Dynamic form generation method, device, computer equipment and storage medium

Abstract

The present application relates to big data and provides a dynamic form generation method, apparatus, device and storage medium, including: obtaining dynamically configured field configuration information, extracting target fields, generating a target form including the target fields, extracting treatment stage-related fields from the target fields and obtaining corresponding dynamic field values; determining the current treatment stage corresponding to the target form according to the dynamic field values; screening sub-treatment data corresponding to the current treatment stage from user treatment data as candidate sub-treatment data; screening target sub-treatment data according to the text matching degree between the treatment stage-related fields and the candidate sub-treatment data; calculating the field matching degree between each keyword in the target sub-treatment data and the target form field, identifying the target keyword from the target sub-treatment data, and obtaining the corresponding target import information from the target sub-treatment data as the field value of the matching target form field and importing it into the target form, thereby improving the flexibility of form generation.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, apparatus, computer device and storage medium for generating a dynamic form. Background Art

[0002] CRF (Case Report Form) is a document designed according to the trial protocol to record the data of each subject during the trial.

[0003] At present, the fields of traditional CRF forms are fixed, which cannot flexibly meet the needs of users. The way to enter data is usually to fill in data from the form interface displayed by the web system or directly import data from an EXCLE file in a preset format. The way to generate CRF forms is not flexible enough. Summary of the invention

[0004] Based on this, it is necessary to provide a dynamic form generation method, device, computer equipment and storage medium to address the above technical problems, support dynamic field design, and improve the flexibility and adaptability of importing data into CRF forms.

[0005] A dynamic form generation method, the method comprising:

[0006] Acquire dynamically configured field configuration information, extract target fields from the field configuration information, and generate a corresponding target form, wherein the target form includes the target fields;

[0007] Extracting a diagnosis and treatment stage associated field associated with the diagnosis and treatment stage from the target field;

[0008] Obtain the dynamic field value corresponding to the diagnosis and treatment stage associated field;

[0009] Determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value;

[0010] Filtering sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user diagnosis and treatment data as candidate sub-diagnosis and treatment data;

[0011] Calculating the text matching degree between the diagnosis and treatment stage associated field and the candidate sub-diagnosis and treatment data, and filtering the candidate sub-diagnosis and treatment data to obtain target sub-diagnosis and treatment data according to the text matching degree;

[0012] 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

[0013] In one embodiment, the method further comprises:

[0014] Acquire a query string, wherein the query string includes a user-defined query expression, wherein the query expression includes at least one query unit, and wherein the query unit includes a conditional statement and a field statement;

[0015] Acquire a query result set corresponding to the query string from a database corresponding to the query string, configure a matching project identifier for the query result set, and acquire a project form of a type corresponding to the project identifier;

[0016] Calculate the project field matching degree between each keyword in the query result set and the corresponding project form field of the project form, identify the result set keyword that matches the project form field from the query result set according to the project field matching degree, obtain the corresponding target import data from the query result set according to the position of the result set keyword, and import the target import data into the project form as the field value of the matching project form field.

[0017] In one embodiment, the data to be imported includes the target sub-diagnosis and treatment data and at least one data in the query result set, and before importing the data to be imported into the corresponding form, the following step is further included:

[0018] The data to be imported is processed to obtain corresponding processed imported data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

[0019] In one embodiment, the acquiring the dynamically configured field configuration information and determining the target field according to the field configuration information comprises:

[0020] 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 field editing area includes a historical custom editing field and a newly added field editing area, the newly added field editing area is used to enter a newly added field;

[0021] Receive a field configuration operation acting on the field configuration interface, and generate corresponding field configuration information according to the field configuration operation, wherein the field configuration operation includes a selection operation on the candidate field area, a selection operation on the historical custom edit field, and an input operation on the newly added field edit area.

[0022] In one embodiment, the method further comprises:

[0023] Obtain a target statistical analysis algorithm, and obtain a form to be counted that matches the target statistical analysis algorithm, wherein 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;

[0024] The data to be analyzed corresponding to the target statistical analysis algorithm are extracted from the table to be counted, the data to be analyzed are calculated according to the target statistical analysis algorithm to obtain corresponding analysis results, and the analysis results are displayed in the form of statistical analysis images.

