Report generation method and device, computer equipment and storage medium
By acquiring and preprocessing users' medical data, performing feature extraction and health assessment, and using the template engine to generate and optimize physical examination reports, the problem of low efficiency and accuracy of physical examination reports in the existing technology is solved, and automated and accurate report generation is achieved.
Patent Information
- Application Number
- CN202510215659.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-26
- Publication Date
- 2025-05-30
AI Technical Summary
The existing physical examination report generation methods are less efficient and accurate, and are susceptible to human factors, resulting in errors and missed examinations.
By obtaining the user's medical data and personal information, preprocessing and feature extraction, using the health assessment model for health assessment, generating reports based on the template engine, and optimizing processing, and finally outputting the automated generated physical examination report.
It realizes the generation of physical examination reports automatically and accurately, improves the efficiency and accuracy of the report generation, and reduces human errors.
Smart Images
Figure CN120072178A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical fields of artificial intelligence development and digital medicine, and particularly to a report generation method, apparatus, computer device, and storage medium. Background Art
[0002] Today, with the rapid development of medical informatization, the processing and analysis methods of physical examination data are undergoing profound changes. The traditional way of generating physical examination reports, that is, doctors manually writing reports, has been difficult to meet the requirements of modern medical systems for efficiency, accuracy, and data security.
[0003] Previously, the generation of physical examination reports mainly relied on doctors' personal experience and handwriting skills. Doctors needed to manually record various physiological indicators of the examinees, make diagnoses based on these data, and finally write a detailed physical examination report. This method is not only time-consuming and laborious, but also prone to errors due to human factors, such as clerical errors, missed detections, or misjudgments, resulting in low efficiency and accuracy in the generation of physical examination reports. Summary of the Invention
[0004] The purpose of the embodiments of this application is to propose a report generation method, apparatus, computer device, and storage medium to solve the technical problem that the existing method for generating physical examination reports has low efficiency and accuracy.
[0005] To solve the above technical problem, the embodiments of this application provide a report generation method, which adopts the following technical solutions:
[0006] Obtain the user's medical data and the user's personal information;
[0007] Preprocess the medical data to obtain corresponding target medical data;
[0008] Perform feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data;
[0009] Perform a health assessment process on the target feature data and the personal information based on a preset health assessment model to obtain a corresponding health assessment result;
[0010] Perform report generation processing on the health assessment result based on a preset template engine to obtain a corresponding physical examination report;
[0011] Perform report optimization processing on the physical examination report to obtain a corresponding target physical examination report;
[0012] Output the target physical examination report.
[0013] Further, the step of performing feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data specifically includes:
[0014] Performing feature extraction processing on the image data in the target medical data based on a preset first feature extraction model to obtain corresponding first feature data;
[0015] Performing feature extraction processing on the time series data in the target medical data based on a preset second feature extraction model to obtain corresponding second feature data;
[0016] Performing integration processing on the first feature data and the second feature data to obtain corresponding integrated data;
[0017] Taking the integrated data as the target feature data.
[0018] Further, the step of performing report generation processing on the health assessment result based on a preset template engine to obtain a corresponding physical examination report specifically includes:
[0019] Obtaining a preset physical examination report template;
[0020] Performing combination processing on the health assessment result and the physical examination report template based on the template engine to obtain a corresponding initial physical examination report;
[0021] Performing information verification on the initial physical examination report;
[0022] If the initial physical examination report passes the information verification, taking the initial physical examination report as the physical examination report.
[0023] Further, the step of performing report optimization processing on the physical examination report to obtain a corresponding target physical examination report specifically includes:
[0024] Obtaining a preset adjustment strategy;
[0025] Performing content personalization adjustment on the physical examination report based on the adjustment strategy to obtain a corresponding first physical examination report;
[0026] Performing language optimization processing on the first physical examination report based on a preset language optimization tool to obtain a corresponding second physical examination report;
[0027] Taking the second physical examination report as the target physical examination report.
[0028] Further, the step of outputting the target physical examination report specifically includes:
[0029] Invoking a preset chart tool;
[0030] Perform data conversion processing on the target physical examination report based on the chart tool to obtain a third physical examination report containing graphic data;
[0031] Call a preset target interface;
[0032] Display the third physical examination report in the target interface.
[0033] Further, the step of preprocessing the medical data to obtain corresponding target medical data specifically includes:
[0034] Perform cleaning processing on the medical data to obtain corresponding first medical data;
[0035] Convert the first medical data into a preset standard format to obtain corresponding second medical data;
[0036] Perform normalization processing on the second medical data to obtain corresponding third medical data;
[0037] Use the third medical data as the target medical data.
[0038] Further, after the step of performing report optimization processing on the physical examination report to obtain a corresponding target physical examination report, it further includes:
[0039] Obtain a preset encryption policy;
[0040] Perform encryption processing on the target physical examination report based on the encryption policy to obtain a corresponding fourth physical examination report;
[0041] Obtain a preset target sending method;
[0042] Send the fourth physical examination report to the user based on the target sending method.
