WO2021184571A1 - 动态表单生成方法、装置、计算机设备和存储介质 - Google Patents

动态表单生成方法、装置、计算机设备和存储介质 Download PDF

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Publication number
WO2021184571A1
WO2021184571A1 PCT/CN2020/098671 CN2020098671W WO2021184571A1 WO 2021184571 A1 WO2021184571 A1 WO 2021184571A1 CN 2020098671 W CN2020098671 W CN 2020098671W WO 2021184571 A1 WO2021184571 A1 WO 2021184571A1
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field
target
diagnosis
data
treatment
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PCT/CN2020/098671
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English (en)
French (fr)
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吴宗霖
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平安国际智慧城市科技股份有限公司
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2282—Tablespace storage structures; Management thereof

Definitions

  • This application relates to the field of computer technology, in particular to a dynamic form generation method, device, computer equipment and storage medium.
  • the CRF (Case Report Form) form refers to a document designed according to the test protocol, used to record the data of each subject during the test.
  • the way to enter data is usually to fill in the data from the form interface displayed by the web system or directly from the EXCLE file in the preset format. Importing data in the CRF form is not flexible enough.
  • a dynamic form generation method, device, computer equipment, and storage medium are provided.
  • a dynamic form generation method includes:
  • a dynamic form generating device includes:
  • An obtaining module configured to obtain dynamically configured field configuration information, extract a target field from the field configuration information, and generate a corresponding target form, the target form including the target field;
  • the dynamic data determination module is used to extract the diagnosis and treatment phase associated fields associated with the diagnosis and treatment phase from the target field, obtain the dynamic field value corresponding to the diagnosis and treatment phase associated field, and determine the current corresponding to the target form according to the dynamic field value.
  • the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage are selected from the user's diagnosis and treatment data as candidate sub-diagnosis and treatment data, and the text matching degree between the diagnosis and treatment stage associated fields and the candidate sub-diagnosis and treatment data is calculated, according to the The text matching degree is selected from the candidate sub-diagnosis and treatment data to obtain the target sub-diagnosis and treatment data; and
  • the first form import module is used to calculate the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target form field of the target form, and to identify the target sub-diagnosis and treatment data from the target sub-diagnosis and treatment data according to the field matching degree
  • the target keyword that matches the target form field is generated, the corresponding target import information is obtained from the target sub-diagnosis and treatment data according to the location of the target keyword, and the target import information is imported into the matching target form field as the field value of the target form field.
  • Target form is used to calculate the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target form field of the target form, and to identify the target sub-diagnosis and treatment data from the target sub-diagnosis and treatment data according to the field matching degree
  • the target keyword that matches the target form field is generated, the corresponding target import information is obtained from the target sub-diagnosis and treatment data according to the location of the target keyword, and the target import information is imported into the matching target form field as
  • a computer device including a memory and one or more processors, the memory stores computer readable instructions, and when the computer readable instructions are executed by the processor, the one or more processors execute The following steps:
  • One or more computer-readable storage media storing computer-readable instructions.
  • the one or more processors perform the following steps:
  • Fig. 1 is an application environment diagram of a dynamic form generation method according to one or more embodiments
  • FIG. 2 is a schematic flowchart of a method for generating a dynamic form according to one or more embodiments
  • Fig. 3 is a structural block diagram of a dynamic form generating device according to one or more embodiments.
  • Figure 4 is a diagram of the internal structure of a computer device according to one or more embodiments.
  • Fig. 5 is a diagram of the internal structure of a computer device in another embodiment.
  • FIG. 1 is a diagram of an application environment in which the dynamic form generation method runs in an embodiment.
  • the application environment includes a terminal 110 and a server 120.
  • the terminal and the server communicate through the network.
  • the communication network may be a wireless or wired communication network, such as an IP network, a cellular mobile communication network, etc., where the number of terminals and servers is not limited.
  • the terminal 110 may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices.
  • the server can be implemented as an independent server or a server cluster composed of multiple servers.
  • the dynamic form generation method can be applied to the terminal or the server.
  • the dynamically configured field configuration information can be obtained from the terminal, and the form processing request carrying the field configuration information can be sent to the server.
  • the server determines the target form field according to the field configuration information, and obtains the current diagnosis and treatment data corresponding to the target form
  • the field value of the matched target form field is adaptively determined and imported into the target form.
  • a dynamic form generation method is provided. Taking the method applied to the terminal 110 or the server 120 in FIG. 1 as an example for description, the method includes the following steps:
  • Step 210 Acquire dynamically configured field configuration information, extract the target field from the field configuration information, and generate a corresponding target form, the target form including the target field.
  • the dynamically configured field configuration information can be the configuration information generated by the user according to the field configuration operation in real time, or it can be the pre-stored configuration information after the user generates the configuration information through the historical field configuration operation, and is used to perform the field configuration of the form.
  • Dynamic configuration The field configuration can be completed by selecting the candidate field in the visual configuration interface to generate field configuration information. It is also possible to determine the target field configuration library through the selection operation of the field configuration library, so that the fields that originally exist in the target field configuration library are adaptively mapped to complete the field configuration operation, and the corresponding field configuration information is generated. Among them, the field configuration library saves the data related to the field.
  • the fields that originally existed in the field configuration library can be obtained through analysis and extraction. For example, according to the type of the disease library field, it is automatically mapped to the corresponding fill-in-the-blank question, single-choice and other types. Get the target field.
  • the field configuration information can also be obtained through voice entry, the recognized voice is converted into text, and the recognized text is used as the target form field of the form.
  • the form field type can support fill-in-the-blank, single-choice, multiple-choice, time and other formats, which can be customized by the user or automatically mapped from the original field type corresponding to the field that originally exists in the target field configuration library.
  • Step 220 Extract the diagnosis and treatment phase associated field associated with the diagnosis and treatment phase from the target field, obtain the dynamic field value corresponding to the diagnosis and treatment phase associated field, and determine the current diagnosis and treatment phase corresponding to the target form according to the dynamic field value.
  • the diagnosis and treatment phase associated field refers to a field used to determine the diagnosis and treatment phase corresponding to the target form, and may be an attribute field of the target form, or one or more preset fields related to the diagnosis and treatment phase in the target form.
  • the diagnosis and treatment stage associated field associated with the diagnosis and treatment stage can be extracted from the preset position or from the target field by comparing the preset character string.
  • the dynamic field value is the field value corresponding to the associated field in the diagnosis and treatment stage that is input by the user's input operation. As the user's diagnosis and treatment time and number of times change, the dynamic field value corresponding to the associated field in the diagnosis and treatment stage also dynamically changes.
  • the dynamic field values corresponding to the associated fields of the diagnosis and treatment stage include different types of dynamic information, including the real-time diagnosis and treatment time, diagnosis and treatment user name, diagnosis and treatment times, and form number, etc.
  • the current diagnosis and treatment corresponding to the target form is determined based on the filled information For the stage, if the number of times of diagnosis and treatment is less than 5 times, it corresponds to the first diagnosis and treatment stage, and if the number of times is more than 5 times and less than 10 times, it corresponds to the second diagnosis and treatment stage.
  • the relationship between the form number and the diagnosis and treatment stage can be a pre-established relationship. For example, there is a corresponding relationship between the order of the form number from small to large and the diagnosis and treatment stages in the order of time. For example, form 1 corresponds to the first diagnosis and treatment stage, and form 2 Corresponds to the second stage of diagnosis and treatment.
  • Step 230 Filter the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user's diagnosis and treatment data as candidate sub-diagnosis and treatment data; calculate the text matching degree between the diagnosis and treatment stage related fields and the candidate sub-diagnosis and treatment data, and filter the candidate sub-diagnosis and treatment data according to the text matching degree.
  • Target sub-diagnosis and treatment data Filter the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user's diagnosis and treatment data as candidate sub-diagnosis and treatment data.