[0025] A dynamic form generation device, the device comprising:

[0026] An acquisition module, used to acquire dynamically configured field configuration information, extract a target field from the field configuration information, and generate a corresponding target form, wherein the target form includes the target field;

[0027] A dynamic data determination module is used to extract a diagnosis and treatment stage-related field associated with the diagnosis and treatment stage from the target field, obtain a dynamic field value corresponding to the diagnosis and treatment stage-related field, determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value, filter sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user diagnosis and treatment data as candidate sub-diagnosis and treatment data, calculate the text matching degree between the diagnosis and treatment stage-related field and the candidate sub-diagnosis and treatment data, and filter the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data according to the text matching degree;

[0028] 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

[0029] In one embodiment, the device further comprises:

[0030] The second form import module is used to obtain 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; obtain a query result set corresponding to the query string from a database corresponding to the query string, configure a matching project identifier for the query result set, and obtain a project form of a type corresponding to the project identifier; calculate the project field matching degree between each keyword in the query result set and the project form field of the corresponding project form, identify the result set keyword matching the project form field from the query result set according to the project field matching degree, obtain the corresponding target import data from the query result set according to the position of the result set keyword, and import the target import data into the project form as the field value of the matching project form field.

[0031] In one embodiment, the data to be imported includes the target sub-diagnosis and treatment data and at least one data in the query result set, and the device further includes:

[0032] The processing module is used to process the data to be imported to obtain corresponding processed imported data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

[0033] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0034] Acquire dynamically configured field configuration information, extract target fields from the field configuration information, and generate a corresponding target form, wherein the target form includes the target fields;

[0035] Extracting a diagnosis and treatment stage associated field associated with the diagnosis and treatment stage from the target field;

[0036] Obtain the dynamic field value corresponding to the diagnosis and treatment stage associated field;

[0037] Determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value;

[0038] Filtering sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user diagnosis and treatment data as candidate sub-diagnosis and treatment data;

[0039] Calculating the text matching degree between the diagnosis and treatment stage associated field and the candidate sub-diagnosis and treatment data, and filtering the candidate sub-diagnosis and treatment data to obtain target sub-diagnosis and treatment data according to the text matching degree;

[0040] 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

[0041] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0042] Acquire dynamically configured field configuration information, extract target fields from the field configuration information, and generate a corresponding target form, wherein the target form includes the target fields;

[0043] Extracting a diagnosis and treatment stage associated field associated with the diagnosis and treatment stage from the target field;

[0044] Obtain the dynamic field value corresponding to the diagnosis and treatment stage associated field;

[0045] Determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value;

[0046] Filtering sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user diagnosis and treatment data as candidate sub-diagnosis and treatment data;

[0047] Calculating the text matching degree between the diagnosis and treatment stage associated field and the candidate sub-diagnosis and treatment data, and filtering the candidate sub-diagnosis and treatment data to obtain target sub-diagnosis and treatment data according to the text matching degree;

[0048] 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

[0049] The above-mentioned dynamic form generation method, device, computer equipment and storage medium obtain dynamically configured field configuration information, extract the target field from the field configuration information, and generate a corresponding target form, wherein the target form includes a target field, extracts the diagnosis and treatment stage-related field associated with the diagnosis and treatment stage from the target field, obtains the dynamic field value corresponding to the diagnosis and treatment stage-related field, determines the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value, and filters 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-related field and the candidate sub-diagnosis and treatment data, and obtains the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data according to the text matching degree; calculates the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target form field of the target form, identifies the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, and selects the target keyword from the target sub-diagnosis and treatment data according to the position of the target keyword. Obtain the corresponding target import information, and import the target import information into the target form as the field value of the matching target form field. Dynamic field design can be achieved through dynamically configured field configuration information. The fields of the form can be customized by the user. The diagnosis and treatment stage-related fields associated with the diagnosis and treatment stage are extracted from the target field, and the dynamic field value corresponding to the diagnosis and treatment stage-related fields is obtained. The corresponding current diagnosis and treatment stage is determined according to the dynamic field value, and then the target sub-diagnosis and treatment data are screened from the candidate sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage. The target import information in the target sub-diagnosis and treatment data 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, so that different forms can be designed for different stages of the disease. By collecting data of the disease at different stages and importing them directly into the form, dynamic and efficient form data import is achieved, and the matching with different stages of the disease is improved, thereby improving the flexibility and diversity of form generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 An application environment diagram of a dynamic form generation method in one embodiment;

[0051] Figure 2 A schematic diagram of a flow chart of a dynamic form generation method in one embodiment;