[0043] To solve the above technical problems, an embodiment of the present application further provides a report generation device, which adopts the following technical solutions:
[0044] A first acquisition module, configured to acquire the user's medical data and the user's personal information;
[0045] A preprocessing module, configured to preprocess the medical data to obtain corresponding target medical data;
[0046] An extraction module, configured to perform feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data;
[0047] An evaluation module, configured to perform a health evaluation process on the target feature data and the personal information based on a preset health evaluation model, so as to obtain a corresponding health evaluation result;
[0048] A generation module, configured to perform a report generation process on the health evaluation result based on a preset template engine, so as to obtain a corresponding physical examination report;
[0049] An optimization module, configured to perform a report optimization process on the physical examination report, so as to obtain a corresponding target physical examination report;
[0050] An output module, configured to output the target physical examination report.
[0051] To solve the above technical problems, an embodiment of the present application further provides a computer device, which adopts the following technical solutions:
[0052] Obtain the medical data of the user and obtain the personal information of the user;
[0053] Preprocess the medical data to obtain corresponding target medical data;
[0054] Perform a feature extraction process on the target medical data based on a preset feature extraction model to obtain corresponding target feature data;
[0055] Perform a health evaluation process on the target feature data and the personal information based on a preset health evaluation model to obtain a corresponding health evaluation result;
[0056] Perform a report generation process on the health evaluation result based on a preset template engine to obtain a corresponding physical examination report;
[0057] Perform a report optimization process on the physical examination report to obtain a corresponding target physical examination report;
[0058] Output the target physical examination report.
[0059] To solve the above technical problems, an embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solutions:
[0060] Obtain the medical data of the user and obtain the personal information of the user;
[0061] Preprocess the medical data to obtain corresponding target medical data;
[0062] Perform a feature extraction process on the target medical data based on a preset feature extraction model to obtain corresponding target feature data;
[0063] Perform a health assessment process on the target feature data and the personal information based on a preset health assessment model to obtain a corresponding health assessment result;
[0064] Perform a report generation process on the health assessment result based on a preset template engine to obtain a corresponding physical examination report;
[0065] Perform a report optimization process on the physical examination report to obtain a corresponding target physical examination report;
[0066] Output the target physical examination report.
[0067] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:
[0068] The present application first obtains the medical data of the user and the personal information of the user; then preprocesses the medical data to obtain corresponding target medical data; then performs a feature extraction process on the target medical data based on a preset feature extraction model to obtain corresponding target feature data; subsequently performs a health assessment process on the target feature data and the personal information based on a preset health assessment model to obtain a corresponding health assessment result; further performs a report generation process on the health assessment result based on a preset template engine to obtain a corresponding physical examination report; and performs a report optimization process on the physical examination report to obtain a corresponding target physical examination report; finally outputs the target physical examination report. By obtaining the medical data of the user and the personal information of the user, preprocessing the medical data to obtain target medical data, then performing a feature extraction process on the target medical data based on the use of a feature extraction model to obtain target feature data, and performing a health assessment process on the target feature data and the personal information based on the use of a pre-health assessment model to obtain a corresponding health assessment result, and then performing a report generation process on the health assessment result based on the use of a template engine to obtain a corresponding physical examination report, and subsequently performing a report optimization process on the physical examination report to obtain a corresponding target physical examination report and outputting it, the present application realizes the automatic and accurate generation of a physical examination report, effectively improving the generation efficiency and accuracy of the physical examination report. BRIEF DESCRIPTION OF THE DRAWINGS
[0069] In order to more clearly illustrate the solutions in the present application, the following will briefly introduce the drawings required for the description of the embodiments of the present application. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0070] Figure 1 is an exemplary system architecture diagram to which the present application can be applied;
[0071] Figure 2Flowchart of an embodiment of the report generation method according to the present application;
[0072] Figure 3 It is a schematic structural diagram of an embodiment of the report generation device according to the present application;
[0073] Figure 4 It is a schematic structural diagram of an embodiment of the computer device according to the present application. Detailed implementation manners
[0074] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second", etc. in the specification and claims of this application or the above drawings are used to distinguish different objects and not to describe a specific order.
[0075] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.
[0076] In order to enable those skilled in the technical field to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.
[0077] As Figure 1 shown, the system architecture 100 may include a terminal device 101, a network 102, and a server 103. The terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. The network 102 is a medium for providing a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.
[0078] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications may be installed on the terminal device 101, such as a web browser application, a shopping application, a search application, an instant messaging tool, an email client, a social platform software, etc.
[0079] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop 1011, tablet computer 1012, or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer, a desktop computer, and so on.
[0080] The server 103 can be a server that provides various services, such as a background server that supports the pages displayed on the terminal device 101.
[0081] It should be noted that the report generation method provided by the embodiments of the present application is generally executed by the server / terminal device. Correspondingly, the report generation device is generally set in the server / terminal device.
[0082] It should be understood that Figure 1 the numbers of the terminal devices, networks, and servers in
[0083] Continue to refer to Figure 2 , which shows a flowchart of an embodiment of the report generation method according to the present application. According to different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted. The report generation method provided by the embodiments of the present application can be applied to any scenario that requires report generation. Then, the report generation method can be applied to the products in these scenarios. For example, the generation of physical examination reports in the field of digital medicine. The described report generation method includes the following steps:
[0084] Step S201, obtain the user's medical data and obtain the user's personal information.