  • the current diagnosis and treatment stage is used to determine which diagnosis and treatment stage the target form belongs to. If the current diagnosis and treatment stage is the first diagnosis and treatment stage, the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage can be filtered according to the diagnosis and treatment stage to which each sub-diagnosis and treatment data belongs as candidate sub-diagnosis and treatment data .
  • Sub-diagnosis and treatment data refers to data generated at different stages in the diagnosis and treatment process.
  • a follow-up record can be one sub-diagnosis and treatment data, and the sub-diagnosis and treatment data includes at least one follow-up record.
  • diagnosis and treatment can be divided into different stages, and the diagnosis and treatment information of each stage is different, and the diagnosis and treatment information of each different stage can be recorded through follow-up of the user.
  • the user diagnosis and treatment data can include user follow-up records at different stages, and the forms for each stage of the diagnosis and treatment can be independent. Therefore, when importing data into the form, first determine the current diagnosis and treatment stage corresponding to the form, and then obtain the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage as the candidate sub-diagnosis and treatment data, and then from the candidate sub-diagnosis and treatment data according to the diagnosis and treatment stage related fields and the candidate sub-diagnosis and treatment data The text matching degree of to obtain the target sub-diagnosis and treatment data.
  • the diagnosis and treatment phase associated fields of the target form can be text-matched with the diagnosis and treatment fields of each follow-up record in the candidate sub-diagnosis and treatment data, and the follow-up records whose matching degree exceeds a preset threshold are used as the target sub-diagnosis and treatment data. If the diagnosis and treatment phase related fields of the target form include hypertension value, blood routine 5 items, and urine routine fields, keywords are extracted from different follow-up records and matched with the diagnosis and treatment phase related fields in the target form, the follow-up with the highest matching degree Record as the target sub-diagnosis and treatment data.
  • Step 240 Calculate the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target form field of the target form, and identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree.
  • the location of the keyword obtains the corresponding target import information from the target sub-diagnosis and treatment data, and imports the target import information into the target form as the field value of the matched target form field.
  • keyword extraction is performed on the target sub-diagnosis and treatment data, the extracted keywords are matched with the target form field, and the adjacent text corresponding to the successfully matched keyword is semantically analyzed to obtain the field value corresponding to the target form field.
  • the field value is automatically imported to the position of the corresponding field in the target form, which realizes the automatic filling of form data, which is convenient and efficient.
  • the target form includes target fields, and the diagnosis and treatment phase associations associated with the diagnosis and treatment phases are extracted from the target fields.
  • Field obtain the dynamic field value corresponding to the associated field of the diagnosis and treatment stage, determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value, filter the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user's diagnosis and treatment data as candidate sub-diagnosis and treatment data; calculate the diagnosis and treatment stage
  • the text matching degree between the associated field and the candidate sub-diagnosis and treatment data, and the target sub-diagnosis and treatment data are filtered from the candidate sub-diagnosis and treatment data according to the text matching degree; the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target form field of the target form is calculated Identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree
  • the fields of the form can be customized by the user.
  • Obtain the dynamic field value corresponding to the associated field of the diagnosis and treatment stage thereby determine the corresponding current diagnosis and treatment stage according to the dynamic field value, and then filter the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage, and combine the target sub-diagnosis and treatment data in the target sub-diagnosis and treatment data
  • the target import information is imported into the target form as the field value of the matching form field.
  • Different dynamic field values can determine different current diagnosis and treatment stages, realize different stages of disease types, design different forms, and collect data on different stages of diseases. Directly import to the form, realize the dynamic and efficient of importing form data, and match with the different stages of the disease, which improves the flexibility and diversity of form generation.
  • the method further includes: obtaining a query string, the query string includes a custom query expression, the query expression includes at least one query unit, and the query unit includes a conditional statement and a field statement; corresponding to the query string Get the query result set corresponding to the query string in the database, configure the matching item ID for the query result set, get the item form corresponding to the item ID; calculate the distance between each keyword in the query result set and the item form field of the corresponding item form According to the item field matching degree, the result set keywords matching the item form fields are identified from the query result set according to the item field matching degree, and the corresponding target import data is obtained from the query result set according to the position of the result set keywords, and the target The imported data is imported into the project form as the field value of the matching project form field.
  • the query expression can be customized, so that users can flexibly combine query conditions. For example: "Male [gender] AND Hunan [address] OR liver cancer [electronic medical record]", where spaces are used to separate conditions and connectors.
  • the data on the left of the square brackets is the query condition statement, and the data in the square brackets need to be queried
  • the fields of AND and OR are the connectors between the conditions.
  • Customized query expressions can be parsed by special analysis tools. All query conditions and query fields are independently controlled by the user and can be freely combined, which greatly improves Improve the flexibility of query.
  • the query string can be received through a unified input portal, and the field of the query string can be customized according to the content of the query.
  • the field statement can include the name of the disease, the name of the drug, etc.
  • the basic query unit includes field sentences, and the query string corresponding to each basic query unit is obtained from the target database.
  • the project identification is used to identify a research topic. For example, the research on liver cancer corresponds to the first project identification, and the research on stomach disease corresponds to the second project identification.
  • the query result set can be classified into different items. Different items correspond to different types of forms, and different types of forms have different fields, indicating that different target data collections are performed for different disease types. Calculate the item field matching degree between each keyword in the query result set and the item form field of the corresponding item form, so as to match the data field of the result set. If it is the same as the field in the item form, import the item form as the field value Corresponding fields, such as the result set and CRF have a gender field, the data of this field in the query result set will be imported into the project form of the project.
  • the result set obtained through the comprehensive query can be directly imported into the form, and field matching is automatically performed, which further improves the flexibility and diversity of the form import method.
  • Users can import data through excel, interface entry, result set import, follow-up data and other methods to achieve the effect of collecting data in all directions.
  • the imported data includes the target sub-diagnosis and treatment data and at least one data in the query result set.
  • it further includes: performing data processing on the data to be imported to obtain the corresponding processed imported data,
  • the data processing includes at least one of data filtering, data aggregation, and adding fields.
  • the aggregation of data can be realized through aggregation functions, such as the maximum and minimum aggregation processing of the data, and the result of the aggregation processing is used as the data to be imported, which realizes the analysis and calculation before the data is imported.
  • Adding a field means that the processing result corresponding to the new field is obtained after the data is operated, so that the new field corresponding to the operation result is added to the data to be imported.
  • the new field can be a field in a project form, which is convenient Subsequently, the corresponding data is extracted from the processed imported data by adding a new field as the field value of the form for import. It is understandable that the data to be imported can also include excel data entered in advance.
  • the data to be imported is processed before the import, and the data to be imported can be processed for secondary processing, which improves the data quality of statistical analysis and improves the effectiveness of the imported data.
  • step 210 includes: displaying a field configuration interface, the field configuration interface includes a candidate field area and a field editing area, the candidate field area displays preset fields in the system dictionary, and the field editing area includes historical custom editing fields and A new field editing area is added.
  • the new field editing area is used to input new fields, receive field configuration operations acting on the field configuration interface, and generate corresponding field configuration information according to the field configuration operations.
  • the field configuration operations include the selection of the candidate fields. The selection operation of the area, the selection operation of the historical custom edit field and the input operation of the new field edit area.
  • the method further includes: obtaining a target statistical analysis algorithm, and obtaining a statistical form matching the target statistical analysis algorithm.
  • the target statistical analysis algorithm includes a descriptive statistical algorithm, a hypothesis testing algorithm, a correlation analysis algorithm, and a regression analysis algorithm. At least one of them is to extract the data to be analyzed corresponding to the target statistical analysis algorithm from the statistical analysis form, perform operations on the data to be analyzed according to the target statistical analysis algorithm to obtain the corresponding analysis result, and display the analysis result in the form of a statistical analysis image.