[0052] Figure 3 is a structural block diagram of a dynamic form generating device in one embodiment;

[0053] Figure 4 is an internal structure diagram of a computer device in one embodiment;

[0054] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0056] The dynamic form generation method provided by this application can be applied to Figure 1 In the application environment shown. Figure 1 FIG. 1 is an application environment diagram for the operation of a dynamic form generation method in an embodiment. Figure 1 As shown, the application environment includes a terminal 110 and a server 120. The terminal and the server communicate with each other through a network, and the communication network can be a wireless or wired communication network, such as an IP network, a cellular mobile communication network, etc., wherein the number of terminals and servers is not limited.

[0057] Among them, the terminal 110 can be, but is not limited to, various personal computers, laptops, 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 terminals as well as servers. When applied to the server, dynamically configured field configuration information can be obtained from the terminal, and a 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 adaptively determines the field value of the matching target form field from the current diagnosis and treatment stage data corresponding to the target form and imports it into the target form.

[0058] In one embodiment, Figure 2 As shown, a dynamic form generation method is provided, which is applied to Figure 1 The terminal 110 or the server 120 in the example is used as an example to illustrate, and the following steps are included:

[0059] Step 210, obtaining dynamically configured field configuration information, extracting target fields from the field configuration information, and generating a corresponding target form, wherein the target form includes the target fields.

[0060] Specifically, the dynamically configured field configuration information can be the configuration information generated by the user in real time according to the field configuration operation, or it can be the configuration information pre-stored after the user generates the configuration information through the historical field configuration operation, which is used to dynamically configure the fields of the form. The field configuration can be completed by selecting the candidate fields in the visual configuration interface to generate the field configuration information. It is also possible to determine the target field configuration library by selecting the field configuration library, so as to adaptively map the fields originally existing in the target field configuration library to complete the field configuration operation and generate the corresponding field configuration information. The field configuration library stores data related to the fields, and the acquisition of the fields originally existing in the field configuration library can be completed by analysis and extraction, such as automatically mapping the field types of the disease library into corresponding fill-in-the-blank questions, single-choice questions, etc., to obtain the target field.

[0061] In one embodiment, field configuration information can also be obtained by voice input, 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 originally existing in the target field configuration library.

[0062] Step 220, extract the diagnosis and treatment stage associated field associated with the diagnosis and treatment stage from the target field, obtain the dynamic field value corresponding to the diagnosis and treatment stage associated field, and determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value.

[0063] The diagnosis and treatment stage-related field refers to a field used to determine the diagnosis and treatment stage corresponding to the target form, which can be an attribute field of the target form, or one or more preset fields related to the diagnosis and treatment stage in the target form. The diagnosis and treatment stage-related field associated with the diagnosis and treatment stage can be extracted from the target field from a preset position or by comparing a preset string. The dynamic field value is the field value corresponding to the diagnosis and treatment stage-related field 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 diagnosis and treatment stage-related field also changes dynamically.

[0064] Specifically, the dynamic field value corresponding to the diagnosis and treatment stage association field includes different types of dynamic information, including the diagnosis and treatment time, diagnosis and treatment user name, number of diagnosis and treatment, and form number filled in in real time. The current diagnosis and treatment stage corresponding to the target form is determined based on the filled in information. For example, the number of diagnosis and treatment within 5 times corresponds to the first diagnosis and treatment stage, and more than 5 times and less than 10 times 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 association relationship, such as there is a corresponding relationship between the order of form numbers from small to large and the diagnosis and treatment stages in the order of time development, such as Form 1 corresponds to the first diagnosis and treatment stage, and Form 2 corresponds to the second diagnosis and treatment stage.

[0065] Step 230, filter out the sub-treatment data corresponding to the current treatment stage from the user treatment data as candidate sub-treatment data; calculate the text matching degree between the treatment stage associated field and the candidate sub-treatment data, and filter out the target sub-treatment data from the candidate sub-treatment data according to the text matching degree.

[0066] Among them, 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 screened according to the diagnosis and treatment stage to which each sub-diagnosis and treatment data belongs, and the sub-diagnosis and treatment data is obtained as the candidate sub-diagnosis and treatment data. Sub-diagnosis and treatment data refers to the data generated at different stages of the diagnosis and treatment process. For example, a follow-up record can be a sub-diagnosis and treatment data, and the sub-diagnosis and treatment data includes at least one follow-up record.