[0085] In this embodiment, the electronic device on which the report generation method runs (such as Figure 1The server / terminal device shown can obtain the user's medical data and personal information through wired or wireless connection methods. It should be noted that the above wireless connection methods can include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future-developed wireless connection methods. The execution entity of this application is specifically a report generation system, or simply referred to as the system. The above medical data can include the user's physical examination data and electronic health records. Specifically, medical devices such as blood pressure monitors, blood glucose meters, and electrocardiographs can be connected through wireless transmission protocols such as Bluetooth and Wi-Fi to automatically obtain the user's physical examination data. And through the API interface, it is integrated with systems such as the hospital information system (HIS) and the laboratory information system (LIS) to import the user's electronic health record (EHR). In addition, the above personal information of the user includes information such as the user's age, gender, family medical history, and living habits.
[0086] Step S202: Preprocess the medical data to obtain corresponding target medical data.
[0087] In this embodiment, the specific implementation process of preprocessing the medical data to obtain corresponding target medical data will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated here too much.
[0088] Step S203: Perform feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data.
[0089] In this embodiment, the specific implementation process of performing feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated here too much.
[0090] Step S204: Perform a health assessment process on the target feature data and the personal information based on a preset health assessment model to obtain a corresponding health assessment result.
[0091] In this embodiment, the above health assessment model is a model pre-constructed according to classification algorithms (such as decision trees, naive Bayes, K-nearest neighbors, etc.) and capable of classifying users into different health status categories based on their medical characteristics and personal information. And the health assessment model also has the function of being able to interpret and explain the classification results to generate health management suggestions matching the classification results.
[0092] By inputting the above-mentioned target feature data and personal information into the health assessment model, the health assessment model will classify the target feature data and personal information and generate corresponding health assessment results. The health assessment results include health status categories and health management suggestions corresponding to the health status categories.
[0093] Step S205: Perform report generation processing on the health assessment results based on a preset template engine to obtain a corresponding physical examination report.
[0094] In this embodiment, for the specific implementation process of performing report generation processing on the health assessment results based on a preset template engine to obtain a corresponding physical examination report, this application will further describe the details in subsequent specific embodiments and will not elaborate too much here.
[0095] Step S206: Perform report optimization processing on the physical examination report to obtain a corresponding target physical examination report.
[0096] In this embodiment, for the specific implementation process of performing report optimization processing on the physical examination report to obtain a corresponding target physical examination report, this application will further describe the details in subsequent specific embodiments and will not elaborate too much here.
[0097] Step S207: Output the target physical examination report.
[0098] In this embodiment, for the specific implementation process of outputting the target physical examination report, this application will further describe the details in subsequent specific embodiments and will not elaborate too much here.
[0099] This application first obtains the user's medical data and the user's personal information; then preprocesses the medical data to obtain the corresponding target medical data; then performs feature extraction processing on the target medical data based on a preset feature extraction model to obtain the corresponding target feature data; subsequently performs a health assessment process on the target feature data and the personal information based on a preset health assessment model to obtain the corresponding health assessment result; further performs a report generation process on the health assessment result based on a preset template engine to obtain the corresponding physical examination report; and performs a report optimization process on the physical examination report to obtain the corresponding target physical examination report; finally outputs the target physical examination report. By obtaining the user's medical data and the user's personal information, preprocessing the medical data to obtain the target medical data, then performing feature extraction processing on the target medical data based on the use of the feature extraction model to obtain the target feature data, and performing a health assessment process on the target feature data and the personal information based on the use of the pre-health assessment model to obtain the corresponding health assessment result, and then performing a report generation process on the health assessment result based on the use of the template engine to obtain the corresponding physical examination report, and subsequently performing a report optimization process on the physical examination report to obtain the corresponding target physical examination report and outputting it, this application can automatically and accurately complete the generation of the physical examination report, effectively improving the generation efficiency and accuracy of the physical examination report.
[0100] In some alternative implementation manners, step S203 includes the following steps:
[0101] Performs feature extraction processing on the image data in the target medical data based on a preset first feature extraction model to obtain the corresponding first feature data.
[0102] In this embodiment, the above-mentioned target medical data may include image data (such as X-ray films, MRI images) and time series data (such as electrocardiograms, blood pressure monitoring data, etc.). The above-mentioned first feature extraction model may specifically adopt a CNN (Convolutional Neural Network) model suitable for image data processing, such as ResNet, Inception, etc. as the basic model.
[0103] The construction process of the above-mentioned first feature extraction model includes: obtaining image data such as X-ray films and MRI images from medical institutions, then performing processing such as cropping, scaling, and normalization on the image data to ensure that the data meets the input requirements of the CNN model. At the same time, annotating the key areas or lesions in the image data to provide labels for supervised learning. Then using the preprocessed image data and the corresponding labels to train the CNN model so that it can accurately identify the key features in the image, thereby obtaining the trained first feature extraction model.
[0104] Subsequently, by using the trained first feature extraction model to extract features from the image data in the target medical data, a high-level feature representation is obtained, that is, the above-mentioned first feature data is obtained.