  • the target statistical analysis algorithm can include a variety of different types of analysis algorithms, such as descriptive statistical algorithms, tabulation and classification, graphs, and calculation of summary data to describe various activities of data characteristics. Multiple variables can be selected for combination, and the analysis results are displayed in graphs.
  • the Shapirovik test and Kolmogorov test are used internally.
  • the hypothesis testing algorithm is a scientific hypothesis that is tested by observing a set of random variable models. You can select a grouping variable and multiple analysis variables for analysis, and the analysis results are displayed in graphs. Chi-square test, T-check, etc. are used internally.
  • Correlation analysis algorithm refers to the analysis of two or more related variable elements to measure the closeness of the two variable factors. Multiple variables can be selected for combination, and the analysis results are displayed in charts. Kendall is used internally Correlation analysis, Pearson correlation analysis, etc.
  • Regression analysis algorithm is a statistical analysis to determine the quantitative relationship between two or more variables. You can select one dependent variable and multiple analysis variables for analysis, and the analysis results are displayed in graphs.
  • steps in the flowchart of FIG. 2 are displayed in sequence as indicated by the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless specifically stated in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least part of the steps in FIG. 2 may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution of these sub-steps or stages The sequence is not necessarily performed sequentially, but may be performed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.
  • a dynamic form generation device which includes: an acquisition module 310, a data determination module 320, and a first form import module 330. Among them:
  • the obtaining module 310 is configured to obtain dynamically configured field configuration information, extract a target field from the field configuration information, and generate a corresponding target form, the target form including the target field.
  • the dynamic data determining module 320 is used to extract the diagnosis and treatment phase associated fields associated with the diagnosis and treatment phase from the target field, obtain the dynamic field value corresponding to the diagnosis and treatment phase associated field, and determine the current diagnosis and treatment phase corresponding to the target form according to the dynamic field value, and obtain the diagnosis and treatment data from the user
  • the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage is selected as candidate sub-diagnosis and treatment data, the text matching degree of the related fields of the diagnosis and treatment stage and the candidate sub-diagnosis and treatment data is calculated, and the target sub-diagnosis and treatment data is filtered from the candidate sub-diagnosis and treatment data according to the text matching degree.
  • the first form importing module 330 is used to calculate the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target form field of the target form, and identify the matching with the target form field from the target sub-diagnosis and treatment data according to the field matching degree
  • the target keyword according to the location of the target keyword, obtains the corresponding target import information from the target sub-diagnosis and treatment data, and imports the target import information into the target form as the field value of the matched target form field.
  • the device further includes:
  • the second form importing module 340 is used to obtain a query string.
  • the query string includes a custom query expression.
  • the query expression includes at least one query unit.
  • the query unit includes conditional statements and field statements; from the database corresponding to the query string Get the query result set corresponding to the query string in the query result set, configure the matching item ID for the query result set, get the item form corresponding to the item ID; calculate the items between each keyword in the query result set and the item form field of the corresponding item form Field matching degree, according to the item field matching degree, the result set keywords matching the project form fields are identified from the query result set, and the corresponding target import data is obtained from the query result set according to the position of the result set keywords, and the target import data is used as a match Import the field values of the project form fields into the project form.
  • the device further includes:
  • the processing module 350 is configured to perform data processing on the data to be imported to obtain corresponding processed imported data, where the data processing includes at least one of data filtering, data aggregation, and field addition.
  • the acquisition module 310 is also used to display a field configuration interface.
  • the field configuration interface includes a candidate field area and a field editing area.
  • the candidate field area displays preset fields in the system dictionary, and the field editing area includes historical custom editing.
  • Field and new field editing area the new field editing area is used to input new fields; receive field configuration operations acting on the field configuration interface, and generate corresponding field configuration information according to field configuration operations.
  • Field configuration operations include candidate fields The selection operation of the area, the selection operation of the historical custom edit field and the input operation of the new field edit area.
  • the device further includes:
  • the analysis display module 360 is used to obtain the target statistical analysis algorithm and obtain the statistical form matching the target statistical analysis algorithm.
  • the target statistical analysis algorithm includes at least one of a descriptive statistical algorithm, a hypothesis testing algorithm, a correlation analysis algorithm, and a regression analysis algorithm.
  • One is to extract the data to be analyzed corresponding to the target statistical analysis algorithm from the list to be statistic, perform calculations on the data to be analyzed according to the target statistical analysis algorithm to obtain the corresponding analysis results, and display the analysis results in the form of statistical analysis images.
  • the various modules in the above-mentioned dynamic form generating device can be implemented in whole or in part by software, hardware, and a combination thereof.
  • the above-mentioned modules may be embedded in the form of hardware or independent of the processor in the computer equipment, or may be stored in the memory of the computer equipment in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.
  • a computer device is provided.
  • the computer device may be a terminal.
  • the internal structure diagram of the computer device may be as shown in FIG. 4.
  • the computer device includes a processor, a memory, a network interface, an input Device and display screen.
  • the memory includes a storage medium and an internal memory.
  • the storage medium of the computer device stores an operating system, and may also store computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor can execute a dynamic form generation method.
  • the internal memory may also store computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor can execute the dynamic form generation method.
  • the display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen. It can be an external keyboard, touchpad, or mouse.
  • the storage medium may be non-volatile or volatile.
  • a computer device is provided.
  • the computer device may be a server, and its internal structure diagram may be as shown in FIG. 5.
  • the computer equipment includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide calculation and control capabilities.
  • the memory of the computer device includes a storage medium and an internal memory.
  • the storage medium stores an operating system, computer readable instructions, and a database.
  • the internal memory provides an environment for the operation of the operating system and computer-readable instructions in the storage medium.
  • the database of the computer equipment is used to store data tables.
  • the network interface of the computer device is used to communicate with an external terminal through a network connection.
  • the computer-readable instructions are executed by the processor to realize a dynamic form generation method.
  • FIG. 4 and FIG. 5 are only block diagrams of part of the structure related to the solution of the present application, and do not constitute a limitation on the computer equipment to which the solution of the present application is applied.
  • the computer device may include more or fewer components than shown in the figures, or combine certain components, or have a different component arrangement.
  • a computer device including a memory and one or more processors.
  • the memory stores computer-readable instructions.
  • the one or more processors execute the following steps: Obtain dynamically configured fields Configuration information, extracting a target field from the field configuration information, and generating a corresponding target form, the target form including the target field; extracting from the target field a diagnosis and treatment phase associated field associated with the diagnosis and treatment phase; obtaining a dynamic field value corresponding to the diagnosis and treatment phase associated field; Determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value; filter the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user's diagnosis and treatment data as candidate sub-diagnosis and treatment data; calculate the text matching degree between the diagnosis and treatment stage associated fields and the candidate sub-diagnosis and treatment data , According to the text matching degree, filter the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data; calculate the field matching degree between each keyword in the target sub-diag
  • the processor further implements the following steps when executing the computer-readable instructions: obtaining a query string, the query string includes a custom query expression, the query expression includes at least one query unit, and the query unit includes a conditional statement And field statements; obtain the query result set corresponding to the query string from the database corresponding to the query string, configure the matching item identifier for the query result set, obtain the item form corresponding to the item identifier, and calculate the corresponding keywords in the query result set
  • the item field matching degree between the item form fields of the item form, the result set keywords matching the item form fields are identified from the query result set according to the item field matching degree, and the corresponding result set is obtained from the query result set according to the position of the result set keywords
  • the target import data of the target import data is imported into the project form as the field value of the matching project form field.
  • the processor further implements the following steps when executing the computer-readable instructions: data processing is performed on the data to be imported to obtain corresponding processed imported data, wherein the data processing includes data filtering, data aggregation, and adding fields At least one of the treatments.
