from which an entry clerk retrieves the unstructured data and identifies corresponding structured data for output to the EDC system, the EDD system is connected with the data management module, and researchers can acquire and call related information in the EDC system through the data management module.
The method comprises project management, data acquisition, data management and data analysis of clinical research projects according to a clinical research scheme. The research nurse CRC assists doctors in work to assist doctors to sign informed consent with patients who enter a group, screening the patients according to whether the informed consent accords with the admission and discharge standard, if so, the research nurse CRC is required to collect the information of patients (the name, address, telephone and the like of the patients are removed or the information is not identified) after the patients are desensitized online according to the scheme, and the data is uploaded and managed through a mobile terminal, and the method specifically comprises the following steps:
201. calling a test item data collection form structure template; for example, a CRC nurse selects a clinical trial item, such as selecting an item name.
202. Acquiring structured patient information under the test item data collection form structure template; for example, after a clinical test item is selected by the CRC of a research nurse, the hospital to be tested and the patient number information under the hospital are selected, and the patient is believed to be desensitized and then stored in the structural template of the test item data collection form, so the CRC of the research nurse is not required to be re-entered, and the corresponding structured patient information can be selected only by selection.
203. Uploading an original file, and converting the original file into structured test data; for example, the original file is an excel document, and structured test data can be directly extracted and produced from each item of character data in the excel; for example, the original file is picture data, each inspection item in the laboratory sheet and the corresponding inspection result are identified by dividing the picture data by a two-dimensional table in an image identification mode, and structured data are automatically formed; if the data is the data which can not be structured, the data is saved and is input into a clinical test data management system by a research nurse CRC or an input member.
204. Associating the structured test data with the structured patient information, and establishing a mapping relation between the structured test data and the original files to enable the current structured test data to correspond to at least one original file; if the structured test data comprises a plurality of structured test parameters, the plurality of structured test parameters respectively establish a mapping relation with the original file.
205. And storing the structured patient information, the structured test data, the original file and the mapping relation between the structured test data and the original file into a clinical test data management system.
206. Acquiring structured test data from a clinical test data management system; researchers can obtain the required structured test data from the clinical test data management system to research, check or statistically analyze. For example, when a researcher screens and counts a certain structured test parameter of all male patients, corresponding structured data is extracted from the EDC system and displayed.
207. Calling a corresponding original file according to a mapping relation between the current structured test data and the original file; for example, when the researcher has a question about the structured test parameters of a certain patient, the researcher can click the structured test parameters and display the corresponding original document (original laboratory sheet) according to the mapping relationship for checking and research.
208. Marking original parameter position marks corresponding to the structured test parameters on the called original files according to the structured test parameters in the current structured test data by using an artificial intelligence automatic learning algorithm; for example, after a researcher calls an original file mapped with the original file through the structured test parameters, the positions of the original parameters corresponding to the structured test parameters on the original file are marked on the original file, for example, corresponding parts in a laboratory sheet picture corresponding to a certain test parameter are highlighted, marked or framed to be displayed, so that the researcher can quickly check the relevant parts of the original file, and the working efficiency is greatly improved.
209. Acquiring corrected original parameter position mark information of a user; for example, currently, the mark is implemented by framing, and when the user finds that the mark position is incorrect, the user only needs to drag the mark frame to the correct position, so as to generate the mark information of the corrected original parameter position.
210. Taking the corrected original parameter position mark information as a self-learning parameter in an artificial intelligent automatic learning algorithm; for example, the corrected original parameter position mark information of the user is obtained and used as a new test set or a sample set to be added into the artificial intelligence automatic learning algorithm, so that the recognition capability of the artificial intelligence automatic learning algorithm can be improved.
Referring to fig. 4, the original file mapping and managing apparatus applied to clinical trial data according to the present invention includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the original file mapping, management method as described above.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the original file mapping and management method in the embodiments of the present invention. The processor executes various functional applications and data processing of the stereo imaging processing device by running non-transitory software programs, instructions and modules stored in the memory, namely, the original file mapping and management method of any one of the above method embodiments is realized.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the stereoscopic imaging processing device, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located from the processor, and the remote memory may be connected to the stereoscopic projection device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory and, when executed by the one or more processors, perform the original file mapping, management method in any of the above-described method embodiments, e.g., performing method steps 101 to 105 in fig. 1 and method steps 201 to 210 in fig. 3 described above.