[0105] Based on a preset second feature extraction model, feature extraction processing is performed on the time series data in the target medical data to obtain corresponding second feature data.
[0106] In this embodiment, the above-mentioned second feature extraction model can specifically adopt an LSTM (Long Short-Term Memory network) model suitable for time series data processing, or a combination of LSTM and other models (such as LSTM + GRU).
[0107] The construction process of the above-mentioned second feature extraction model includes: obtaining time series data from electrocardiogram devices, health monitoring devices, etc., such as electrocardiograms, blood pressure monitoring data, etc. Then, denoising, smoothing, standardization, etc. are performed on the time series data to ensure the accuracy and consistency of the data. At the same time, the data is divided into a training set, a validation set, and a test set according to requirements. Furthermore, the preprocessed time series data is used to train the LSTM model so that it can capture the time series features and trends in the data, thereby obtaining the trained second feature extraction model.
[0108] Subsequently, by using the trained second feature extraction model to perform feature extraction processing on the time series data in the target medical data, a time series feature vector is obtained, that is, the above-mentioned second feature data is obtained.
[0109] Integrate the first feature data and the second feature data to obtain corresponding integrated data.
[0110] In this embodiment, the above-mentioned integrated data includes the first feature data and the second feature data.
[0111] Use the integrated data as the target feature data.
[0112] In this application, feature extraction processing is performed on the image data in the target medical data based on a preset first feature extraction model to obtain corresponding first feature data; and feature extraction processing is performed on the time series data in the target medical data based on a preset second feature extraction model to obtain corresponding second feature data; then the first feature data and the second feature data are integrated to obtain corresponding integrated data; subsequently, the integrated data is used as the target feature data. By combining the use of the first feature extraction model and the second feature extraction model, this application respectively performs feature extraction on the image data in the target medical data to obtain corresponding first feature data, and performs feature extraction on the time series data in the target medical data to obtain corresponding second feature data, effectively improving the feature extraction processing ability for the target medical data. Subsequently, integrating the first feature data and the second feature data can achieve quickly and accurately obtaining the corresponding target feature data, ensuring the accuracy of the obtained target feature data.
[0113] In some optional implementation manners of this embodiment, step S205 includes the following steps:
[0114] Obtain a preset physical examination report template.
[0115] In this embodiment, according to actual business requirements, a set of physical examination report templates is designed in advance. The physical examination report template includes key content areas such as health status assessment and health management suggestions, and placeholder for data filling is reserved. Among them, during the design process of the physical examination report template, it is necessary to ensure the unity and professionalism of the report format, and at the same time consider the user's reading experience.
[0116] Based on the template engine, combine the health assessment result with the physical examination report template to obtain a corresponding initial physical examination report.
[0117] In this embodiment, there is no specific limitation on the selection of the above template engine. For example, Thymeleaf or Freemarker can be used. The template engine can parse the placeholders in the template and fill the prepared data into the corresponding positions. By using the rendering function of the template engine, the prepared health assessment result can be combined with the above physical examination report template to automatically generate a physical examination report including content such as health status assessment and health management suggestions.
[0118] Perform information verification on the initial physical examination report.
[0119] In this embodiment, the above information verification includes verifying whether the language expression of the generated initial physical examination report is clear and easy to understand to ensure the accuracy and integrity of the information in the initial physical examination report.
[0120] If the initial physical examination report passes the information verification, then use the initial physical examination report as the physical examination report.
[0121] In this embodiment, based on the obtained health status assessment and health management suggestions, it is possible to further help the user formulate a reasonable health management plan. Continuously optimize the content and form of the report according to the user's feedback to continuously improve the service quality. And cooperate with professionals such as dietitians and fitness coaches to provide the user with comprehensive health management suggestions and improve the overall service level.
[0122] This application obtains a preset physical examination report template; then combines and processes the health assessment results with the physical examination report template based on the template engine to obtain a corresponding initial physical examination report; subsequently, performs information verification on the initial physical examination report; if the initial physical examination report passes the information verification, then use the initial physical examination report as the physical examination report. By using the template engine to combine and process the generated health assessment results with the obtained physical examination report template, this application can automatically and accurately generate the corresponding initial physical examination report, improving the generation efficiency of the physical examination report. In addition, it will also intelligently perform information verification on the initial physical examination report to ensure the information accuracy and integrity of the generated physical examination report.
[0123] In some alternative implementation manners, step S206 includes the following steps:
[0124] Obtain a preset adjustment strategy.
[0125] In this embodiment, the strategy content of the above adjustment strategy includes: report content adjustment, language style optimization, and personalized element addition processing. Specifically, the report content adjustment includes: making corresponding adjustments to the report content according to the user's personal information. For example, for users of different age groups, provide targeted health suggestions; for users with a family medical history, add relevant disease warning information. The language style optimization includes: considering the user's reading habits and comprehension ability, adjusting the language style of the report. For older users or users with weaker comprehension abilities, use a more concise and easy-to-understand language expression; for younger users, appropriately add some professional terms and detailed explanations. The personalized element addition includes: adding some personalized elements in the report, such as the user's name, photo, etc., to increase the exclusivity and affinity of the report.
[0126] Perform content personalization adjustment on the physical examination report based on the adjustment strategy to obtain a corresponding first physical examination report.