  • the processor further implements the following steps when executing the computer-readable instructions: displaying a field configuration interface.
  • the field configuration interface includes a candidate field area and a field editing area.
  • the candidate field area displays preset fields in the system dictionary.
  • the editing area includes historical custom editing fields and new field editing areas.
  • the new field editing area is used to input new fields; it receives field configuration operations acting on the field configuration interface, and generates corresponding field configuration information according to the field configuration operations.
  • Field configuration operations include the selection operation of the candidate field area, the selection operation of the historical custom edit field, and the input operation of the newly added field edit area.
  • the processor further implements the following steps when executing the computer-readable instructions: acquiring the target statistical analysis algorithm, and acquiring the statistical form matching the target statistical analysis algorithm.
  • the target statistical analysis algorithm includes descriptive statistical algorithms and hypothesis testing. At least one of algorithm, correlation analysis algorithm, and regression analysis algorithm; extract the data to be analyzed corresponding to the target statistical analysis algorithm from the statistical form, and calculate the corresponding analysis result according to the target statistical analysis algorithm to obtain the corresponding analysis result.
  • the analysis results are displayed in the form of analysis images.
  • One or more computer-readable storage media storing computer-readable instructions.
  • the one or more processors perform the following steps: obtaining dynamically configured field configuration information, Extract the target field from the field configuration information, and generate the corresponding target form, the target form includes the target field; extract the diagnosis and treatment phase associated field associated with the diagnosis and treatment phase from the target field; obtain the dynamic field value corresponding to the diagnosis and treatment phase associated field; according to the dynamic field
  • the value determines the current diagnosis and treatment stage corresponding to the target form; selects the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user's diagnosis and treatment data as candidate sub-diagnosis and treatment data; calculates the text matching degree between the diagnosis and treatment stage associated fields and the candidate sub-diagnosis and treatment data, according to the text
  • the matching degree is filtered from the candidate sub-diagnosis and treatment data to obtain the target sub-diagnosis and treatment data; the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target
  • the corresponding target import information is obtained from the target sub-diagnosis and treatment data according to the location of the target keyword, and the target import information is imported into the target form as the field value of the matched target form field.
  • the computer-readable storage medium may be non-volatile or volatile.
  • the following steps are also implemented: obtaining a query string, the query string includes a custom query expression, the query expression includes at least one query unit, and the query unit includes a condition Sentences and field statements; obtain the query result set corresponding to the query string from the database corresponding to the query string, configure the matching item identifier for the query result set, obtain the item form corresponding to the item identifier, and calculate each keyword in the query result set
  • the item field matching degree between the item form fields of the corresponding item form, the result set keywords matching the item form fields are identified from the query result set according to the item field matching degree, and the result set keywords are obtained from the query result set according to the position of the result set keywords
  • the corresponding target import data is imported into the project form as the field value of the matching project form field.
  • the following steps are also implemented: data processing is performed on the to-be-imported data to obtain corresponding processed imported data, wherein the data processing includes data filtering, data aggregation, and data processing. At least one treatment in the field.
  • the following steps are also implemented: display a field configuration interface, the field configuration interface includes a candidate field area and a field editing area, and the candidate field area displays preset fields in the system dictionary.
