Data screening and visual exporting method and device, storage medium and program product

Abstract

The invention discloses a data screening and visual exporting method and device, a storage medium and a program product, and relates to the technical field of medical health data management.The data screening and visual exporting method comprises the steps that multiple dimension screening conditions input by a user are received, structured query is executed, and a target data set is obtained; performing real-time data screening on the target data set based on the multi-dimensional screening conditions to obtain a screened data list, and dynamically rendering and displaying the screened data list in a table form; obtaining a time rule set by a user, and generating a date sequence for the screened data list through the time rule; generating and displaying a dynamic date title based on the date sequence; obtaining a target language set by the user based on the dynamic date title, and switching the language of the dynamic date title through the target language to obtain a switched multi-language title; and combining the screened data list, the dynamic date title and the multi-language title to obtain a structured data set, and exporting the structured data set through an exporting module.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical health data management, and particularly relates to a data filtering and visualized exporting method and device, a storage medium and a program product. BACKGROUND

[0002] With the popularity of medical devices such as ventilator devices, medical institutions or health management platforms need to statistically analyze patient device usage data.

[0003] The prior art uses a data exporting function to achieve this goal, that is, patient device usage data is exported by an existing data exporting tool for subsequent analysis. In the current medical health data management scenario, due to the large number of patients and the variety of device types, the amount of data generated is extremely large. These data not only contain the basic information of patients, but also cover key information such as device operating parameters, performance indicators, and usage time. However, the existing data management method often has difficulty in efficiently processing these complex and multi-dimensional data. On the one hand, the traditional data filtering method can usually only query based on a single condition, and cannot meet the needs of multi-dimensional and flexible filtering, resulting in inaccurate filtering results and difficulty in quickly locating target data. On the other hand, in terms of data display, there is a lack of intuitive and dynamic visualization means, which makes medical staff or data analysts need to spend a lot of time to interpret and understand the data, reducing work efficiency. In addition, in the data exporting link, manual data arrangement is required, which is low in efficiency, and after the date changes, the exporting template needs to be reconfigured, which is cumbersome to operate. SUMMARY

[0004] The main purpose of the present application is to provide a data filtering and visualized exporting method, device, storage medium and program product, aiming to solve the technical problem that the current data platform cannot flexibly and efficiently manage medical data.

[0005] To achieve the above-mentioned purpose, the present application provides a data filtering and visualized exporting method, which is applied to a data management platform, and the data management platform comprises a multi-condition search module, a dynamic date title generation module, a multi-language title switching module and an exporting module. The data filtering and visualized exporting method comprises the following steps: receiving a plurality of dimension filtering conditions input by a user through the multi-condition search module, and performing a structured query to obtain a target data set; calling a backend interface based on the plurality of dimension filtering conditions through the multi-condition search module to perform real-time data filtering on the target data set, obtaining a filtered data list, and dynamically rendering and displaying the filtered data list in a table form; The dynamic date title generation module obtains a time rule set by the user, and generates a date sequence for the filtered data list according to the time rule; A dynamic date title is generated based on the date sequence and displayed; The multi-language title switching module obtains a target language set by the user based on the dynamic date title, and switches the language of the dynamic date title to obtain a switched multi-language title; The filtered data list, the dynamic date title, and the multi-language title are combined to obtain a structured data set, and the structured data set is exported by the export module.

[0006] In an embodiment, the step of calling a backend interface based on multiple dimension filtering conditions by the multi-condition search module to perform real-time data filtering on the target data set to obtain a filtered data list, and dynamically rendering and displaying the filtered data list in a table form includes: The multi-condition search module calls a backend interface to obtain patient information, device parameters, performance indicators, and time range data based on multiple dimension filtering conditions; According to the patient information and the device parameters, a fuzzy matching rule is used to perform target field matching from the target data set to obtain a matching result set; According to the performance indicators and the time range data, the matching result set is subjected to secondary filtering to obtain a filtered data list; The filtered data list is dynamically rendered and displayed in a table form on the interface of the data management platform, wherein the column titles of the table are automatically generated according to the data types, and the row data are dynamically filled according to the filtering results.

[0007] In an embodiment, the step of performing secondary filtering on the matching result set according to the performance indicators and the time range data to obtain a filtered data list includes: According to a preset performance indicator threshold range, the performance indicators of each data in the matching result set are compared; When the performance indicators of the data exceed the preset threshold range, the data is marked as abnormal data, and the abnormal data is excluded from the matching result set to obtain an excluded data set; According to the time range data, the excluded data set is subjected to time range filtering to retain the data within the time range to obtain a filtered data list.

[0008] In an embodiment, the step of obtaining a time rule set by the user by the dynamic date title generation module, and generating a date sequence for the filtered data list according to the time rule includes: obtaining a time rule input by a user through the dynamic date title generation module, the time rule comprising a start date, an end date, and a format requirement of date generation; performing format verification on the time rule; when the format verification on the time rule passes, generating a date sequence for the filtered data list according to the format requirement of date generation between the start date and the end date.

[0009] In an embodiment, after the step of generating a date sequence for the filtered data list according to the format requirement of date generation between the start date and the end date when the format verification on the time rule passes, the method further comprises: detecting whether there is a change in the data in the filtered data list; when detecting that there is a change in the data in the filtered data list, determining whether the time of the changed data is beyond the current date range; when the time of the changed data is beyond the current date range, extending the date sequence to obtain an updated date sequence.

[0010] In an embodiment, the step of obtaining a target language set by a user based on the dynamic date title through the multi-language title switching module, and switching the language of the dynamic date title to the target language to obtain a switched multi-language title comprises: obtaining a target language set by a user based on the dynamic date title through the multi-language title switching module; detecting the type of the target language; according to the type, calling a preset language conversion library to obtain a table header mapping of the target language; switching the language of the dynamic date title to the target language according to the table header mapping, and converting the dynamic date title from a current language to the target language to obtain a switched multi-language title.