[0127] In this embodiment, the content of the physical examination report can be personalized adjusted according to the strategy content of the above adjustment strategy, so as to obtain a corresponding first physical examination report.
[0128] Perform language optimization processing on the first physical examination report based on a preset language optimization tool to obtain a corresponding second physical examination report.
[0129] In this embodiment, the above language optimization tool may specifically include a natural language processing tool, a sentiment analysis tool, and a text generation tool. The process of performing language optimization processing on the first physical examination report based on the language optimization tool may include: using the natural language processing tool to check the language fluency of the report, discovering and correcting grammar errors, spelling mistakes, etc. Analyze the language expressions in the report through the sentiment analysis tool to ensure that the information transmission meets the emotional needs of the user. For example, for disease warning information, use a more gentle and encouraging language expression to avoid bringing excessive anxiety and stress to the user. And use the text generator to perform automatic or semi-automatic text generation on some parts of the report, such as health suggestions, disease prevention measures, etc. These generated texts should be manually reviewed and modified to ensure their accuracy and applicability.
[0130] Use the second physical examination report as the target physical examination report.
[0131] This application obtains a preset adjustment strategy; then performs content personalization adjustment on the physical examination report based on the adjustment strategy to obtain a corresponding first physical examination report; then performs language optimization processing on the first physical examination report based on a preset language optimization tool to obtain a corresponding second physical examination report; subsequently, use the second physical examination report as the target physical examination report. This application performs content personalization adjustment on the physical examination report based on the use of the adjustment strategy to obtain a corresponding first physical examination report, and then performs language optimization processing on the first physical examination report based on the use of the language optimization tool, so as to efficiently and accurately complete the report optimization processing of the physical examination report, making the language expression in the physical examination report more natural and user-friendly, easy for users to understand, and effectively improving the professionalism and personalization of the generated target physical examination report.
[0132] In some alternative implementation manners, step S207 includes the following steps:
[0133] Call a preset chart tool.
[0134] In this embodiment, there is no specific limitation on the selection of the above chart tool. For example, any one of tools such as ECharts and D3.js can be used.
[0135] Perform data conversion processing on the target physical examination report based on the chart tool to obtain a third physical examination report containing graphic data.
[0136] In this embodiment, by using the chart tool, complex data can be converted into easy-to-understand graphics, which can help users intuitively grasp their health status.
[0137] Call a preset target interface.
[0138] In this embodiment, the above-mentioned target interface can be a friendly and intuitive user interface designed using a modern front-end framework (such as React or Vue.js), supporting Web-side and mobile-side access.
[0139] Display the third physical examination report in the target interface.
[0140] In this embodiment, the third physical examination report can be displayed in the target interface for users to view.
[0141] This application calls a preset chart tool; then performs data conversion processing on the target physical examination report based on the chart tool to obtain a third physical examination report containing graphic data; then calls a preset target interface; and subsequently displays the third physical examination report in the target interface. By performing data conversion processing on the target physical examination report based on the use of the chart tool, this application obtains a third physical examination report containing graphic data, and then displays the third physical examination report based on the use of the target interface, thereby automatically and intelligently completing the visualization output of the physical examination report and improving the output intelligence of the physical examination report.
[0142] In some optional implementation manners of this embodiment, step S202 includes the following steps:
[0143] Clean the medical data to obtain corresponding first medical data.
[0144] In this embodiment, the above-mentioned cleaning processing includes removing outliers and missing values to ensure the integrity and accuracy of the data.
[0145] Convert the first medical data into a preset standard format to obtain corresponding second medical data.
[0146] In this embodiment, by converting data from different sources into a standard format, it is convenient for subsequent processing and analysis. Specifically, the data is converted into a format suitable for input to a deep learning model, such as converting image data into a pixel matrix of a specific size and converting time series data into a vector or sequence of a fixed length.
[0147] Normalize the second medical data to obtain corresponding third medical data.
[0148] In this embodiment, by normalizing the above-mentioned second medical data, the influence of the dimension can be reduced and the analysis accuracy can be improved. Specifically, according to the distribution characteristics of the data, the data can be standardized or normalized to ensure the comparability of different features in terms of numerical values, thereby avoiding biases in the model training process.
[0149] Use the third medical data as the target medical data.
[0150] In this embodiment, batch processing technology (such as Apache Spark) can be used to preprocess a large amount of medical data, thereby further improving the processing efficiency of the preprocessing.
[0151] This application performs cleaning processing on the medical data to obtain corresponding first medical data; then converts the first medical data into a preset standard format to obtain corresponding second medical data; then performs normalization processing on the second medical data to obtain corresponding third medical data; subsequently, the third medical data is used as the target medical data. This application performs cleaning processing, format conversion processing, and normalization processing on medical data, thereby realizing efficient and accurate preprocessing of medical data, and effectively improving the data accuracy and standardization of the generated target medical data.
[0152] In some optional implementation manners of this embodiment, after step S206, the above electronic device may further perform the following steps:
[0153] Obtain a preset encryption policy.
[0154] In this embodiment, the policy content of the above encryption policy includes: using the SSL / TLS protocol for encryption during data transmission, and using encryption algorithms such as AES to protect data security during storage.