  • the field editing area includes historical custom editing fields and new field editing areas.
  • the new field editing area is used to input new fields; it receives field configuration operations on the field configuration interface, and generates corresponding field configuration information according to the field configuration operations ,
  • the field configuration operation includes the selection operation of the candidate field area, the selection operation of the historical custom edit field and the input operation of the new field edit area.
  • the following steps are also implemented: obtaining the target statistical analysis algorithm, obtaining the statistical form matching the target statistical analysis algorithm, the target statistical analysis algorithm including descriptive statistical algorithm, hypothesis At least one of inspection algorithm, correlation analysis algorithm, and regression analysis algorithm; extract the data to be analyzed corresponding to the target statistical analysis algorithm from the statistical form, and calculate the corresponding analysis result according to the target statistical analysis algorithm to obtain the corresponding analysis result.
  • the analysis results are displayed in the form of statistical analysis images.
  • Non-volatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory may include random access memory (RAM) or external cache memory.
  • RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Channel (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

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Abstract

一种动态表单生成方法、装置、设备和存储介质，包括：获取动态配置的字段配置信息，提取目标字段，生成对应的目标表单，目标表单包括目标字段（210），从目标字段提取诊疗阶段关联的诊疗阶段关联字段，获取诊疗阶段关联字段对应的动态字段值；根据动态字段值确定目标表单对应的当前诊疗阶段（220）；从用户诊疗数据中筛选与当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；计算诊疗阶段关联字段与候选子诊疗数据的文本匹配度，根据文本匹配度从候选值诊疗数据筛选得到目标子诊疗数据（230）；计算目标子诊疗数据中各个关键字与目标表单字段之间的字段匹配度，根据字段匹配度从目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从目标子诊疗数据获取对应的目标导入信息，将目标导入信息作为匹配的目标表单字段的字段值导入至目标表单（240）。

Description

动态表单生成方法、装置、计算机设备和存储介质
相关申请的交叉引用
本申请要求于2020年03月17日提交中国专利局，申请号为202010186201.0，申请名称为“动态表单生成方法、装置、计算机设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及计算机技术领域，特别是涉及一种动态表单生成方法、装置、计算机设备和存储介质。
背景技术
CRF(Case Report Form，病例报告表)表单指按试验方案所规定设计的一种文件，用以记录每一受试者在试验过程中的数据。
目前，发明人意识到，传统的CRF表单的字段是固定的，从而不能灵活的满足用户的需求，录入数据的方式通常也是从web***展示的表单界面填写数据或直接从预设格式的EXCLE文件中导入数据，CRF表单生成的方式不够灵活。
目前，查询功能的应用非常广泛，能够使用户方便快捷地找到自己想要的数据，所以大部分软件存在查询功能。
发明内容
根据本申请公开的各种实施例，提供一种动态表单生成方法、装置、计算机设备和存储介质。
一种动态表单生成方法，所述方法包括：
获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段；
获取所述诊疗阶段关联字段对应的动态字段值；
根据所述动态字段值确定所述目标表单对应的当前诊疗阶段；
从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；
计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配 度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
一种动态表单生成装置，所述装置包括：
获取模块，用于获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
动态数据确定模块，用于从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段，获取所述诊疗阶段关联字段对应的动态字段值，根据所述动态字段值确定所述目标表单对应的当前诊疗阶段，从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据，计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
第一表单导入模块，用于计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
一种计算机设备，包括存储器和一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述处理器执行时，使得所述一个或多个处理器执行以下步骤：
获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段；
获取所述诊疗阶段关联字段对应的动态字段值；
根据所述动态字段值确定所述目标表单对应的当前诊疗阶段；
从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；
计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述 目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
一个或多个存储有计算机可读指令的计算机可读存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行以下步骤：
获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段；
获取所述诊疗阶段关联字段对应的动态字段值；
根据所述动态字段值确定所述目标表单对应的当前诊疗阶段；
从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；
计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。
图1为根据一个或多个实施例中动态表单生成方法的应用环境图；
图2为根据一个或多个实施例中动态表单生成方法的流程示意图；
图3为根据一个或多个实施例中动态表单生成装置的结构框图；
图4为根据一个或多个实施例中计算机设备的内部结构图；
图5为另一个实施例中计算机设备的内部结构图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
本申请提供的动态表单生成方法，可以应用于如图1所示的应用环境中。图1为一个 实施例中动态表单生成方法运行的应用环境图。如图1所示，该应用环境包括终端110、服务器120。终端、服务器之间通过网络进行通信，通信网络可以是无线或者有线通信网络，例如IP网络、蜂窝移动通信网络等，其中终端和服务器的个数不限。
终端110可以但不限于是各种个人计算机、笔记本电脑、智能手机、平板电脑和便携式可穿戴设备。服务器可以用独立的服务器或者是多个服务器组成的服务器集群来实现。动态表单生成方法可以应用于终端也可以应用于服务器。当应用于服务器时，可以从终端获取动态配置的字段配置信息，将携带字段配置信息的表单处理请求发送至服务器，服务器根据字段配置信息确定目标表单字段，并从目标表单对应的当前诊疗阶段数据自适应的确定匹配的目标表单字段的字段值导入至目标表单。
在其中一个实施例中，如图2所示，提供了一种动态表单生成方法，以该方法应用于图1中的终端110或服务器120为例进行说明，包括以下步骤：
步骤210，获取动态配置的字段配置信息，从字段配置信息提取目标字段，生成对应的目标表单，目标表单包括目标字段。
具体地，动态配置的字段配置信息可以是用户实时的根据字段配置操作生成的配置信息，也可以是用户通过历史字段配置操作生成配置信息后，预先存储的配置信息，用于对表单的字段进行动态的配置。可以通过对可视配置界面中候选字段进行的选择操作完成字段配置，生成字段配置信息。也可以通过对字段配置库的选择操作，确定目标字段配置库，从而对目标字段配置库中原本存在的字段进行自适应的映射完成字段配置操作，生成对应的字段配置信息。其中字段配置库中保存有与字段相关的数据，可以通过分析、提取完成字段配置库中原本存在的字段的获取，如根据病种库字段类型自动映射成为相应的填空题、单选等类型，得到目标字段。
在其中一个实施例中，还可通过语音录入的方式获取字段配置信息，识别语音转换为文本，将识别的文本作为表单的目标表单字段。表单字段类型可以支持填空题、单选、复选、时间等格式，可以由用户自定义或由目标字段配置库中原本存在的字段对应的原始字段类型自动映射得到。