[0011] In an embodiment, the step of merging the filtered data list, the dynamic date title, and the multi-language title to obtain a structured data set, and exporting the structured data set through the export module comprises: organizing the data in the filtered data list according to a preset data structure to form a data main part; merging the dynamic date title and the multi-language title as a metadata part of the data set with the data main part to obtain a merged structured data set; performing format verification on the merged structured data set to obtain a format verification result; When the format checking result is that the field is complete, the export module calls a table generation library to encapsulate the merged structured data set according to a preset format, to obtain encapsulated data. The encapsulated data is provided to a user, so that the user downloads or saves the encapsulated data to a specified location.

[0012] In addition, to achieve the above object, the present application also proposes a data screening and visual export device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the data screening and visual export method as described above.

[0013] In addition, to achieve the above object, the present application also proposes a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the data screening and visual export method as described above.

[0014] In addition, to achieve the above object, the present application also provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the data screening and visual export method as described above.

[0015] The one or more technical solutions proposed in the present application have at least the following technical effects: 1) By integrating multiple dimensions of screening conditions such as patient information, device parameters, compliance indicators and time range, users can quickly locate target patients or device groups, avoiding full data browsing. Structured query and real-time backend interface linkage ensure accurate and rapid response of screening results, greatly shortening the data search time of clinical or operational personnel. Based on the time rules set by the user, a continuous date sequence can be automatically generated as a table column title, and the originally scattered time point usage data is intuitively presented in the form of a horizontal time axis. Through the multi-language title switching module, the table header text of non-date fields is replaced in real time according to the user's selected language, while the date title remains unchanged. This meets the localization needs of multi-lingual users and improves the professionalism and usability. The screening results, dynamically generated date columns and multi-language table headers are organically integrated to build a structured data set with clear logic and complete fields, and one-key operation is used to complete data export, improving efficiency.

[0016] 2) Through multi-condition real-time filtering, users can accurately filter the required data based on multiple dimensions without manual filtering. This significantly improves the speed and efficiency of data filtering, allowing users to obtain the required information in a short time. The application of fuzzy matching rules enables more flexible filtering on patient information and device parameter fields, avoiding data omission or misfiltering caused by traditional exact matching. The filtered data is dynamically rendered and displayed in table form, making the information easy to understand. The column titles of the table are automatically generated based on the data type, avoiding the hassle of manually setting or adjusting the column titles. Dynamic filling of row data ensures that users can see the latest results after each filtering, improving the real-time performance of data display and user experience.

[0017] 3) Through the dynamic date title generation module, users can set the start date and end date, as well as the date generation format requirements, so that the date information in the filtered data list can be more clearly presented. The automatic generation of date sequences not only improves the readability of data, but also helps users more intuitively understand the trend of data changes over time. Users only need to make simple settings, and the system can automatically generate date sequences that meet the requirements according to time rules, saving time and effort and improving work efficiency. Through the setting of time rules, users can flexibly choose the format and range of dates. This flexibility allows users to customize data filtering according to specific needs, providing more accurate time dimension analysis and helping to optimize data processing and decision support. The step of format verification of time rules can effectively avoid errors caused by users inputting non-standard date formats. The verification mechanism ensures that the date format entered by the user meets the system requirements, thereby improving the accuracy of the data and avoiding data loss or incorrect parsing due to format problems. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0020] Figure 1 Flowchart provided for Embodiment One of the data filtering and visualization export method of the present application; Figure 2 Flowchart provided for Embodiment Two of the data filtering and visualization export method of the present application; Figure 3The flowchart provided in Embodiment Three of the data screening and visualization exporting method of the present application; Figure 4 The timing diagram provided in Embodiment One of the data screening and visualization exporting method of the present application; Figure 5 The device structure diagram of the hardware running environment involved in the data screening and visualization exporting method in the embodiments of the present application.

[0021] The object implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0022] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and do not limit the present application.

[0023] In order to better understand the technical solutions of the present application, the specific embodiments will be described in detail below with reference to the drawings and the specific embodiments.

[0024] The main solution of the embodiments of the present application is that the data screening and visualization exporting method is applied to a data management platform, and the data management platform comprises a multi-condition search module, a dynamic date title generation module, a multi-language title switching module and an exporting module. The data screening and visualization exporting method comprises: receiving a plurality of dimension filtering conditions input by a user through the multi-condition search module, and performing a structured query to obtain a target data set; calling a backend interface based on the plurality of dimension filtering conditions through the multi-condition search module to perform real-time data screening on the target data set, obtaining a filtered data list, and dynamically rendering and displaying the filtered data list in a table form; obtaining a time rule set by the user through the dynamic date title generation module, and generating a date sequence for the filtered data list through the time rule; generating and displaying a dynamic date title based on the date sequence; obtaining a target language set by the user based on the dynamic date title through the multi-language title switching module, and switching the language of the dynamic date title to obtain a switched multi-language title through the target language; merging the filtered data list, the dynamic date title and the multi-language title to obtain a structured data set, and exporting the structured data set through the exporting module.

[0025] Since the prior art only supports single-condition search, such as searching only by patient name, it cannot meet the multi-dimensional screening requirement; the Excel table header title language is fixed, such as only supporting Chinese or English, which cannot adapt to multi-language users; and the date title is mostly static preset, which cannot be dynamically generated with the data time range, and the date format is not adjustable; when exporting, the user needs to manually arrange the data, which is low in efficiency, and the date needs to be reconfigured after changing, which is cumbersome to operate.

[0026] The application provides a solution, which realizes multi-dimensional screening through a multi-condition search module, integrates conditions such as patient information, device parameters, performance indicators and time ranges, and enables a user to quickly locate target data and avoid full-volume browsing. A dynamic date title generation module supports user-defined starting date, ending date and format requirements, automatically generates a continuous date sequence as a table column title, and intuitively presents the trend of data change over time. A multi-language title switching module allows the user to select a target language, replaces the table header text of non-date fields in real time, keeps the date title unchanged, and meets the needs of multi-lingual users. An export module combines the filtered data, dynamic date title and multi-language title into a structured data set, supports one-key export, does not need to be manually arranged, and improves efficiency. The solution solves the problems of single-condition search, fixed language, static date preset and complicated export in the prior art, optimizes the data processing process, and improves the user experience.

[0027] It should be noted that the execution subject of the embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone or the like, or an electronic device, a data management platform or the like capable of realizing the above functions. The embodiment and the following embodiments will be described below by taking the data management platform as an example.