[0155] Perform encryption processing on the target physical examination report based on the encryption policy to obtain a corresponding fourth physical examination report.
[0156] In this embodiment, the target physical examination report can be encrypted according to the policy content of the above encryption policy to obtain a corresponding fourth physical examination report.
[0157] Obtain a preset target sending method.
[0158] In this embodiment, the above target sending method may specifically adopt an electronic method, such as email, mobile application notification, etc.
[0159] Send the fourth physical examination report to the user based on the target sending method.
[0160] In this embodiment, the communication address of the user can be obtained, and then based on this communication address, the fourth physical examination report can be sent to the user using the above target sending method.
[0161] In addition, through an identity authentication and authorization mechanism, it can be ensured that only authorized users can access their personal health data.
[0162] This application obtains a preset encryption policy; then encrypts the target physical examination report based on the encryption policy to obtain a corresponding fourth physical examination report; then obtains a preset target sending method; subsequently, based on the target sending method, sends the fourth physical examination report to the user. After optimizing the physical examination report to obtain the corresponding target physical examination report, this application will also automatically and intelligently encrypt the target physical examination report based on the use of the encryption policy to obtain the corresponding fourth physical examination report, and then send the fourth physical examination report to the user based on the obtained target sending method, effectively improving the transmission security and intelligence of the target physical examination report.
[0163] In some alternative implementation manners, the obtained user information has obtained the consent of the user and complies with the provisions of relevant laws and relevant policies.
[0164] In addition, the non-company software tools or components that appear in the embodiments of this application are only introduced by way of example and do not represent actual use.
[0165] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution is prior or subsequent. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
[0166] It should be emphasized that to further ensure the privacy and security of the above-mentioned target physical examination report, the above-mentioned target physical examination report can also be stored in a node of a blockchain.
[0167] The blockchain referred to in this application is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithm. Blockchain, in essence, is a decentralized database, a string of data blocks generated by using cryptographic methods. Each data block contains information about a batch of network transactions, which is used to verify the validity (anti-counterfeiting) of the information and generate the next block. The blockchain can include a blockchain underlying platform, a platform product service layer, and an application service layer, etc.
[0168] The embodiments of this application can obtain and process relevant data based on artificial intelligence technology. Among them, Artificial Intelligence (AI) is to use a digital computer or a machine controlled by a digital computer to simulate, extend, and expand human intelligence, sense the environment, acquire knowledge, and use knowledge to obtain the best results of theory, method, technology, and application systems.
[0169] The basic technologies of artificial intelligence generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation / interaction systems, and mechatronics. The software technologies of artificial intelligence mainly include several major directions such as computer vision technology, robotics, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning.
[0170] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disc, a read-only memory (ROM), etc., or a random access memory (RAM), etc.
[0171] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments. Their execution order is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.
[0172] Further reference Figure 3 to Figure 2 As an implementation of the method shown above, an embodiment of a report generation device is provided in this application. This device embodiment corresponds to the method embodiment shown in Figure 2 and this device can be specifically applied to various electronic devices.
[0173] As Figure 3 shown, the report generation device 300 described in this embodiment includes: a first acquisition module 301, a preprocessing module 302, an extraction module 303, an evaluation module 304, a generation module 305, an optimization module 306, and an output module 307. Among them:
[0174] The first acquisition module 301 is used to acquire the medical data of the user and acquire the personal information of the user;
[0175] The preprocessing module 302 is used to preprocess the medical data to obtain the corresponding target medical data;
[0176] An extraction module 303, configured to perform feature extraction processing on target medical data based on a preset feature extraction model to obtain corresponding target feature data;
[0177] An evaluation module 304, configured to perform a health evaluation process on the target feature data and the personal information based on a preset health evaluation model to obtain a corresponding health evaluation result;
[0178] A generation module 305, configured to perform report generation processing on the health evaluation result based on a preset template engine to obtain a corresponding physical examination report;
[0179] An optimization module 306, configured to perform report optimization processing on the physical examination report to obtain a corresponding target physical examination report;
[0180] An output module 307, configured to output the target physical examination report.
[0181] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the report generation method in the foregoing embodiment, and will not be elaborated herein.
[0182] In some optional implementation manners of this embodiment, the extraction module 303 includes:
[0183] A first extraction sub-module, configured to perform feature extraction processing on the image data in the target medical data based on a preset first feature extraction model to obtain corresponding first feature data;
[0184] A second extraction sub-module, configured to perform feature extraction processing on the time series data in the target medical data based on a preset second feature extraction model to obtain corresponding second feature data;
[0185] An integration sub-module, configured to perform integration processing on the first feature data and the second feature data to obtain corresponding integrated data;
[0186] A first determination sub-module, configured to use the integrated data as the target feature data.
[0187] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the report generation method in the foregoing embodiment, and will not be elaborated herein.
[0188] In some optional implementation manners of this embodiment, the generation module 305 includes:
[0189] A first acquisition sub-module, configured to acquire a preset physical examination report template;
[0190] A processing sub-module, configured to perform a combining process on the health assessment result and the physical examination report template based on the template engine to obtain a corresponding initial physical examination report;
[0191] A verification sub-module, configured to verify the information in the initial physical examination report;
[0192] A second determination sub-module, configured to use the initial physical examination report as the physical examination report if the initial physical examination report passes the information verification.