[0067] Specifically, diagnosis and treatment can be divided into different stages, and the diagnosis and treatment information of each stage is different. The diagnosis and treatment information of each stage can be recorded through follow-up records of users. User diagnosis and treatment data can include user follow-up records of different stages, and the forms for each stage of 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, then obtain the sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage as candidate sub-diagnosis and treatment data, and then obtain the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data based on the text matching degree between the diagnosis and treatment stage-related fields and the candidate sub-diagnosis and treatment data.

[0068] The treatment stage-related fields of the target form can be matched with the treatment fields of each follow-up record in the candidate sub-treatment data, and the follow-up records with a matching degree exceeding the preset threshold are used as the target sub-treatment data. If the treatment stage-related fields of the target form include hypertension values, five blood routine test items, and urine routine test fields, keywords are extracted from different follow-up records and matched with the treatment stage-related fields in the target form, and the follow-up record with the highest matching degree is used as the target sub-treatment data.

[0069] 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

[0070] Specifically, keywords are extracted from the target sub-diagnosis and treatment data, and the extracted keywords are matched with the target form fields. The adjacent texts corresponding to the successfully matched keywords are semantically analyzed to obtain the field values ​​corresponding to the target form fields. The field values ​​are automatically imported into the corresponding field positions in the target form, thus realizing automatic filling of form data, which is convenient and efficient.

[0071] In this embodiment, by acquiring dynamically configured field configuration information, the target field is extracted from the field configuration information, and a corresponding target form is generated, wherein the target form includes a target field, and a treatment stage-associated field associated with the treatment stage is extracted from the target field, and a dynamic field value corresponding to the treatment stage-associated field is acquired, and the current treatment stage corresponding to the target form is determined according to the dynamic field value, and sub-treatment data corresponding to the current treatment stage is screened from the user's treatment data as candidate sub-treatment data; the text matching degree between the treatment stage-associated field and the candidate sub-treatment data is calculated, and the target sub-treatment data is obtained from the candidate sub-treatment data according to the text matching degree; the field matching degree between each keyword in the target sub-treatment data and the target form field of the target form is calculated, and the target keyword matching the target form field is identified from the target sub-treatment data according to the field matching degree, and the corresponding target import information is acquired from the target sub-treatment data according to the position of the target keyword. The target import information is imported into the target form as the field value of the matching target form field. Dynamic field design can be achieved through dynamically configured field configuration information. The fields of the form can be customized by users. The treatment stage-related fields associated with the treatment stage are extracted from the target fields to obtain the dynamic field values ​​corresponding to the treatment stage-related fields. The corresponding current treatment stage is determined according to the dynamic field values. The target sub-treatment data is then screened from the candidate sub-treatment data corresponding to the current treatment stage. The target import information in the target sub-treatment data is imported into the target form as the field value of the matching form field. Different dynamic field values ​​can determine different current treatment stages, so that different forms can be designed for different stages of the disease. By collecting data of different diseases at different stages and directly importing them into the form, dynamic and efficient form data import is achieved, and the matching with different stages of the disease is improved, thereby improving the flexibility and diversity of form generation.

[0072] In one embodiment, the method also includes: obtaining a query string, the query string includes a customized query expression, the query expression includes at least one query unit, and the query unit includes a conditional statement and a field statement; obtaining a query result set corresponding to the query string from a database corresponding to the query string, configuring a matching project identifier for the query result set, and obtaining a project form of a type corresponding to the project identifier; calculating the project field matching degree between each keyword in the query result set and the project form field of the corresponding project form, identifying a result set keyword matching the project form field from the query result set according to the project field matching degree, obtaining corresponding target import data from the query result set according to the position of the result set keyword, and importing the target import data into the project form as the field value of the matching project form field.

[0073] Among them, the query expression can be customized, so that users can flexibly combine query conditions. For example: "Male [sex] AND Hunan [address] OR Liver cancer [electronic medical record]", in which the space is used as the separator of the condition and the connector, the data on the left side of the bracket is the query condition statement, the data inside the bracket is the field to be queried, and AND and OR are the connectors between the conditions. The customized query expression can be parsed through a special parsing tool. All query conditions and query fields are controlled by the user and can be freely combined, which greatly improves the flexibility of the query. The query string can be received through a unified input entry, and the fields of the query string can be customized according to the query content. For example, for the query of medical data, the field statement may include the name of the disease, the name of the drug, etc. When parsing the query expression, the parsing algorithm can be customized, such as parsing from left to right, identifying the separator, and obtaining each basic query unit. The basic query unit includes the field statement, and the query result set corresponding to the query string is obtained from the target database according to each basic query unit. The project identifier is used to identify a research topic, such as the first project identifier for the research on liver cancer, and the second project identifier for the research on gastric disease.