[0028] Based on this, the embodiment of the application provides a data screening and visualized export method, which refers to Figure 1 , Figure 1 FIG. 1 is a flowchart of a data screening and visualized export method according to a first embodiment of the application.

[0029] In the embodiment, the data screening and visualized export method includes steps S10-S40: Step S10: receiving a plurality of dimension screening conditions input by a user through the multi-condition search module, and performing a structured query to obtain a target data set.

[0030] It should be noted that the method of the embodiment is applied to a data management platform, and the data platform is mainly a medical health data management platform. The data management platform includes a multi-condition search module, a dynamic date title generation module, a multi-language title switching module and an export module.

[0031] The multi-condition search module is used to provide an interactive interface and support the user to screen data through multi-dimensional combined conditions. The multi-condition search module is also used for time sequence association, that is, the data after screening is taken as the input of the dynamic date title generation module to trigger date sequence calculation.

[0032] It should be noted that since the multi-condition search module can provide an interactive interface, the user can input multiple dimension filtering conditions on this interactive interface, which can specifically include patient information, device parameters, adherence indicators, and time ranges, etc. These filtering conditions can comprehensively cover multiple key aspects of data management, ensuring that the user can accurately locate the required target data set. After receiving the multiple dimension filtering conditions input by the user, the multi-condition search module performs a structured query operation to filter out the target data set that meets all the conditions from the vast data set. This process is not only efficient, but also ensures the accuracy and integrity of the data, laying a solid foundation for subsequent data processing and analysis.

[0033] It can be understood that the multi-condition search module can automatically convert the multi-dimension combination conditions input by the user into structured query logic, so as to query the stored target data set through the structured query statement.

[0034] The target data set can contain patient information, device operation data, performance indicator records, and time stamp key fields, and the combination of these fields provides the user with a comprehensive and detailed data view.

[0035] Step S20: Real-time data filtering of the target data set based on multiple dimension filtering conditions is performed by the multi-condition search module calling the backend interface, and a filtered data list is obtained, and the filtered data list is dynamically rendered and displayed in table form.

[0036] After obtaining the target data set, the multi-condition search module further calls the backend interface to perform real-time data filtering of the target data set based on the multiple dimension filtering conditions set by the user. This step ensures the timeliness and accuracy of the filtering result, so that the user can obtain the latest and most relevant data. During the filtering process, the system dynamically excludes data records that do not meet the conditions, and only retains data items that meet all the filtering conditions to form a filtered data list, which contains all data records that meet the conditions.

[0037] Subsequently, the filtered data list is dynamically rendered in table form on the interface of the data management platform, and the filtered data list is dynamically rendered and displayed in table form on the interface. This dynamic rendering method not only makes the data display more intuitive, but also can update the data content in real time, ensuring that the user always sees the latest filtering result.

[0038] Step S30: Obtain the time rule set by the user through the dynamic date title generation module, and generate a date sequence for the filtered data list through the time rule.

[0039] To meet the user's demand for data time dimension analysis, the application further provides a dynamic date title generation module. This module allows users to customize the start date, end date, and date generation format requirements. The dynamic date title generation module is used to automatically generate a continuous date sequence based on the time interval of the filtered data list or the user-selected time rule. For example, if the time interval of the filtered data list is the last 30 days, a sequence of the last 30 days is automatically generated. If the user provides a custom preview range, such as the last 10 days, a continuous date sequence can be generated based on the user's custom preview range.

[0040] Step S40: generating dynamic date titles based on the date sequence and displaying.

[0041] It should be noted that after generating the date sequence, the dynamic date title generation module will further generate dynamic date titles based on these sequences. These titles not only clearly show the time range of the data, but also can be flexibly adjusted according to the user's date format requirements. For example, the user can choose to display the date in the format of "year-month-day", or choose other formats that meet their needs. The generated dynamic date title will be displayed in real time on the interface of the data management platform, corresponding to the filtered data list, so that the user can intuitively see the trend of data changes over time. This dynamically generated date title not only improves the readability of the data, but also provides users with a more convenient time dimension analysis tool.

[0042] At the same time, the generated dynamic date title is also bound to the user's search data, serving as the field mapping basis for the multi-language title switching module.

[0043] Step S50: obtaining the target language set by the user based on the dynamic date title through the multi-language title switching module, and switching the language of the dynamic date title to the target language to obtain the switched multi-language title.

[0044] It should be noted that data management often needs to meet the needs of users of different languages. The multi-language title switching module is designed to solve this problem. Users can choose the target language, such as English, French, Spanish, etc., based on their own needs on the basis of the dynamic date title. The multi-language title switching module will receive the target language information set by the user and automatically switch the language of the dynamic date title to the language specified by the user, generating the switched multi-language title. This process does not require the user to manually translate or modify, greatly improving the efficiency and convenience of data management. At the same time, the multi-language title switching module will preserve the original format and content of the date title when switching languages, only switching the language, ensuring the accuracy and consistency of the data.

[0045] Specifically, the multilingual title switching module allows for language configuration, such as providing a language switching entry in the upper right corner of the interface, offering options like Simplified Chinese, English, and Español, and supporting one-click switching for users.

[0046] In one feasible implementation, step S50 may include steps A11 to A14: Step A11: Obtain the target language set by the user based on the dynamic date title through the multilingual title switching module; It's worth noting that when managing data, users can easily find clear language switching indicators on the data management platform interface, such as the language switch button prominently located in the upper right corner. Clicking this button will bring up a drop-down menu with multiple language options, clearly listing common languages ​​such as Simplified Chinese, English, and Español. Users can then select their target language, for example, English. Upon receiving the user's selected target language, the multilingual title switching module will quickly initiate the language switching process. This module will precisely locate the dynamic date title section, retaining the original format and content of the date title, such as the specific year, month, day, and time interval, while only switching the language. For example, the dynamic date title that was originally displayed in Chinese as "October 1, 2024 - October 31, 2024" will be accurately displayed as "October 1, 2024 - October 31, 2024" after switching to English, thus obtaining a multilingual title after the switch and meeting the understanding needs of users of different languages ​​for data titles.