[0193] In this embodiment, the operations respectively performed by the above-mentioned modules or units correspond one by one to the steps of the report generation method in the foregoing embodiment, and will not be elaborated herein.
[0194] In some alternative implementation manners of this embodiment, the optimization module 306 includes:
[0195] A second acquisition sub-module, configured to acquire a preset adjustment strategy;
[0196] An adjustment sub-module, configured to perform content personalization adjustment on the physical examination report based on the adjustment strategy to obtain a corresponding first physical examination report;
[0197] An optimization sub-module, configured to perform language optimization processing on the first physical examination report based on a preset language optimization tool to obtain a corresponding second physical examination report;
[0198] A third determination sub-module, configured to use the second physical examination report as the target physical examination report.
[0199] In this embodiment, the operations respectively performed by the above-mentioned modules or units correspond one by one to the steps of the report generation method in the foregoing embodiment, and will not be elaborated herein.
[0200] In some alternative implementation manners of this embodiment, the output module 307 includes:
[0201] A first calling sub-module, configured to call a preset chart tool;
[0202] A conversion sub-module, configured to perform data conversion processing on the target physical examination report based on the chart tool to obtain a third physical examination report including graphic data;
[0203] A second calling sub-module, configured to call a preset target interface;
[0204] A display sub-module, configured to display the third physical examination report in the target interface.
[0205] In this embodiment, the operations respectively performed by the above-mentioned modules or units correspond one by one to the steps of the report generation method in the foregoing embodiment, and will not be elaborated herein.
[0206] In some alternative implementation manners of this embodiment, the preprocessing module 302 includes:
[0207] A second processing sub-module, configured to clean the medical data to obtain corresponding first medical data;
[0208] A third processing sub-module, configured to convert the first medical data into a preset standard format to obtain corresponding second medical data;
[0209] A fourth processing sub-module, configured to normalize the second medical data to obtain corresponding third medical data;
[0210] A fourth determination sub-module, configured to use the third medical data as the target medical data.
[0211] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the report generation method in the foregoing embodiment, and will not be elaborated herein.
[0212] In some alternative implementation manners of this embodiment, the report generation device further includes:
[0213] A second acquisition module, configured to acquire a preset encryption policy;
[0214] An encryption module, configured to encrypt the target physical examination report based on the encryption policy to obtain a corresponding fourth physical examination report;
[0215] A third acquisition module, configured to acquire a preset target sending manner;
[0216] A sending module, configured to send the fourth physical examination report to the user based on the target sending manner.
[0217] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the report generation method in the foregoing embodiment, and will not be elaborated herein.
[0218] To solve the above technical problems, an embodiment of the present application further provides a computer device. For details, please refer to Figure 4 , Figure 4 which is the basic structural block diagram of the computer device in this embodiment.
[0219] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are communicatively connected to each other via a system bus. It should be noted that only the computer device 4 with components 41-43 is shown in the figure, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Among them, those skilled in the art of this technology can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.
[0220] The computer device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device can perform human-computer interaction with the user through a keyboard, a mouse, a remote control, a touchpad, or a voice control device, etc.
[0221] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, a hard disk, a multimedia card, a card-type memory (such as an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 4. Of course, the memory 41 can also include both the internal storage unit and the external storage device of the computer device 4. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the report generation method. In addition, the memory 41 can also be used to temporarily store various data that have been output or will be output.
[0222] In some embodiments, the processor 42 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the computer-readable instructions stored in the memory 41 or process data, such as running the computer-readable instructions of the report generation method.
[0223] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.
[0224] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:
[0225] In the embodiments of the present application, the present application first obtains the medical data of the user and obtains the personal information of the user; then preprocesses the medical data to obtain corresponding target medical data; then performs feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data; subsequently performs a health assessment process on the target feature data and the personal information based on a preset health assessment model to obtain a corresponding health assessment result; further performs a report generation process on the health assessment result based on a preset template engine to obtain a corresponding physical examination report; and performs a report optimization process on the physical examination report to obtain a corresponding target physical examination report; finally outputs the target physical examination report. By obtaining the medical data of the user and the personal information of the user, preprocessing the medical data to obtain target medical data, then performing feature extraction processing on the target medical data based on the use of the feature extraction model to obtain target feature data, and performing a health assessment process on the target feature data and the personal information based on the use of the pre-health assessment model to obtain a corresponding health assessment result, and then performing a report generation process on the health assessment result based on the use of the template engine to obtain a corresponding physical examination report, and subsequently performing a report optimization process on the physical examination report to obtain a corresponding target physical examination report and outputting it, the present application realizes the automatic and accurate generation of the physical examination report, effectively improving the generation efficiency and accuracy of the physical examination report.
[0226] The present application also provides another implementation manner, that is, to provide a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor, so that the at least one processor executes the steps of the report generation method as described above.