A computer-readable storage medium storing computer-executable instructions for execution by one or more processors, e.g., one of the processors in fig. 4, to cause the one or more processors to perform the original file mapping and management method in any of the method embodiments described above, e.g., to perform method steps 101 to 105 in fig. 1 and method steps 201 to 210 in fig. 3 described above.
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.
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 general hardware platform, and certainly can also be implemented by hardware. It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a computer readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiment, and the present invention shall fall within the protection scope of the present invention as long as the technical effects of the present invention are achieved by the same means.
Claims (13)
1. The original file mapping and managing method applied to clinical test data is characterized by comprising the following steps of:
acquiring structured test data and an original file corresponding to the structured test data;
establishing a mapping relation between the structured test data and the original file;
storing the structured test data, the original file, the mapping relation between the structured test data and the original file in a clinical test data management system;
acquiring structured test data from a clinical test data management system;
and calling the corresponding original file according to the mapping relation between the current structured test data and the original file.
2. The original file mapping and management method applied to clinical trial data as claimed in claim 1,
the structured test data comprises a plurality of structured test parameters, and each structured test parameter establishes a mapping relation with an original file corresponding to the structured test data;
obtaining structured test data from a clinical test data management system includes: acquiring one structured test parameter in the structured test data;
the method for calling the corresponding original file according to the mapping relation between the current structured test data and the original file comprises the following steps: and calling the corresponding original file according to the mapping relation between the structured test parameters and the corresponding original file.
3. The method for original file mapping, management applied to clinical trial data as set forth in claim 2, further comprising,
and marking an original parameter position mark corresponding to the structural test parameter on the called original file according to the current structural test parameter.
4. The method for original file mapping and management applied to clinical trial data as claimed in claim 3, wherein: and marking original parameter position marks corresponding to the structured test parameters on the called original files through an artificial intelligence automatic learning algorithm.
5. The method for original file mapping and management applied to clinical trial data as claimed in claim 4, further comprising:
acquiring corrected original parameter position mark information of a user;
and taking the corrected original parameter position mark information as a self-learning parameter in an artificial intelligent automatic learning algorithm.
6. The method for original file mapping and management applied to clinical trial data as set forth in claim 1, further comprising:
calling a test item data collection form structure template;
acquiring structured patient information under the test item data collection form structure template;
associating the structured trial data with structured patient information;
storing the structured patient information in a clinical trial data management system;
obtaining corresponding structured test data based on the structured patient information, or,
and acquiring corresponding structured patient information according to the structured test data.
7. The original file mapping and managing method applied to clinical trial data according to any one of claims 1 to 3,
the structured test data is obtained by converting an original file and comprises the following steps:
extracting structural information in an original file to directly generate structural test data;
or,
the structured information in the original file forms structured test data through structured recognition;
or,
and inputting structured test data according to the content in the original file.
8. The method for original file mapping and management applied to clinical trial data as claimed in claim 4, wherein: the structured recognition is image recognition.
9. The method for mapping and managing original documents applied to clinical trial data as claimed in claim 7, wherein the step of forming structured trial data by structured recognition of the structured information in the original documents comprises:
acquiring an original file;
and identifying the structured test data in the original file through an artificial intelligence automatic learning algorithm intelligent image.
10. The method for original file mapping and management applied to clinical trial data as claimed in claim 9, further comprising:
acquiring correction structured test data input by a user;
and taking the corrected structured test data as a self-learning parameter in an artificial intelligent automatic learning algorithm.
11. The original file mapping and managing system applied to clinical test data is characterized by comprising the following components:
the data acquisition module is used for acquiring the structured test data and the original file corresponding to the structured test data;
the mapping generation module is used for establishing a mapping relation between the structured test data and the original file;
the data storage module is used for storing the structural test data, the original file, the structural test data and the mapping relation between the structural test data and the original file in a clinical test data management system;
the data extraction module is used for acquiring structured test data from the clinical test data management system;
and the data calling module is used for calling the corresponding original file according to the mapping relation between the current structured test data and the original file.
12. The original file mapping and managing device applied to clinical test data is characterized by comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-10.
13. A computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform the method of any one of claims 1-10.
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