[0047] Step A12: Detect the type of the target language; In practice, the target language type refers to the specific language selected by the user. After receiving the user's target language information, the multilingual title switching module uses its built-in language recognition mechanism to accurately detect the target language type. This detection process is fast and accurate, identifying whether the user has selected English, French, Spanish, or other supported languages. For example, when the user selects "Español," the module quickly recognizes it as Spanish, providing an accurate basis for subsequent language switching operations. By detecting the target language type, the multilingual title switching module ensures that the correct language conversion rules and vocabulary correspondences are used when switching languages, thereby generating accurate multilingual titles and providing users with a superior data management experience.

[0048] Step A13: Based on the type, call the preset language conversion library to obtain the header mapping of the target language; It is to be noted that the multi-language title switching module has performed language package management in advance, and has pre-allocated a multi-language library in JSON format. The multi-language library is a pre-set language conversion library, and includes field mapping relationships, i.e., table header mapping, such as patient name→Patient Name→Nombre del Paciente.

[0049] Step A14: Switching the language of the dynamic date title according to the table header mapping, converting the dynamic date title from the current language to the target language, to obtain a switched multi-language title.

[0050] In a specific implementation, after obtaining the table header mapping of the target language, the multi-language title switching module will accurately switch the language of the dynamic date title according to this mapping relationship. It will compare and convert each field in the dynamic date title one by one to ensure that the table header texts of all non-date fields are accurately replaced with the target language, while the date title remains unchanged in format and content. For example, if the dynamic date title originally displays Chinese and includes fields such as “patient name” and “examination date”, when the user selects to switch to English, the module will convert “patient name” to “Patient Name” according to the pre-set language conversion library, and “examination date” will remain unchanged in date format, thereby generating a complete and accurate multi-language title. This process is fully automated and does not require user manual intervention, greatly improving the efficiency and accuracy of data management. At the same time, the multi-language title switching module also supports real-time switching of multiple languages. Users can change the target language at any time on the data management platform interface, and the module will immediately respond and generate the corresponding multi-language title to meet the diverse needs of users of different languages for data titles. Through the user's target language setting, the Excel table header and table column name are updated in real time, and when the user has high-frequency switching needs, the loaded language package can be reused to reduce the call overhead.

[0051] It can be understood that language switching does not affect the generated date title, only the table header text is modified to ensure compatibility with step 4 of the export function.

[0052] Step S60: merging the filtered data list, the dynamic date title, and the multi-language title to obtain a structured data set, and exporting the structured data set through the export module.

[0053] It is to be noted that the export module is a one-key export module that can merge the filtered data list, the dynamic date title, and the multi-language title to construct a structured data set, and can directly export the structured data set.

[0054] In a feasible implementation, step S60 can include steps A21-A23: Step A21: Organize the data in the filtered data list according to the preset data structure to form the data main part; It should be noted that in the process of constructing the structured data set, the data in the filtered data list needs to be systematically organized first. Specifically, the export module will accurately fill each item of data in the filtered data list into the corresponding field position according to the preset data structure template, and embed the preset formula to realize automatic calculation. For example, for a medical health data management platform, the data main part may include patient basic information such as name, age, gender, examination item details such as examination type, examination time, examination result value, equipment operation parameters such as equipment model, operation time, fault code, and key fields, and can also add formula fields such as "age automatic calculation", "examination result abnormality marking", "equipment operation time statistics" and the like. Through this structured organization method, it can ensure that the exported data has a clear logical framework, unified format specification and automatic calculation ability, laying a solid foundation for subsequent data analysis, sharing and application.

[0055] Step A22: Merge the dynamic date title and the multi-language title as the metadata part of the data set with the data main part to obtain the merged structured data set; It should be noted that after completing the structured organization of the data main part, the export module will embed the dynamic date title and the multi-language title as key metadata into the data set. This process is realized through a metadata mapping mechanism, which automatically identifies the time range attributes of the dynamic date title, such as the start date, end date, and language type attributes of the multi-language title, such as Chinese, English, and Spanish, and establishes a correlation relationship between these attributes and the data main part. For example, in the medical data scenario, the dynamic date title "2024-01-01 to 2024-01-31" will be used as time dimension metadata, and the "Patient Name" and "Nombre del Paciente" in the multi-language title will be used as language dimension metadata, forming a three-dimensional structured association with patient examination records and other data main parts. Through this metadata fusion design, the integrity of the data set is ensured, and a standardized interface is provided for subsequent multi-dimensional data analysis, while supporting data tracing and verification in different language environments.

[0056] Step A23: Format verification of the merged structured data set to obtain the format verification result; Specifically, format verification is a mandatory field integrity verification, such as verifying whether the patient's name and device SN are complete, to obtain the format verification result. If the format verification result is that the field is incomplete, a prompt message can be generated to prompt the user to supplement.

[0057] Step A24: When the format verification result is field complete, the export module calls the table generation library to encapsulate the merged structured data set according to the preset format, and obtains encapsulated data; In a specific implementation, if the format verification result is field complete, the export module will immediately start the encapsulation process by calling a professional table generation library, such as Apache POI or OpenXML SDK, to standardize and encapsulate the structured data set according to a pre-set data format template. The template not only defines the arrangement order of data columns, field types such as text type, numerical type, date type, etc., but also includes visual presentation rules such as font style, cell border, background color, etc. For example, in the medical data export scenario, the patient name column may be set to bold Songti 12 font, the examination date column uses automatic line feed format and adds a light gray background, and the abnormal examination result value is highlighted in red font. Through such standardized encapsulation, not only can the exported data maintain consistent visual effects on different terminal devices, but also can automatically detect data format abnormalities such as date format errors and numerical value out of range through pre-set verification rules, and generate detailed error logs for user troubleshooting when problems are found. After encapsulation is completed, the system generates an XML mapping file containing all metadata information, providing technical support for subsequent data tracing and version management.

[0058] Specifically, the data can be encapsulated in the date title column + multi-language table header format to obtain encapsulated data.

[0059] Step A25: The encapsulated data is provided to the user, so that the user can download or save the encapsulated data to a specified location.

[0060] In a specific implementation, the encapsulated data can be displayed on the data management platform, and a download button can be provided. If the encapsulated data is large, a progress bar is returned at the moment of generation, and after encapsulation is completed, a download link is pushed to the front end, so that the user can download or save the encapsulated data according to the link or button.