[0227] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:
[0228] In the embodiments of the present application, the present application first obtains the medical data of the user and the personal information of the user; then preprocesses the medical data to obtain the corresponding target medical data; then performs feature extraction processing on the target medical data based on a preset feature extraction model to obtain the corresponding target feature data; subsequently performs health assessment processing on the target feature data and the personal information based on a preset health assessment model to obtain the corresponding health assessment result; further performs report generation processing on the health assessment result based on a preset template engine to obtain the corresponding physical examination report; and performs report optimization processing on the physical examination report to obtain the corresponding target physical examination report; finally outputs the target physical examination report. By obtaining the medical data of the user and the personal information of the user, preprocessing the medical data to obtain the target medical data, then performing feature extraction processing on the target medical data based on the use of the feature extraction model to obtain the target feature data, and performing health assessment processing on the target feature data and the personal information based on the use of the pre-health assessment model to obtain the corresponding health assessment result, and then performing report generation processing on the health assessment result based on the use of the template engine to obtain the corresponding physical examination report, and subsequently performing report optimization processing on the physical examination report to obtain the corresponding target physical examination report and outputting it, the present application realizes automatically and accurately generating the physical examination report, effectively improving the generation efficiency and accuracy of the physical examination report.
[0229] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present application.
[0230] Obviously, the embodiments described above are only a part of the embodiments of the present application, rather than all of them. The preferred embodiments of the present application are shown in the drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosed content of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments or equivalently replace some of the technical features. Any equivalent structure made by using the content of the specification and drawings of the present application, directly or indirectly applied in other related technical fields, is similarly within the scope of patent protection of the present application.
Claims
1. A report generation method, characterized in that: The steps include: Access to a user's medical data, and to personal information of said user; Preprocessing the medical data to obtain corresponding target medical data; Perform feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data; Performing health assessment processing on the target feature data and the personal information based on a preset health assessment model to obtain a corresponding health assessment result; Performing report generation processing on the health assessment results based on a preset template engine to obtain a corresponding physical examination report; Performing report optimization processing on the physical examination report to obtain a corresponding target physical examination report; The target physical examination report is output.
2. The report generation method according to claim 1, characterized in that: The step of performing feature extraction processing on the target medical data based on the preset feature extraction model to obtain corresponding target feature data specifically includes: Performing feature extraction processing on the image data in the target medical data based on a preset first feature extraction model to obtain corresponding first feature data; Performing feature extraction processing on the time series data in the target medical data based on a preset second feature extraction model to obtain corresponding second feature data; Integrate the first feature data and the second feature data to obtain corresponding integrated data; The integrated data is used as the target feature data.
3. The report generation method according to claim 1, characterized in that: The step of performing report generation processing on the health assessment result based on a preset template engine to obtain a corresponding physical examination report specifically includes: Get the preset physical examination report template; Based on the template engine, the health assessment result is combined with the physical examination report template to obtain a corresponding initial physical examination report; Verifying information on the initial physical examination report; If the initial physical examination report passes the information verification, the initial physical examination report will be used as the physical examination report.
4. The report generation method according to claim 1, characterized in that: The step of performing report optimization processing on the physical examination report to obtain a corresponding target physical examination report specifically includes: Get the preset adjustment strategy; Based on the adjustment strategy, the content of the physical examination report is adjusted in a personalized manner to obtain a corresponding first physical examination report; Performing language optimization processing on the first physical examination report based on a preset language optimization tool to obtain a corresponding second physical examination report; The second physical examination report is used as the target physical examination report.
5. The report generation method according to claim 1, characterized in that: The step of outputting the target physical examination report specifically includes: Call the preset chart tool; Performing data conversion processing on the target physical examination report based on the chart tool to obtain a third physical examination report containing graphic data; Call the preset target interface; The third physical examination report is displayed in the target interface.
6. The report generation method according to claim 1, characterized in that: The step of preprocessing the medical data to obtain corresponding target medical data specifically includes: Cleaning the medical data to obtain corresponding first medical data; Converting the first medical data into a preset standard format to obtain corresponding second medical data; normalizing the second medical data to obtain corresponding third medical data; The third medical data is used as the target medical data.
7. The report generation method according to claim 1, characterized in that: After the step of performing report optimization processing on the physical examination report to obtain the corresponding target physical examination report, the method further includes: Get the preset encryption policy; Encrypting the target physical examination report based on the encryption strategy to obtain a corresponding fourth physical examination report; Get the preset target sending method; Based on the target sending mode, the fourth physical examination report is sent to the user.
8. A report generating device, characterized in that: include: A first acquisition module is used to acquire the medical data of the user and the personal information of the user; A preprocessing module, used for preprocessing the medical data to obtain corresponding target medical data; An extraction module is used to perform feature extraction processing on the target medical data based on a preset feature extraction model to obtain corresponding target feature data; An evaluation module, used to perform health evaluation processing on the target feature data and the personal information based on a preset health evaluation model to obtain a corresponding health evaluation result; A generation module, used to perform report generation processing on the health assessment result based on a preset template engine to obtain a corresponding physical examination report; An optimization module, used for performing report optimization processing on the physical examination report to obtain a corresponding target physical examination report; An output module is used to output the target physical examination report.
9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the report generating method according to any one of claims 1 to 7 when executing the computer-readable instructions.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the report generating method according to any one of claims 1 to 7 are implemented.