步骤220，从目标字段提取与诊疗阶段关联的诊疗阶段关联字段，获取诊疗阶段关联字段对应的动态字段值，根据动态字段值确定目标表单对应的当前诊疗阶段。
诊疗阶段关联字段是指用于确定目标表单对应的诊疗阶段的字段，可以是目标表单的属性字段，或目标表单中的一个或多个与诊疗阶段相关的预设字段。可以从预设位置或通过比对预设字符串从目标字段提取与诊疗阶段关联的诊疗阶段关联字段。其中动态字段值是接收用户的输入操作输入的与诊疗阶段关联字段对应的字段值，随着用户诊疗时间和次数的变化，诊疗阶段关联字段对应的动态字段值也动态变化。
具体地，诊疗阶段关联字段对应的动态字段值包括不同类型的动态信息，包括实时填写的诊疗时间、诊疗用户名称、诊疗次数、以及表单编号等，根据已填写的信息确定目标表单对应的当前诊疗阶段，如诊疗次数在5次以内对应第一诊疗阶段，在5次以上10次 以内对应第二诊疗阶段。表单编号与诊疗阶段的关系可以是预先建立的关联关系，如表单编号从小到大的顺序分别与以时间发展为顺序的诊疗阶段之间存在对应关系，如表单1对应第一诊疗阶段，表单2对应第二诊疗阶段。
步骤230，从用户诊疗数据中筛选与当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；计算诊疗阶段关联字段与候选子诊疗数据的文本匹配度，根据文本匹配度从候选子诊疗数据筛选得到目标子诊疗数据。
当前诊疗阶段用于确定目标表单属于哪个诊疗阶段，如当前诊疗阶段为第一诊疗阶段，则可根据各个子诊疗数据所属的诊疗阶段，筛选得到当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据。子诊疗数据是指诊疗过程中不同阶段产生的数据，如一个随访记录可以为一个子诊疗数据，子诊疗数据包括至少一个随访记录。
具体地，诊疗可以分为不同的阶段，每个阶段的诊疗信息是不同的，可通过对用户的随访记录各个不同阶段的诊疗信息。用户诊疗数据可以包括各个不同阶段的用户随访记录，诊疗的每个阶段的表单都可以是独立的。从而在导入数据至表单时，先确定表单对应的当前诊疗阶段，再获取当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据，再从候选子诊疗数据中根据诊疗阶段关联字段与候选子诊疗数据的文本匹配度获取目标子诊疗数据。
可以将目标表单的诊疗阶段关联字段与候选子诊疗数据中各个随访记录的诊疗字段进行文本匹配，匹配度超过预设阈值的随访记录作为目标子诊疗数据。如目标表单的诊疗阶段关联字段包括高血压值、血常规5项、尿常规字段，则从不同的随访记录中提取关键字，与目标表单中的诊疗阶段关联字段进行匹配，匹配度最高的随访记录作为目标子诊疗数据。
步骤240，计算目标子诊疗数据中各个关键字与目标表单的目标表单字段之间的字段匹配度，根据字段匹配度从目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从目标子诊疗数据获取对应的目标导入信息，将目标导入信息作为匹配的目标表单字段的字段值导入至目标表单。
具体地，对目标子诊疗数据进行关键字的提取，将提取的关键字与目标表单字段进行匹配，匹配成功的关键字对应的邻近文本进行语义分析，从而得到目标表单字段对应的字段值，将字段值自动导入至目标表单中对应字段的位置，实现了表单数据的自动填充，方便高效。
本实施例中，通过获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括目标字段，从目标字段提取与诊疗阶段关联的诊疗阶段关联字段，获取诊疗阶段关联字段对应的动态字段值，根据动态字段值确定目标表单对应的当前诊疗阶段，从用户诊疗数据中筛选与当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；计算诊疗阶段关联字段与候选子诊疗数据的文本匹配度，根据文本匹配度从候选子诊疗数据筛选得到目标子诊疗数据；计算目标子诊疗数据中各个关键字与目标表 单的目标表单字段之间的字段匹配度，根据字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至目标表单，通过动态配置的字段配置信息可以实现动态字段设计，表单的字段可以由用户自定义设计，通过从目标字段提取与诊疗阶段关联的诊疗阶段关联字段，获取诊疗阶段关联字段对应的动态字段值，从而根据动态字段值确定对应的当前诊疗阶段，再从当前诊疗阶段对应的候选子诊疗数据中筛选得到目标子诊疗数据，将目标子诊疗数据中的目标导入信息作为匹配的表单字段的字段值导入至目标表单，不同的动态字段值可以确定不同的当前诊疗阶段，实现病种不同的阶段设计不同的表单，通过收集种病在不同阶段的数据，直接导入到表单，实现表单数据导入的动态高效性，且与病种不同的阶段的匹配性，提高了表单生成的灵活性与多样性。
在其中一个实施例中，方法还包括：获取查询字符串，查询字符串包括自定义的查询表达式，查询表达式包括至少一个查询单元，查询单元包括条件语句和字段语句；从查询字符串对应的数据库中获取查询字符串对应的查询结果集，为查询结果集配置匹配的项目标识，获取项目标识对应类型的项目表单；计算查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据项目字段匹配度从查询结果集中识别出与所述项目表单字段匹配的结果集关键字，根据结果集关键字的位置从查询结果集获取对应的目标导入数据，将目标导入数据作为匹配的项目表单字段的字段值导入至项目表单。
查询表达式可自定义，从而用户可以很灵活的组合查询条件。例如：“男[性别]AND湖南[地址]OR肝癌[电子病历]”，其中，以空格作为条件和连接符的分割，中括号左边的数据是查询条件语句，中括号里面的数据是需要查询的字段，AND和OR是各条件之间的连接符，可通过专门的解析工具对自定义的查询表达式进行解析，所有的查询条件和查询字段都由用户自主控制，自由组合，极大地提高了查询的灵活性。可通过统一的输入入口接收查询字符串，查询字符串的字段可根据查询的内容自定义，如对于医药数据的查询，字段语句可包括病种名称、药品名称等。解析查询表达式时可自定义解析算法，如从左向右依次解析，识别分割符，得到各个基本查询单元，基本查询单元包括字段语句，根据各个基本查询单元从目标数据库中获取查询字符串对应的查询结果集。项目标识用于标识一个研究课题，如对肝癌的研究对应第一项目标识，对胃病的研究对应第二项目标识。
具体地，可以将查询结果集归入不同的项目中，不同的项目对应不同类型的表单，不同类型的表单的字段不同，表示对不同的病种进行不同目标数据的收集。计算查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，从而对结果集的数据字段进行匹配，如果与项目表单中的字段相同，则作为字段值导入项目表单中对应的字段，如结果集和CRF都有性别这个字段，查询结果集中这个字段数据就会导入进项目的项目表单中。
本实施例中，可以将通过综合查询，查询出来的结果集可以直接导入到表单中，自动 进行字段的匹配，进一步提高了表单的导入方式的灵活性与多样性。用户可以通过excel、界面录入、结果集导入、随访数据等多种方式导入数据，达到全方位收集数据的效果。
在其中一个实施例中，导入数据包括目标子诊疗数据和查询结果集中的至少一种数据，将待导入数据导入对应的表单之前还包括：将待导入数据进行数据处理得到对应的处理导入数据，其中数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
具体地，数据过滤时可以自定义过滤条件，通过条件参数过滤掉一部分不需要的数据，可对不同项目对应的表单配置不同的过滤条件，从而将与项目无关的数据进行过滤，且过滤条件可重复利用，提高过滤效率。可以通过聚合函数实现对数据的聚合，如对数据进行最大值、最小值等聚合处理，将聚合处理结果作为待导入数据，实现了数据导入前的分析与运算。增加字段是指对数据进行运算后得到与新增字段对应的处理结果，从而在待导入数据中增加与运算结果对应的新增字段，新增字段可以是某个项目表单中的字段，从而便于后续从处理导入数据中通过新增字段提取对应的数据作为表单的字段值进行导入。可以理解的是待导入数据还可以包括提前录入的excel数据。
本实施例中，在导入前对待导入数据进行数据处理，可以对待导入数据进行二次加工处理，提高统计分析的数据质量，能提高导入数据的有效性。
在其中一个实施例中，步骤210包括：显示字段配置界面，字段配置界面包括候选字段区和字段编辑区，候选字段区显示***字典中的预设字段，字段编辑区包括历史自定义编辑字段和新增字段编辑区，新增字段编辑区用于输入新增的字段，接收作用于字段配置界面的字段配置操作，根据字段配置操作生成对应的字段配置信息，字段配置操作包括对所述候选字段区的选择操作、对历史自定义编辑字段的选择操作和新增字段编辑区的输入操作。
具体地，通过候选字段区的***字典或字段编辑区的历史自定义编辑字段进行选择拖拽生成表单的字段，或在字段编辑区的新增字段编辑区输入自定义字段，再将输入的自定义字段选择拖拽生成表单的字段，通过可视化界面设计表单的字段，方便快捷。
在其中一个实施例中，方法还包括：获取目标统计分析算法，获取与目标统计分析算法匹配的待统计表单，目标统计分析算法包括描述性统计算法、假设检验算法、相关分析算法、回归分析算法中的至少一种，从待统计表单中提取与目标统计分析算法对应的待分析数据，根据目标统计分析算法对待分析数据进行运算得到对应的分析结果，通过统计分析图像的形式展示分析结果。
具体地，目标统计分析算法可以包括多种不同类型的分析算法，如描述性统算法，运用制表和分类，图形以及计算概括性数据来描述数据特征的各项活动。可以选择多个变量进行组合，分析结果以图表显示，内部使用了夏皮罗维克检验法和科尔莫戈罗夫检验法。假设检验算法，通过观察一组随机变量的模型进行检验的科学假说，可以选择一个分组变量多个分析变量进行分析，分析结果以图表显示，内部使用了卡方检验、T校验等。相关分析算法，指对两个或多个具备相关性的变量元素进行分析，从而衡量两个变量因素的相 关密切程度，可以选择多个变量进行组合，分析结果以图表显示，内部使用了肯达尔相关分析、皮尔森相关分析等。回归分析算法，是确定两种或两种以上变量间相互依赖的定量关系的一种统计分析，可以选择一个因变量多个分析变量进行分析，分析结果以图表显示。
本实施例中，提供描述性统计分析、假设校验、相关分析、回归分析等多种专业的科研统计方式，能为科研人员提供易于查看的图表、灵活变量组合、专业的统计数据，是科研人员进行科研工作的好助手。
应该理解的是，虽然图2的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图2中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
在其中一个实施例中，如图3所示，提供了一种动态表单生成装置，包括：获取模块310、数据确定模块320、第一表单导入模块330其中：
获取模块310，用于获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，目标表单包括所述目标字段。
动态数据确定模块320，用于从目标字段提取与诊疗阶段关联的诊疗阶段关联字段，获取诊疗阶段关联字段对应的动态字段值，根据动态字段值确定目标表单对应的当前诊疗阶段，从用户诊疗数据中筛选与当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据，计算诊疗阶段关联字段与候选子诊疗数据的文本匹配度，根据文本匹配度从候选子诊疗数据筛选得到目标子诊疗数据。