[0061] The embodiment provides a data screening and visualization export method. By integrating screening conditions of multiple dimensions such as patient information, equipment parameters, compliance indicators and time ranges, a user can quickly locate a target patient or equipment group and avoid full data browsing. Structured query and backend interface real-time linkage ensure accurate screening results and rapid response, greatly shortening the data search time of clinical or operational personnel. Based on the time rules set by the user, a continuous date sequence can be automatically generated as a table column title, and the originally scattered time point usage data is intuitively presented in the form of a horizontal time axis. Through a multi-language title switching module, the table header text of non-date fields is replaced in real time according to the user's selected language, while the date title remains unchanged. The localization needs of multi-lingual users are met, and the professionalism and usability are improved. The screening results, dynamically generated date columns and multi-language table headers are organically integrated to build a structured data set with clear logic and complete fields. Data export is completed through one-key operation, improving efficiency.

[0062] Based on the first embodiment of the application, in the second embodiment of the application, the same or similar contents as the above-mentioned first embodiment can refer to the above introduction, and the following will not be repeated. On this basis, please refer to Figure 2 , step S20 includes steps S201-S204: Step S201: calling a backend interface based on multiple dimension screening conditions to obtain patient information, equipment parameters, performance indicators and time range data through the multi-condition search module.

[0063] It should be noted that the multi-condition search module, as the core component of data screening, is designed with a modular architecture, which realizes efficient interaction with the backend database through standardized interfaces. This module supports setting multiple screening dimensions at the same time: patient dimensions include age range, gender, diagnosis type and other basic attributes; equipment dimensions cover equipment model, running time, treatment mode, maintenance record and other technical parameters; performance dimensions include cumulative, actual, effective use days, single-day time threshold, compliance level, i.e. compliant / non-compliant / non-use; and time dimensions support custom start date, end date and time granularity, such as daily / weekly / monthly aggregation.

[0064] In a specific implementation, when a user configures a screening condition through a front-end interactive interface, the module automatically converts unstructured input into a standard query statement, for example, converting "CT device with detection accuracy higher than 95% in the past three months" into a three-tuple query condition containing a time range, a device type, and a performance indicator. After the back-end interface receives the query request, it starts a distributed query engine and scans the patient information library, the device operation log library, and the performance monitoring library in parallel, and converts full table scanning into index lookup through index optimization technology. When the query result is returned, the module automatically performs a data cleaning process, including de-duplication processing such as merging multiple maintenance records of the same device, missing value filling, replacing missing performance indicators with industry averages, and correcting abnormal values, marking parameter values exceeding the theoretical limit of the device as error data, and finally generating a standardized dataset containing patient ID, device serial number, performance score, and valid time range, providing basic data support for subsequent dynamic date title generation and multi-language title switching.

[0065] The present embodiment supports free combination of 10+ search dimensions such as "device model = iBreeze 20C + compliance level = All + time range = 30 days" for patient information, device parameters, compliance indicators, etc., breaking through the limitations of traditional single-condition search and reducing manual screening time.

[0066] Step S202: Perform target field matching from the target dataset according to the patient information and the device parameters using a fuzzy matching rule to obtain a matching result set.

[0067] It should be noted that for patient information and device parameters, a fuzzy matching rule is used to find fields in the dataset that match the user input conditions. For example, fuzzy query can be implemented through string matching, regular expressions, or keyword matching. Through fuzzy matching, a new matching result set is obtained. This matching result set contains all entries that meet the patient information and device parameters.

[0068] Let the patient information be P1, P2,..., P k , the device parameters be E1, E2,..., E l , the target dataset be D = {d1, d2,..., d m}, and the matching result set M obtained after fuzzy matching can be represented as: Step S203: Perform secondary screening on the matching result set according to the performance indicator and the time range data to obtain a screening data list.

[0069] After fuzzy matching, the matching result set obtained still needs to be further screened to ensure compliance with performance indicators and time ranges. Based on certain performance standards, such as the response speed, accuracy, etc. of the device, the matching result set is filtered. According to the time range specified by the user, such as the past week, the past month, etc., data that meets the time range is further screened out.

[0070] In a feasible implementation, step S203 can include steps B11-B13: Step B11: According to the preset performance indicator threshold range, the performance indicators of each data in the matching result set are compared; It should be noted that the preset performance indicator threshold range is a key standard for measuring whether the performance of the device or patient is up to standard. In step B11, the system will compare each data in the matching result set one by one to see if its performance indicators fall within the preset threshold range. For example, for medical devices, performance indicators can include detection accuracy, response time, failure rate, etc. of the device, and the preset threshold range can be set according to industry standards or clinical needs. Through comparison, the system can filter out data whose performance indicators meet the requirements, providing a basis for subsequent screening.

[0071] Step B12: When the performance indicators of the data exceed the preset threshold range, the data is marked as abnormal data, and the abnormal data is excluded from the matching result set to obtain an excluded data set; It can be understood that when the performance indicators of the data exceed the preset threshold range, it means that these data may not meet the established standards or requirements, and may have errors, faults or other abnormal situations. In order to ensure the accuracy and reliability of the screened data list, the system will automatically mark these data that exceed the threshold range as abnormal data. Subsequently, these abnormal data will be excluded from the matching result set, thereby obtaining a more pure and required excluded data set. This step is of great significance to improve data quality and reduce interference factors in subsequent analysis.

[0072] Step B13: According to the time range data, the excluded data set is screened by time range, and data within the time range is retained to obtain a screened data list.

[0073] After obtaining the filtered data set, the system also needs to further filter the data according to the time range specified by the user. The time range is an important filtering condition, which can help users quickly locate the data in a specific time period, so as to more accurately analyze and make decisions. The system will compare the time of each data in the filtered data set with the time range input by the user, and only keep the data that falls within the specified time range. Finally, after this step of filtering, the system will get a filtered data list that meets the user's requirements, which will be used as the basis data for subsequent dynamic date title generation and multi-language title switching.

[0074] Step S204: dynamically render the filtered data list in table form on the interface of the data management platform, where the column titles of the table are automatically generated according to the data types, and the row data are dynamically filled according to the filtering results.