[0074] Specifically, the query result set can be classified into different projects. Different projects correspond to different types of forms. Different types of forms have different fields, which means that different target data are collected for different diseases. The project field matching degree between each keyword in the query result set and the project form field of the corresponding project form is calculated, so as to match the data field of the result set. If it is the same as the field in the project form, it is imported into the corresponding field in the project form as a field value. For example, if both the result set and CRF have the field of gender, the data of this field in the query result set will be imported into the project form of the project.

[0075] In this embodiment, the result set obtained through comprehensive query can be directly imported into the form, and the fields can be matched automatically, 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 an all-round way.

[0076] In one embodiment, the imported data includes target sub-diagnosis and treatment data and at least one data in the query result set, and before importing the data to be imported into the corresponding form, it also includes: processing the data to be imported to obtain corresponding processed imported data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

[0077] Specifically, you can customize the filtering conditions when filtering data, and filter out some unnecessary data through conditional parameters. You can configure different filtering conditions for the forms corresponding to different projects, so that data unrelated to the project can be filtered, and the filtering conditions can be reused to improve filtering efficiency. Aggregation of data can be achieved through aggregation functions, such as performing aggregation processing such as maximum and minimum values ​​on the data, and using the aggregation processing results as the data to be imported, thereby realizing analysis and calculation before data import. Adding fields means obtaining the processing results corresponding to the newly added fields after calculating the data, thereby adding new fields corresponding to the calculation results to the data to be imported. The newly added fields can be fields in a certain project form, so as to facilitate the subsequent extraction of corresponding data from the processed imported data through the newly added fields as the field values ​​of the form for import. It is understandable that the data to be imported can also include Excel data entered in advance.

[0078] In this embodiment, data processing is performed on the data to be imported before importing, and secondary processing can be performed on the data to be imported, thereby improving the data quality of statistical analysis and improving the effectiveness of the imported data.

[0079] In one embodiment, 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, the field editing area includes a historical custom editing field and a newly added field editing area, the newly added field editing area is used to enter a newly added field, receiving a field configuration operation acting on the field configuration interface, generating corresponding field configuration information according to the field configuration operation, the field configuration operation includes a selection operation on the candidate field area, a selection operation on the historical custom editing field and an input operation on the newly added field editing area.

[0080] Specifically, you can select and drag the fields in the form through the system dictionary in the candidate field area or the historical custom edit fields in the field editing area, or enter the custom fields in the new field editing area in the field editing area, and then drag the entered custom fields to generate the fields in the form. It is convenient and quick to design the fields of the form through a visual interface.

[0081] In one embodiment, the method also includes: obtaining a target statistical analysis algorithm, obtaining a form to be counted that matches the target statistical analysis algorithm, the target statistical analysis algorithm including at least one of a descriptive statistical algorithm, a hypothesis testing algorithm, a correlation analysis algorithm, and a regression analysis algorithm, extracting data to be analyzed corresponding to the target statistical analysis algorithm from the form to be counted, performing operations on the data to be analyzed according to the target statistical analysis algorithm to obtain corresponding analysis results, and displaying the analysis results in the form of a statistical analysis image.

[0082] Specifically, the target statistical analysis algorithm can include a variety of different types of analysis algorithms, such as descriptive statistics, which use tabulation and classification, graphics, and calculation of summary data to describe data characteristics. Multiple variables can be selected for combination, and the analysis results are displayed in charts. The Shapirov test and Kolmogorov test methods are used internally. Hypothesis testing algorithm is a scientific hypothesis tested by observing a model of a set of random variables. One grouping variable and multiple analysis variables can be selected for analysis. The analysis results are displayed in charts. Chi-square test, T test, etc. are used internally. Correlation analysis algorithm refers to the analysis of two or more variable elements with correlation, so as to measure the degree of correlation between two variable factors. Multiple variables can be selected for combination, and the analysis results are displayed in charts. Kendall correlation analysis, Pearson correlation analysis, etc. are used internally. Regression analysis algorithm is a statistical analysis that determines the quantitative relationship between two or more variables that are interdependent. One dependent variable and multiple analysis variables can be selected for analysis, and the analysis results are displayed in charts.