第一表单导入模块330，用于计算目标子诊疗数据中各个关键字与目标表单的目标表单字段之间的字段匹配度，根据字段匹配度从目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从目标子诊疗数据获取对应的目标导入信息，将目标导入信息作为匹配的目标表单字段的字段值导入至目标表单。
在其中一个实施例中，装置还包括：
第二表单导入模块340，用于获取查询字符串，查询字符串包括自定义的查询表达式，查询表达式包括至少一个查询单元，查询单元包括条件语句和字段语句；从查询字符串对应的数据库中获取查询字符串对应的查询结果集，为查询结果集配置匹配的项目标识，获取项目标识对应类型的项目表单；计算查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据项目字段匹配度从查询结果集中识别出与项目表单字段匹配的结果集关键字，根据结果集关键字的位置从查询结果集获取对应的目标导入数据，将目标导入数据作为匹配的项目表单字段的字段值导入至项目表单。
在其中一个实施例中，装置还包括：
处理模块350，用于将待导入数据进行数据处理得到对应的处理导入数据，其中数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
在其中一个实施例中，获取模块310还用于显示字段配置界面，字段配置界面包括候选字段区和字段编辑区，候选字段区显示***字典中的预设字段，字段编辑区包括历史自定义编辑字段和新增字段编辑区，新增字段编辑区用于输入新增的字段；接收作用于字段配置界面的字段配置操作，根据字段配置操作生成对应的字段配置信息，字段配置操作包括对候选字段区的选择操作、对历史自定义编辑字段的选择操作和新增字段编辑区的输入操作。
在其中一个实施例中，装置还包括：
分析展示模块360，用于获取目标统计分析算法，获取与目标统计分析算法匹配的待统计表单，目标统计分析算法包括描述性统计算法、假设检验算法、相关分析算法、回归分析算法中的至少一种，从待统计表单中提取与目标统计分析算法对应的待分析数据，根据目标统计分析算法对待分析数据进行运算得到对应的分析结果，通过统计分析图像的形式展示分析结果。
关于动态表单生成装置的具体限定可以参见上文中对于动态表单生成方法的限定，在此不再赘述。上述动态表单生成装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在其中一个实施例中，提供了一种计算机设备，该计算机设备可以是终端，其内部结构图可以如图4所示,该计算机设备包括通过***总线连接的处理器、存储器、网络接口、输入装置和显示屏。其中，存储器包括存储介质和内存储器。该计算机设备的存储介质存储有操作***，还可存储有计算机可读指令，该计算机可读指令被处理器执行时，可使得处理器执行一种动态表单生成方法。该内存储器中也可储存有计算机可读指令，该计算机可读指令被处理器执行时，可使得处理器执行动态表单生成方法。计算机设备的显示屏可以是液晶显示屏或者电子墨水显示屏，计算机设备的输入装置可以是显示屏上覆盖的触摸层，也可以是计算机设备外壳上设置的按键、轨迹球或触控板，还可以是外接的键盘、触控板或鼠标等。存储介质可以是非易失性，也可以是易失性的。
在其中一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，其内部结构图可以如图5所示。该计算机设备包括通过***总线连接的处理器、存储器、网络接口和数据库。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括存储介质、内存储器。该存储介质存储有操作***、计算机可读指令和数据库。该内存储器为存储介质中的操作***和计算机可读指令的运行提供环境。该计算机设备的数据库用于存储数据表。该计算机设备的网络接口用于与外部的终端通过网络连接通信。 该计算机可读指令被处理器执行时以实现一种动态表单生成方法。
本领域技术人员可以理解，图4、图5中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
一种计算机设备，包括存储器和一个或多个处理器，存储器中储存有计算机可读指令，计算机可读指令被处理器执行时，使得一个或多个处理器执行以下步骤：获取动态配置的字段配置信息，从字段配置信息提取目标字段，生成对应的目标表单，目标表单包括所述目标字段；从目标字段提取与诊疗阶段关联的诊疗阶段关联字段；获取诊疗阶段关联字段对应的动态字段值；根据动态字段值确定目标表单对应的当前诊疗阶段；从用户诊疗数据中筛选与当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；计算诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据文本匹配度从候选子诊疗数据筛选得到目标子诊疗数据；计算目标子诊疗数据中各个关键字与目标表单的目标表单字段之间的字段匹配度，根据字段匹配度从目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从目标子诊疗数据获取对应的目标导入信息，将目标导入信息作为匹配的目标表单字段的字段值导入至目标表单。
在其中一个实施例中，处理器执行计算机可读指令时还实现以下步骤：获取查询字符串，查询字符串包括自定义的查询表达式，查询表达式包括至少一个查询单元，查询单元包括条件语句和字段语句；从查询字符串对应的数据库中获取查询字符串对应的查询结果集，为查询结果集配置匹配的项目标识，获取项目标识对应类型的项目表单，计算查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据项目字段匹配度从查询结果集中识别出与项目表单字段匹配的结果集关键字，根据结果集关键字的位置从查询结果集获取对应的目标导入数据，将目标导入数据作为匹配的项目表单字段的字段值导入至项目表单。
在其中一个实施例中，处理器执行计算机可读指令时还实现以下步骤：将所述待导入数据进行数据处理得到对应的处理导入数据，其中所述数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
在其中一个实施例中，处理器执行计算机可读指令时还实现以下步骤：显示字段配置界面，字段配置界面包括候选字段区和字段编辑区，候选字段区显示***字典中的预设字段，字段编辑区包括历史自定义编辑字段和新增字段编辑区，新增字段编辑区用于输入新增的字段；接收作用于字段配置界面的字段配置操作，根据字段配置操作生成对应的字段配置信息，字段配置操作包括对候选字段区的选择操作、对历史自定义编辑字段的选择操作和新增字段编辑区的输入操作。
在其中一个实施例中，处理器执行计算机可读指令时还实现以下步骤：获取目标统计分析算法，获取与目标统计分析算法匹配的待统计表单，目标统计分析算法包括描述性统计算法、假设检验算法、相关分析算法、回归分析算法中的至少一种；从待统计表单中提取与目标统计分析算法对应的待分析数据，根据目标统计分析算法对待分析数据进行运算得到对应的分析结果，通过统计分析图像的形式展示分析结果。
一个或多个存储有计算机可读指令的计算机可读存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器执行以下步骤：获取动态配置的字段配置信息，从字段配置信息提取目标字段，生成对应的目标表单，目标表单包括所述目标字段；从目标字段提取与诊疗阶段关联的诊疗阶段关联字段；获取诊疗阶段关联字段对应的动态字段值；根据动态字段值确定目标表单对应的当前诊疗阶段；从用户诊疗数据中筛选与当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；计算诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据文本匹配度从候选子诊疗数据筛选得到目标子诊疗数据；计算目标子诊疗数据中各个关键字与目标表单的目标表单字段之间的字段匹配度，根据字段匹配度从目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从目标子诊疗数据获取对应的目标导入信息，将目标导入信息作为匹配的目标表单字段的字段值导入至目标表单。其中，该计算机可读存储介质可以是非易失性，也可以是易失性的。
在其中一个实施例中，计算机可读指令被处理器执行时还实现以下步骤：获取查询字符串，查询字符串包括自定义的查询表达式，查询表达式包括至少一个查询单元，查询单元包括条件语句和字段语句；从查询字符串对应的数据库中获取查询字符串对应的查询结果集，为查询结果集配置匹配的项目标识，获取项目标识对应类型的项目表单，计算查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据项目字段匹配度从查询结果集中识别出与项目表单字段匹配的结果集关键字，根据结果集关键字的位置从查询结果集获取对应的目标导入数据，将目标导入数据作为匹配的项目表单字段的字段值导入至项目表单。
在其中一个实施例中，计算机可读指令被处理器执行时还实现以下步骤：将所述待导入数据进行数据处理得到对应的处理导入数据，其中所述数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
在其中一个实施例中，计算机可读指令被处理器执行时还实现以下步骤：显示字段配置界面，字段配置界面包括候选字段区和字段编辑区，候选字段区显示***字典中的预设字段，字段编辑区包括历史自定义编辑字段和新增字段编辑区，新增字段编辑区用于输入新增的字段；接收作用于字段配置界面的字段配置操作，根据字段配置操作生成对应的字段配置信息，字段配置操作包括对候选字段区的选择操作、对历史自定义编辑字段的选择操作和新增字段编辑区的输入操作。
在其中一个实施例中，计算机可读指令被处理器执行时还实现以下步骤：获取目标统计分析算法，获取与目标统计分析算法匹配的待统计表单，目标统计分析算法包括描述性统计算法、假设检验算法、相关分析算法、回归分析算法中的至少一种；从待统计表单中提取与目标统计分析算法对应的待分析数据，根据目标统计分析算法对待分析数据进行运算得到对应的分析结果，通过统计分析图像的形式展示分析结果。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，所述的计算机可读指令可存储于一计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (18)

  1. 一种动态表单生成方法，包括：
    获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
    从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段；
    获取所述诊疗阶段关联字段对应的动态字段值；
    根据所述动态字段值确定所述目标表单对应的当前诊疗阶段；
    从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；
    计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