[0075] According to the filtering results, the data can be displayed in table form. The column titles of the table are usually automatically generated according to the types of the filtered data, such as patient name, device model, performance indicator, etc. Fill in the row data: dynamically fill in the rows of the table according to the filtered data.

[0076] For dynamic rendering, matching records can be displayed in the table, including patient name, device SN, model, treatment mode, compliance indicator, and time axis usage data, etc.

[0077] This embodiment can accurately filter the required data based on multiple dimensions through multi-condition real-time filtering, without the need for manual filtering. It significantly improves the speed and efficiency of data filtering, allowing users to obtain the required information in a short time. The application of fuzzy matching rules allows more flexible filtering on patient information and device parameter fields, avoiding data omission or misfiltering caused by traditional exact matching. The filtered data is dynamically rendered and displayed in table form, making the information easy to understand. The column titles of the table are automatically generated according to the data types, avoiding the trouble of manually setting or adjusting the column titles. The dynamically filled row data ensures that users can see the latest results after each filtering, improving the real-time performance of data display and user experience.

[0078] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as the above-mentioned first embodiment can be referred to the above introduction, and the following will not be repeated. On this basis, please refer to Figure 3 , step S30 includes steps S301-S303: Step S301: Obtain the time rule input by the user through the dynamic date title generation module, the time rule including the start date, the end date and the format requirement of the date generation.

[0079] It should be noted that when the user inputs the time rule through the front-end interactive interface, the system will provide a visual configuration panel to support three date generation modes: fixed cycle mode, such as generating according to natural months, dynamic interval mode, such as generating a title every 7 days, and custom rule mode, such as skipping holidays. Taking the medical scenario as an example, the user can select "generate according to treatment cycle" and set "start date as first treatment date, end date as last treatment date, format requirement as month / day / year or day / month / year", which can be switched in real time through the drop-down menu. The system will automatically parse the rule and generate a continuous date sequence as a table column title. The built-in intelligent verification mechanism in this module will immediately trigger an error prompt and prevent subsequent processes when it detects that the end date is earlier than the start date or the date format does not meet the standard. The generated date title set is stored as an independent metadata layer, which can be called independently for time axis analysis and can also be cross-linked with device parameters, patient information, and other dimensions. In a multi-language environment, the date title remains language-neutral, ensuring semantic consistency in the time dimension when switching between different language table headers.

[0080] Step S302: Format verification is performed on the time rule.

[0081] In specific implementation, the format verification is to judge whether the format input by the user is legal, for example, the user inputs the format as 2023 / 13-32, which indicates that this format is illegal, at this time, a prompt information can be generated, and the prompt information is popped up on the interface, and the default value is restored.

[0082] Specifically, the format rule legality is represented as follows: Wherein, F is the date cycle format, if F is daily, weekly or monthly, the format rule legality verification result is 1, otherwise 0.

[0083] Step S303: When the format verification of the time rule passes, generate a date sequence for the filtered data list according to the format requirement of the date generation between the start date and the end date.

[0084] It should be noted that if the format check of the time rule passes, a continuous date sequence will be automatically generated in the filtered data list according to the start date and end date set by the user, combined with the specified date generation format requirements. This process not only ensures the continuity and accuracy of the date title, but also greatly improves the flexibility and readability of data display. For example, in the medical data analysis scenario, if the user needs to analyze the use of a certain device within a certain time period, only needs to set the start date as the device put into use date and the end date as the current date, and select the weekly generation of date title, the system can automatically generate the corresponding date sequence of each week as the column title of the table, so that the trend of device use over time is clear at a glance. In addition, this date sequence generation mechanism also supports custom date formats to meet the diverse needs of different users and scenarios. The generated date sequence as the table column title, combined with the row data in the filtered data list, together builds a clear structure and easy-to-understand data display framework, providing users with an efficient and convenient data analysis experience.

[0085] In a feasible implementation, if the data is updated, the date sequence can be dynamically expanded, so after step S303, it further includes: detecting whether the data in the filtered data list has changed; when it is detected that the data in the filtered data list has changed, determining whether the time of the changed data is beyond the current date range; when the time of the changed data is beyond the current date range, expanding the date sequence to obtain an updated date sequence.

[0086] It should be noted that if it is detected that the data in the screening data list is updated, the dynamic monitoring mechanism will be started immediately. First, the data change detection algorithm is used to identify the newly added, modified or deleted records, and the specific changed fields are located. When the time attribute of the changed data exceeds the coverage range of the current date sequence, for example, the time of the newly added record is later than the end date or earlier than the start date, the system will automatically trigger the date sequence expansion process. The expansion direction includes extending backward, such as automatically extending to 2024-01-31 when the original end date is 2023-12-31 and the new data is added on 2024-01-05, or tracing back, such as automatically advancing the start date to 2023-01-01 when the new data is added on 2023-01-01. The expansion granularity remains consistent with the original date generation rule. If the original rule is to generate by week, the newly added date sequence will also be incremented by week. The expanded date sequence is updated to the table column header layer at the same time, and the newly added data rows are automatically associated through the data binding mechanism, ensuring the completeness and real-time performance of the table display. This mechanism supports batch data update scenarios. When it is detected that the time attributes of multiple data all exceed the current range, the system will calculate the earliest / latest time points of all changed data, and complete the batch expansion of the date sequence at one time, avoiding performance loss caused by frequent refreshing. After the expansion is completed, the system will notify the user through an interface prompt box that the date sequence has been automatically updated, and highlight the newly added data area to help the user quickly locate the changed content. This dynamic expansion capability enables the data display framework to adapt to the continuously changing data environment, especially suitable for medical device long-term monitoring, patient treatment cycle tracking and other applications that require continuous updates, effectively solving the problem that traditional static date headers cannot adapt to dynamic data growth.

[0087] When data is backtracked, redundant columns can be collapsed, keeping the interface clean.