[0083] In this embodiment, various professional scientific research statistical methods such as descriptive statistical analysis, hypothesis verification, correlation analysis, regression analysis, etc. are provided, which can provide researchers with easy-to-view charts, flexible variable combinations, and professional statistical data, and are a good assistant for researchers in their scientific research work.

[0084] It should be understood that although Figure 2 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 At least part of the steps 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 order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0085] In one embodiment, Figure 3 As shown, a dynamic form generation device is provided, including: an acquisition module 310, a data determination module 320, and a first form importing module 330, wherein:

[0086] The acquisition module 310 is used to acquire the dynamically configured field configuration information, extract the target field from the field configuration information, and generate a corresponding target form, wherein the target form includes the target field.

[0087] The dynamic data determination module 320 is used to extract the treatment stage associated field associated with the treatment stage from the target field, obtain the dynamic field value corresponding to the treatment stage associated field, determine the current treatment stage corresponding to the target form according to the dynamic field value, filter the sub-treatment data corresponding to the current treatment stage from the user treatment data as candidate sub-treatment data, calculate the text matching degree between the treatment stage associated field and the candidate sub-treatment data, and filter the target sub-treatment data from the candidate sub-treatment data according to the text matching degree.

[0088] The first form import 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

[0089] In one embodiment, the apparatus further comprises:

[0090] The second form import 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, and the query unit includes a conditional statement and a field statement; obtain a query result set corresponding to the query string from a database corresponding to the query string, configure a matching project identifier for the query result set, and obtain a project form of a type corresponding to the project identifier; calculate the project field matching degree between each keyword in the query result set and the project form field of the corresponding project form, identify the result set keyword that matches the project form field from the query result set according to the project field matching degree, obtain the corresponding target import data from the query result set according to the position of the result set keyword, and import the target import data into the project form as the field value of the matching project form field.

[0091] In one embodiment, the apparatus further comprises:

[0092] The processing module 350 is used to process the data to be imported to obtain corresponding processed imported data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

[0093] In one embodiment, the acquisition module 310 is also used to display a field configuration interface, which 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 newly added field editing area. The newly added field editing area is used to enter newly added 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 selection operations on the candidate field area, selection operations on the historical custom editing fields, and input operations on the newly added field editing area.

[0094] In one embodiment, the apparatus further comprises:

[0095] The analysis and display module 360 ​​is used to obtain the target statistical analysis algorithm and the form to be counted that matches 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. The data to be analyzed corresponding to the target statistical analysis algorithm are extracted from the form to be counted, and the corresponding analysis results are obtained by operating the data to be analyzed according to the target statistical analysis algorithm, and the analysis results are displayed in the form of statistical analysis images.

[0096] The specific definition of the dynamic form generation device can be found in the definition of the dynamic form generation method above, which will not be repeated here. Each module in the above dynamic form generation device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0097] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, a memory, a network interface, an input device and a display screen connected through a system bus. Among them, the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor can execute a dynamic form generation method. The internal memory may also store a computer program. When the computer program is executed by the processor, the processor can execute a dynamic form generation method. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0098] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device 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 computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device 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. When the computer program is executed by the processor, a dynamic form generation method is implemented.

[0099] Those skilled in the art will understand that Figure 4 , Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0100] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the following steps when executing the computer program: obtaining dynamically configured field configuration information, extracting a target field from the field configuration information, and generating a corresponding target form, wherein the target form includes the target field; extracting a diagnosis and treatment stage-associated field associated with the diagnosis and treatment stage from the target field; obtaining a dynamic field value corresponding to the diagnosis and treatment stage-associated field; determining the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value; screening sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from user diagnosis and treatment data as candidate sub-diagnosis and treatment data; calculating a text matching degree between the diagnosis and treatment stage-associated field and the candidate sub-diagnosis and treatment data, and screening the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data according to the text matching degree; calculating a field matching degree between each keyword in the target sub-diagnosis and treatment data and a target form field of the target form, identifying a target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, and obtaining corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and importing the target import information into the target form as the field value of the matching target form field.