    计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
  2. 根据权利要求1所述的方法，其中，所述方法还包括：
    获取查询字符串，所述查询字符串包括自定义的查询表达式，所述查询表达式包括至少一个查询单元，所述查询单元包括条件语句和字段语句；
    从所述查询字符串对应的数据库中获取查询字符串对应的查询结果集，为所述查询结果集配置匹配的项目标识，获取所述项目标识对应类型的项目表单；及
    计算所述查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据所述项目字段匹配度从查询结果集中识别出与所述项目表单字段匹配的结果集关键字，根据所述结果集关键字的位置从所述查询结果集获取对应的目标导入数据，将所述目标导入数据作为匹配的项目表单字段的字段值导入至所述项目表单。
  3. 根据权利要求2所述的方法，其中，待导入数据包括所述目标子诊疗数据和查询结果集中的至少一种数据，将所述待导入数据导入对应的表单之前还包括：
    将所述待导入数据进行数据处理得到对应的处理导入数据，其中所述数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
  4. 根据权利要求1所述的方法，其中，所述获取动态配置的字段配置信息包括：
    显示字段配置界面，所述字段配置界面包括候选字段区和字段编辑区，所述候选字段区显示***字典中的预设字段，所述字段编辑区包括历史自定义编辑字段和新增字段编辑区，所述新增字段编辑区用于输入新增的字段；及
    接收作用于所述字段配置界面的字段配置操作，根据所述字段配置操作生成对应的字段配置信息，所述字段配置操作包括对所述候选字段区的选择操作、对所述历史自定义编辑字段的选择操作和所述新增字段编辑区的输入操作。
  5. 根据权利要求1所述的方法，其中，所述方法还包括：
    获取目标统计分析算法，获取与所述目标统计分析算法匹配的待统计表单，所述目标统计分析算法包括描述性统计算法、假设检验算法、相关分析算法、回归分析算法中的至少一种；及
    从所述待统计表单中提取与所述目标统计分析算法对应的待分析数据，根据所述目标统计分析算法对所述待分析数据进行运算得到对应的分析结果，通过统计分析图像的形式展示所述分析结果。
  6. 一种动态表单生成装置，包括：
    获取模块，用于获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
    动态数据确定模块，用于从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段，获取所述诊疗阶段关联字段对应的动态字段值，根据所述动态字段值确定所述目标表单对应的当前诊疗阶段，从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据，计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
    第一表单导入模块，用于计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
  7. 根据权利要求6所述的装置，其中，所述装置还包括：
    第二表单导入模块，用于获取查询字符串，所述查询字符串包括自定义的查询表达式，所述查询表达式包括至少一个查询单元，所述查询单元包括条件语句和字段语句；从所述查询字符串对应的数据库中获取查询字符串对应的查询结果集，为所述查询结果集配置匹配的项目标识，获取所述项目标识对应类型的项目表单；计算所述查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据所述项目字段匹配度从查询结果集中识别出与所述项目表单字段匹配的结果集关键字，根据所述结果集关键字的位置从所述查询结果集获取对应的目标导入数据，将所述目标导入数据作为匹配的项目表单字段的字段值导入至所述项目表单。
  8. 根据权利要求7所述的装置，其中，待导入数据包括所述目标子诊疗数据和查询结果集中的至少一种数据，所述装置还包括：
    处理模块，用于将所述待导入数据进行数据处理得到对应的处理导入数据，其中所述数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
  9. 一种计算机设备，包括存储器及一个或多个处理器，所述存储器中储存有计算机 可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
    从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段；
    获取所述诊疗阶段关联字段对应的动态字段值；
    根据所述动态字段值确定所述目标表单对应的当前诊疗阶段；
    从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；
    计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
    计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
  10. 根据权利要求9所述的计算机设备，其中，所述处理器执行所述计算机可读指令时还执行以下步骤：
    获取查询字符串，所述查询字符串包括自定义的查询表达式，所述查询表达式包括至少一个查询单元，所述查询单元包括条件语句和字段语句；
    从所述查询字符串对应的数据库中获取查询字符串对应的查询结果集，为所述查询结果集配置匹配的项目标识，获取所述项目标识对应类型的项目表单；及
    计算所述查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据所述项目字段匹配度从查询结果集中识别出与所述项目表单字段匹配的结果集关键字，根据所述结果集关键字的位置从所述查询结果集获取对应的目标导入数据，将所述目标导入数据作为匹配的项目表单字段的字段值导入至所述项目表单。
  11. 根据权利要求10所述的计算机设备，其中，所述处理器执行所述计算机可读指令时还执行以下步骤：
    将所述待导入数据进行数据处理得到对应的处理导入数据，其中所述数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
  12. 根据权利要求9所述的计算机设备，其中，所述处理器执行所述计算机可读指令时还执行以下步骤：
    显示字段配置界面，所述字段配置界面包括候选字段区和字段编辑区，所述候选字段区显示***字典中的预设字段，所述字段编辑区包括历史自定义编辑字段和新增字段编辑区，所述新增字段编辑区用于输入新增的字段；及
    接收作用于所述字段配置界面的字段配置操作，根据所述字段配置操作生成对应的字 段配置信息，所述字段配置操作包括对所述候选字段区的选择操作、对所述历史自定义编辑字段的选择操作和所述新增字段编辑区的输入操作。
  13. 根据权利要求9所述的计算机设备，其中，所述处理器执行所述计算机可读指令时还执行以下步骤：
    获取目标统计分析算法，获取与所述目标统计分析算法匹配的待统计表单，所述目标统计分析算法包括描述性统计算法、假设检验算法、相关分析算法、回归分析算法中的至少一种；及
    从所述待统计表单中提取与所述目标统计分析算法对应的待分析数据，根据所述目标统计分析算法对所述待分析数据进行运算得到对应的分析结果，通过统计分析图像的形式展示所述分析结果。
  14. 一个或多个存储有计算机可读指令的计算机可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    获取动态配置的字段配置信息，从所述字段配置信息提取目标字段，生成对应的目标表单，所述目标表单包括所述目标字段；
    从所述目标字段提取与诊疗阶段关联的诊疗阶段关联字段；
    获取所述诊疗阶段关联字段对应的动态字段值；
    根据所述动态字段值确定所述目标表单对应的当前诊疗阶段；
    从所述用户诊疗数据中筛选与所述当前诊疗阶段对应的子诊疗数据作为候选子诊疗数据；
    计算所述诊疗阶段关联字段与所述候选子诊疗数据的文本匹配度，根据所述文本匹配度从所述候选子诊疗数据筛选得到目标子诊疗数据；及
    计算所述目标子诊疗数据中各个关键字与所述目标表单的目标表单字段之间的字段匹配度，根据所述字段匹配度从所述目标子诊疗数据中识别出与目标表单字段匹配的目标关键字，根据目标关键字的位置从所述目标子诊疗数据获取对应的目标导入信息，将所述目标导入信息作为匹配的目标表单字段的字段值导入至所述目标表单。
  15. 根据权利要求14所述的存储介质，其中，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    获取查询字符串，所述查询字符串包括自定义的查询表达式，所述查询表达式包括至少一个查询单元，所述查询单元包括条件语句和字段语句；
    从所述查询字符串对应的数据库中获取查询字符串对应的查询结果集，为所述查询结果集配置匹配的项目标识，获取所述项目标识对应类型的项目表单；及
    计算所述查询结果集中各个关键字与对应的项目表单的项目表单字段之间的项目字段匹配度，根据所述项目字段匹配度从查询结果集中识别出与所述项目表单字段匹配的结果集关键字，根据所述结果集关键字的位置从所述查询结果集获取对应的目标导入数据，将所述目标导入数据作为匹配的项目表单字段的字段值导入至所述项目表单。
  16. 根据权利要求15所述的存储介质，其中，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    将所述待导入数据进行数据处理得到对应的处理导入数据，其中所述数据处理包括数据过滤、数据聚合、增加字段中的至少一种处理。
  17. 根据权利要求14所述的存储介质，其中，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    显示字段配置界面，所述字段配置界面包括候选字段区和字段编辑区，所述候选字段区显示***字典中的预设字段，所述字段编辑区包括历史自定义编辑字段和新增字段编辑区，所述新增字段编辑区用于输入新增的字段；及
    接收作用于所述字段配置界面的字段配置操作，根据所述字段配置操作生成对应的字段配置信息，所述字段配置操作包括对所述候选字段区的选择操作、对所述历史自定义编辑字段的选择操作和所述新增字段编辑区的输入操作。
  18. 根据权利要求14所述的存储介质，其中，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    获取目标统计分析算法，获取与所述目标统计分析算法匹配的待统计表单，所述目标统计分析算法包括描述性统计算法、假设检验算法、相关分析算法、回归分析算法中的至少一种；及
    从所述待统计表单中提取与所述目标统计分析算法对应的待分析数据，根据所述目标统计分析算法对所述待分析数据进行运算得到对应的分析结果，通过统计分析图像的形式展示所述分析结果。
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