[0088] Through the dynamic date header generation module, users can set the start date and end date, as well as the generation format requirements of the date, so that the date information in the screening data list can be presented more clearly. The automatic generation of date sequence not only improves the readability of data, but also helps users more intuitively understand the trend of data changes over time. Users only need to make simple settings, and the system can automatically generate date sequences that meet the requirements according to the time rules, saving time and effort and improving work efficiency. Through the setting of time rules, users can flexibly choose the format and range of dates. This flexibility allows users to customize the data according to their specific needs, providing more accurate time dimension analysis and helping to optimize data processing and decision support. The step of format checking of the time rule can effectively avoid errors caused by users inputting non-standard date formats. The checking mechanism ensures that the date format input by the user meets the system requirements, thereby improving the accuracy of the data and avoiding data loss or incorrect parsing due to format problems.

[0089] For example, in order to facilitate the understanding of the implementation process of the data screening and visualization derivation method obtained by combining the above-mentioned embodiment one, please refer to Figure 4 , Figure 4A time sequence diagram of a data screening and visualization export method is provided, specifically: including a user, a front-end interface, a multi-condition search module, a dynamic date title generation module, a multi-language title switching module, an export module, and a back-end server, the back-end server includes data storage and calculation, when the user opens the intelligent search and export page, the front-end page requests page resources such as templates and default configurations from the back-end server, the back-end server returns the page resources to the front-end page, the front-end page displays a function interface including search condition input boxes and language switching entrances, the user inputs or selects search conditions based on the displayed function page, including patient name, device model, treatment mode, etc., the front-end page passes the search conditions in JSON format to the multi-condition search module, the multi-condition search module calls a data query interface and carries the search conditions to the back-end server, the back-end server performs data screening, matches patient device usage data in the database, and returns a data list after screening, including patient / device / adherence information to the multi-condition search module, the multi-condition search module displays the search results on the front-end page and updates the displayed data list, for example, by displaying a table to the user, if the user selects a data interval such as "30 days" or specifies start and end dates, the front-end page passes the data interval / start and end dates to the dynamic title generation module, the dynamic title generation module calculates the date sequence to be displayed, such as "05-21 / 05-22 / . / 05-30", and passes the date sequence to the front-end page, the front-end page generates a date title according to the user's selected format, such as "month / day / year", and displays the dynamic date title to the user, only updating the table column header, if the user clicks the language switching entrance on the front-end page, such as "Simplified Chinese"→"English", the front-end page passes the target language, such as "English", to the multi-language title switching module, the multi-language title switching module calls a multi-language vocabulary, such as "patient name"→"Patient Name", and returns the table header mapping in the target language to the front-end page, the front-end page replaces the Excel header title, such as "patient name"→"Patient Name", and displays the multi-language table header to the user in real time, if the user clicks the one-key export button, the front-end page passes the search results, dynamic date title, and multi-language table header integrated data to the export module, the export module integrates the data, encapsulates it in Excel format, and requests the back-end server to generate an Excel file with the target language as the title and the selected format as the date, the back-end server returns an Excel file download link, the export module passes the download link to the front-end page, and the front-end page displays a download prompt, such as "file generated, click to download", to the user, when the user clicks to download the Excel file, the export is completed.

[0090] It should be noted that the above examples are only used for understanding the present application and do not constitute a limitation on the data screening and visualization exporting method of the present application. More forms of simple transformation based on the technical concept are within the protection scope of the present application.

[0091] The present application provides a data screening and visualization exporting device, which comprises at least one processor and a memory connected in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the data screening and visualization exporting method in the above embodiment one.

[0092] Reference will be made to the following description of the embodiments of the present application, taken in conjunction with the accompanying drawings, in which Figure 5 which shows a structural schematic diagram of a data screening and visualization exporting device suitable for being used to implement the embodiments of the present application. The data screening and visualization exporting device in the embodiments of the present application can include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant), PADs (Portable Application Description), PMPs (Portable Media Player), vehicle-mounted terminals (for example, vehicle-mounted navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 5 The data screening and visualization exporting device shown is only an example and should not bring any limitation on the functions and use range of the embodiments of the present application.

[0093] As Figure 5As shown, the data filtering and visualization exporting device can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to programs stored in a ROM (Read Only Memory) 1002 or programs loaded from a storage device 1003 into a RAM (Random Access Memory) 1004. Various programs and data required for the operation of the data filtering and visualization exporting device are also stored in the RAM 1004. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, an LCD (Liquid Crystal Display), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the data filtering and visualization exporting device to communicate with other devices wirelessly or by wire to exchange data. Although the data filtering and visualization exporting device with various systems is shown in the figure, it should be understood that all the shown systems are not required to be implemented or possessed. More or fewer systems can be alternatively implemented or possessed.

[0094] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are performed.

[0095] The data filtering and visualization exporting device provided by the present disclosure adopts the data filtering and visualization exporting method in the above-mentioned embodiments, and can solve the technical problem that the current data platform cannot flexibly and efficiently manage medical data. Compared with the prior art, the data filtering and visualization exporting device provided by the present disclosure has the same beneficial effects as the data filtering and visualization exporting method provided by the above-mentioned embodiments, and other technical features in the data filtering and visualization exporting device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0096] It should be understood that various aspects of the disclosure can be implemented in hardware, software, firmware, or a combination thereof. In the description of the embodiments above, specific features, structures, materials or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0097] The above description is merely illustrative of the application and is not intended to limit the scope of the application. Any variations and modifications that can be made by any person skilled in the art within the spirit and scope of the application are intended to be encompassed by the application. The scope of the application is defined by the appended claims.

[0098] The application provides a computer readable storage medium having stored thereon computer readable program instructions (i.e. computer programs) for performing the data screening and visualization exporting method in the above embodiments.

[0099] The computer readable storage medium provided by the application may, for example, be a U disk, but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, system or device, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more conductive wires, a portable computer diskette, a hard disk, a RAM (Random Access Memory), a ROM (Read Only Memory), an EPROM (Erasable Programmable Read Only Memory or flash memory), an optical fiber, a CD-ROM (CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer readable storage medium can be transmitted in any suitable medium, including but not limited to electrical wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0100] The above computer readable storage medium can be contained in the data screening and visualization exporting device; or can exist separately and not be assembled into the data screening and visualization exporting device.