[0101] In one embodiment, when the processor executes the computer program, 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 conditional statement and a field statement; obtaining a query result set corresponding to the query string from a database corresponding to the query string, configuring a matching project identifier for the query result set, obtaining a project form of a type corresponding to the project identifier, calculating the project field matching degree between each keyword in the query result set and the project form field of the corresponding project form, identifying a result set keyword that matches the project form field from the query result set according to the project field matching degree, obtaining corresponding target import data from the query result set according to the position of the result set keyword, and importing the target import data into the project form as the field value of the matching project form field.

[0102] In one embodiment, the data to be imported includes target sub-diagnosis and treatment data and at least one data in the query result set. Before the processor executes importing the data to be imported into the corresponding form, it also implements the following steps: processing the data to be imported to obtain corresponding processed import data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

[0103] In one embodiment, dynamically configured field configuration information is obtained, and a target field is determined according to the field configuration information, including: displaying a field configuration interface, the field configuration interface including a candidate field area and a field editing area, the candidate field area displays preset fields in a system dictionary, the field editing area includes a historical custom editing field and a newly added field editing area, and the newly added field editing area is used to input newly added fields; receiving a field configuration operation acting on the field configuration interface, generating corresponding field configuration information according to the field configuration operation, the field configuration operation including a selection operation on the candidate field area, a selection operation on the historical custom editing field, and an input operation on the newly added field editing area.

[0104] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining a target statistical analysis algorithm, obtaining a form to be counted that matches the target statistical analysis algorithm, the target statistical analysis algorithm including at least one of a descriptive statistical algorithm, a hypothesis testing algorithm, a correlation analysis algorithm, and a regression analysis algorithm; extracting data to be analyzed corresponding to the target statistical analysis algorithm from the form to be counted, performing operations on the data to be analyzed according to the target statistical analysis algorithm to obtain corresponding analysis results, and displaying the analysis results in the form of statistical analysis images.

[0105] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: obtaining dynamically configured field configuration information, extracting the target field from the field configuration information, and generating a corresponding target form, wherein the target form includes the target field; extracting the diagnosis and treatment stage-associated field associated with the diagnosis and treatment stage from the target field; obtaining the dynamic field value corresponding to the diagnosis and treatment stage-associated field; determining the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value; screening 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; calculating the text matching degree between the diagnosis and treatment stage-associated field and the candidate sub-diagnosis and treatment data, and filtering the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data according to the text matching degree; calculating the field matching degree between each keyword in the target sub-diagnosis and treatment data and the target form field of the target form, identifying the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, and obtaining the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and importing the target import information into the target form as the field value of the matching target form field.

[0106] In one embodiment, when the computer program is executed by the processor, 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 conditional statement and a field statement; obtaining a query result set corresponding to the query string from a database corresponding to the query string, configuring a matching project identifier for the query result set, obtaining a project form of a type corresponding to the project identifier, calculating the project field matching degree between each keyword in the query result set and the project form field of the corresponding project form, identifying a result set keyword that matches the project form field from the query result set according to the project field matching degree, obtaining corresponding target import data from the query result set according to the position of the result set keyword, and importing the target import data into the project form as the field value of the matching project form field.

[0107] In one embodiment, the data to be imported includes target sub-diagnosis and treatment data and at least one data in the query result set. When the computer program is executed by the processor, the following steps are also implemented before the data to be imported is imported into the corresponding form: the data to be imported is processed to obtain corresponding processed imported data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

[0108] In one embodiment, dynamically configured field configuration information is obtained, and a target field is determined according to the field configuration information, including: displaying a field configuration interface, the field configuration interface including a candidate field area and a field editing area, the candidate field area displays preset fields in a system dictionary, the field editing area includes a historical custom editing field and a newly added field editing area, and the newly added field editing area is used to input newly added fields; receiving a field configuration operation acting on the field configuration interface, generating corresponding field configuration information according to the field configuration operation, the field configuration operation including a selection operation on the candidate field area, a selection operation on the historical custom editing field, and an input operation on the newly added field editing area.

[0109] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining a target statistical analysis algorithm, obtaining a form to be counted that matches the target statistical analysis algorithm, the target statistical analysis algorithm including at least one of a descriptive statistical algorithm, a hypothesis testing algorithm, a correlation analysis algorithm, and a regression analysis algorithm; extracting data to be analyzed corresponding to the target statistical analysis algorithm from the form to be counted, performing operations on the data to be analyzed according to the target statistical analysis algorithm to obtain corresponding analysis results, and displaying the analysis results in the form of statistical analysis images.