[0101] The computer readable storage medium carries one or more programs, when the one or more programs are executed by the data filtering and visualization exporting device, the data filtering and visualization exporting device is caused to: receive a plurality of dimension filtering conditions input by a user through a multi-condition search module, and perform a structured query to obtain a target data set; call a backend interface based on the plurality of dimension filtering conditions to perform real-time data filtering on the target data set through the multi-condition search module to obtain a filtered data list, and dynamically render and display the filtered data list in a table form; obtain a time rule set by the user through a dynamic date title generation module, and generate a date sequence for the filtered data list through the time rule; generate and display a dynamic date title based on the date sequence; obtain a target language set by the user based on the dynamic date title through a multi-language title switching module, and switch the language of the dynamic date title to obtain a switched multi-language title through the target language; merge the filtered data list, the dynamic date title and the multi-language title to obtain a structured data set, and export the structured data set through an exporting module.

[0102] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0103] The flow and block diagrams in the drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flow and block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or combinations of hardware and software.

[0104] The modules involved in the embodiments of the present application can be implemented in software or in hardware. In some cases, the names of the modules do not limit the modules themselves.

[0105] The readable storage medium provided by the present application is a computer readable storage medium, which stores computer readable program instructions (i.e., a computer program) for executing the above-mentioned data screening and visualization exporting method, and can solve the technical problem that the current data platform cannot flexibly and efficiently manage medical data. Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the data screening and visualization exporting method provided by the above-mentioned embodiments, and will not be described here.

[0106] The present application also provides a computer program product comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned data screening and visualization exporting method.

[0107] The computer program product provided by the present application can solve the technical problem that the current data platform cannot flexibly and efficiently manage medical data. Compared with the prior art, the computer program product provided by the present application has the same beneficial effects as the data screening and visualization exporting method provided by the above-mentioned embodiments, and will not be described here.

[0108] The above only describes some embodiments of the present application, and does not limit the patent scope of the present application, and any equivalent structural transformation made by using the content of the present application specification and drawings, or direct / indirect application in other related technical fields is included in the patent protection scope of the present application.

Claims

1. A method for data filtering and visualization export, characterized in that, The data filtering and visualization export method is applied to a data management platform, which includes: a multi-condition search module, a dynamic date title generation module, a multi-language title switching module, and an export module. The data filtering and visualization export methods include: The multi-condition search module receives multiple filtering conditions input by the user and executes a structured query to obtain the target dataset. The multi-condition search module calls the backend interface to perform real-time data filtering on the target dataset based on multiple dimensions of filtering conditions, obtains a filtered data list, and dynamically renders and displays the filtered data list in table form. The dynamic date title generation module obtains the user-set time rules and generates a date sequence from the filtered data list based on the time rules. Generate and display dynamic date titles based on the date sequence; The multilingual title switching module obtains the target language set by the user based on the dynamic date title, and switches the language of the dynamic date title using the target language to obtain the switched multilingual title. The filtered data list, the dynamic date title, and the multilingual title are merged to obtain a structured dataset, which is then exported through the export module.

2. The method as described in claim 1, characterized in that, The step of calling the backend interface through the multi-condition search module to perform real-time data filtering on the target dataset based on multiple dimensions of filtering conditions, obtaining a filtered data list, and dynamically rendering and displaying the filtered data list in tabular form includes: The multi-condition search module calls the backend interface to obtain patient information, equipment parameters, performance indicators, and time range data based on multiple dimensions of filtering conditions; Based on the patient information and the device parameters, fuzzy matching rules are used to match the target fields from the target dataset to obtain a matching result set; The matching result set is further filtered based on the performance indicators and the time range data to obtain a filtered data list. The filtered data list is dynamically rendered and displayed in a table format on the data management platform interface. The column headers of the table are automatically generated according to the data type, and the row data is dynamically filled according to the filtering results.

3. The method as described in claim 2, characterized in that, The step of performing secondary filtering on the matching result set based on the performance indicators and the time range data to obtain a filtered data list includes: Based on a preset performance index threshold range, the performance index of each data item in the matching result set is compared. When the performance indicators of the data exceed a preset threshold range, the data is marked as abnormal data and removed from the matching result set to obtain the removed dataset. The dataset to be removed is filtered by time range based on the time range data, and the data within the time range is retained to obtain a filtered data list.

4. The method as described in claim 1, characterized in that, The step of obtaining user-defined time rules through the dynamic date title generation module and generating a date sequence from the filtered data list using the time rules includes: The system obtains the time rules input by the user through the dynamic date title generation module. The time rules include the start date, end date, and date generation format requirements. Perform format validation on the time rules; When the format validation of the time rule passes, a date sequence is generated for the filtered data list between the start date and the end date according to the date generation format requirements.

5. The method as described in claim 4, characterized in that, After the step of generating a date sequence for the filtered data list according to the date generation format requirements between the start date and the end date when the format validation of the time rule passes, the method further includes: Detect whether there are any changes in the data in the filtered data list; When changes are detected in the filtered data list, it is determined whether the time of the changed data exceeds the current date range; If the time of the changed data exceeds the current date range, the date sequence is expanded to obtain an updated date sequence.

6. The method as described in claim 1, characterized in that, The step of obtaining the target language set by the user based on the dynamic date title through the multilingual title switching module, and switching the language of the dynamic date title through the target language to obtain the switched multilingual title includes: The multilingual title switching module obtains the user's target language set based on the dynamic date title. Detect the type of the target language; Based on the type, a preset language conversion library is invoked to obtain the header mapping of the target language; The language of the dynamic date title is switched according to the header mapping, and the dynamic date title is converted from the current language to the target language to obtain the switched multilingual title.

7. The method as described in claim 1, characterized in that, The step of merging the filtered data list, the dynamic date title, and the multilingual title to obtain a structured dataset, and exporting the structured dataset through the export module, includes: The data in the filtered data list is organized according to a preset data structure to form the main data body; The dynamic date header and the multilingual header are used as the metadata part of the dataset and merged with the data body part to obtain the merged structured dataset; Perform format validation on the merged structured dataset and obtain the format validation results; When the format verification result indicates that the fields are complete, the export module calls the table generation library to encapsulate the merged structured dataset according to a preset format to obtain encapsulated data. The packaged data is provided to the user so that the user can download or save the packaged data to a specified location.

8. A data filtering and visualization export device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the data filtering and visualization export method as described in any one of claims 1 to 7.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the data filtering and visualization export method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the data filtering and visualization export method as described in any one of claims 1 to 7.

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