[0110] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, 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 link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0111] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A dynamic form generation method, the method comprising: Acquire dynamically configured field configuration information, extract target fields from the field configuration information, and generate a corresponding target form, wherein the target form includes the target fields; Extracting a diagnosis and treatment stage associated field associated with the diagnosis and treatment stage from the target field; Obtain the dynamic field value corresponding to the diagnosis and treatment stage associated field; Determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value; Filtering sub-diagnosis and treatment data corresponding to the current diagnosis and treatment stage from the user diagnosis and treatment data as candidate sub-diagnosis and treatment data; Calculating the text matching degree between the diagnosis and treatment stage associated field and the candidate sub-diagnosis and treatment data, and filtering the candidate sub-diagnosis and treatment data to obtain target sub-diagnosis and treatment data according to the text matching degree; 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

2. The method according to claim 1, characterized in that The method further comprises: Acquire a query string, wherein the query string includes a user-defined query expression, wherein the query expression includes at least one query unit, and wherein the query unit includes a conditional statement and a field statement; Acquire a query result set corresponding to the query string from a database corresponding to the query string, configure a matching project identifier for the query result set, and acquire a project form of a type corresponding to the project identifier; Calculate the project field matching degree between each keyword in the query result set and the corresponding project form field of the project form, identify the result set keyword that matches the project form field from the query result set according to the project field matching degree, obtain the corresponding target import data from the query result set according to the position of the result set keyword, and import the target import data into the project form as the field value of the matching project form field.

3. The method according to claim 2, characterized in that The data to be imported includes the target sub-diagnosis and treatment data and at least one data in the query result set, and before importing the data to be imported into the corresponding form, the following is also included: The data to be imported is processed to obtain corresponding processed imported data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

4. The method according to claim 1, characterized in that: The obtaining of the dynamically configured field configuration information 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, the field editing area includes a historical custom editing field and a newly added field editing area, the newly added field editing area is used to enter a newly added field; Receive a field configuration operation acting on the field configuration interface, and generate corresponding field configuration information according to the field configuration operation, wherein the field configuration operation includes a selection operation on the candidate field area, a selection operation on the historical custom edit field, and an input operation on the newly added field edit area.

5. The method according to claim 1, characterized in that The method further comprises: Obtain a target statistical analysis algorithm, and obtain a form to be counted that matches the target statistical analysis algorithm, wherein 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; The data to be analyzed corresponding to the target statistical analysis algorithm are extracted from the table to be counted, the data to be analyzed are calculated according to the target statistical analysis algorithm to obtain corresponding analysis results, and the analysis results are displayed in the form of statistical analysis images.

6. A dynamic form generation device, characterized in that: The device comprises: An acquisition module, used to acquire dynamically configured field configuration information, extract a target field from the field configuration information, and generate a corresponding target form, wherein the target form includes the target field; A dynamic data determination module is used to extract a diagnosis and treatment stage-related field associated with the diagnosis and treatment stage from the target field, obtain a dynamic field value corresponding to the diagnosis and treatment stage-related field, determine the current diagnosis and treatment stage corresponding to the target form according to the dynamic field value, filter 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 field and the candidate sub-diagnosis and treatment data, and filter the target sub-diagnosis and treatment data from the candidate sub-diagnosis and treatment data according to the text matching degree; 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, identify the target keyword matching the target form field from the target sub-diagnosis and treatment data according to the field matching degree, obtain the corresponding target import information from the target sub-diagnosis and treatment data according to the position of the target keyword, and import the target import information into the target form as the field value of the matching target form field.

7. The device according to claim 6, characterized in that The device also includes: The second form import module is used to obtain 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; obtain a query result set corresponding to the query string from a database corresponding to the query string, configure a matching project identifier for the query result set, and obtain a project form of a type corresponding to the project identifier; calculate the project field matching degree between each keyword in the query result set and the project form field of the corresponding project form, identify the result set keyword matching the project form field from the query result set according to the project field matching degree, obtain the corresponding target import data from the query result set according to the position of the result set keyword, and import the target import data into the project form as the field value of the matching project form field.

8. The device according to claim 7, characterized in that The data to be imported includes the target sub-diagnosis and treatment data and at least one data in the query result set, and the device further includes: The processing module is used to process the data to be imported to obtain corresponding processed imported data, wherein the data processing includes at least one of data filtering, data aggregation, and adding fields.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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