Medical data acquisition methods, devices, computer equipment and storage media

Abstract

This application provides a medical data acquisition method, apparatus, computer device, and storage medium. The method includes: responding to a medical data acquisition request, obtaining influencing factors related to a medical disease to be acquired, and medical reference indicators corresponding to the influencing factors; invoking a preset data acquisition device to execute a data acquisition task corresponding to the influencing factors to acquire medical data samples, and inputting the medical data samples into a preset data analyzer to obtain medical data indicators; determining and adjusting a data acquisition task to be adjusted based on the medical reference indicators and the medical data indicators; and iteratively acquiring data based on the adjusted data acquisition task until a target medical data sample matching the medical reference indicators is acquired and output. This application embodiment achieves the effect of automatic, efficient, and accurate acquisition of medical data.

Description

Technical Field

[0001] This application relates to the field of ultrasound image processing technology, specifically to a medical data acquisition method, device, computer equipment, and storage medium (computer-readable storage medium). Background Technology

[0002] With the rapid development of computer technology, online diagnosis has been widely used. Some online diagnoses are achieved through AI. AI diagnosis requires the collection and analysis of a large amount of medical data, such as case reports and medical images, to obtain AI diagnostic data.

[0003] In the actual data collection process, not all medical data such as case reports and medical images need to be collected for preprocessing and analysis. Instead, important and special medical data (such as lesions, malformations, and scattered plaques) related to the disease need to be manually screened and summarized. This data screening and summarization work is very labor-intensive and cannot achieve the purpose of accurate analysis and collection. Summary of the Invention

[0004] This application provides a medical data acquisition method, device, computer equipment, and storage medium, which solves the technical problem of inaccurate medical data acquisition in the present invention.

[0005] On one hand, embodiments of this application provide a medical data acquisition method, including:

[0006] In response to a medical data collection request, obtain the influencing factors associated with the medical diseases to be collected, as well as the corresponding medical reference indicators for the influencing factors;

[0007] A preset data collector is invoked to execute the data collection task corresponding to the influencing factor to collect medical data samples, and the medical data samples are input into a preset data analyzer to obtain medical data indicators.

[0008] Based on the medical reference indicators and the medical data indicators, determine the data collection tasks to be adjusted and make adjustments accordingly;

[0009] Iterative data collection is performed based on the adjusted data collection task until a target medical data sample that matches the medical reference indicators is collected and output.

[0010] In some embodiments of this application, the step of calling a preset data collector to execute the data collection task corresponding to the influencing factor to collect medical data samples, and inputting the medical data samples into a preset data analyzer to obtain medical data indicators, includes:

[0011] Obtain the medical features associated with the influencing factors, and generate data collection tasks corresponding to each of the medical features;

[0012] Each data acquisition task is assigned a preset data acquisition device to analyze the preset medical data and obtain the medical data sample corresponding to each data acquisition task.

[0013] The medical data samples corresponding to each of the data acquisition tasks are input into the data analyzer corresponding to the data acquisition task to obtain the first medical feature, and medical data indicators are extracted from each of the first medical features.

[0014] In some embodiments of this application, the step of invoking a preset data collector to execute the data collection task corresponding to the impact factor to collect medical data samples includes:

[0015] Inputting target medical data of image type from preset medical data into the image recognition module of a preset data acquisition device to obtain the second medical feature of the target medical data; and / or,

[0016] Input the target medical data (text type) into the character recognition module of the preset data acquisition device to obtain the second medical feature of the target medical data;

[0017] Obtain target medical features that match the preset medical features of the influencing factors, and set the target medical data corresponding to the target medical features as medical data samples.

[0018] In some embodiments of this application, determining and adjusting the data acquisition task to be adjusted based on the medical reference indicators and the medical data indicators includes:

[0019] The medical data indicators of the same type are compared with the medical reference indicators. If the medical data indicators do not match the medical reference indicators, the difference data indicators are obtained.

[0020] For the data collection task corresponding to the aforementioned difference data indicator, increase the sample size and proportion of the data collection task to obtain a new data collection task.

[0021] In some embodiments of this application, after the medical data indicators corresponding to the data acquisition task until the adjustment are consistent with the medical reference indicators, and the target medical data sample corresponding to the data acquisition task is output, the process includes:

[0022] Obtain medical data samples corresponding to each of the data acquisition tasks, and extract the medical features of the medical data samples;

[0023] The medical characteristics of the medical data sample are compared with the preset medical characteristics of the influence factor. If there is a target medical characteristic that is different from the preset medical characteristics, the target medical characteristic is added to the influence factor to obtain an updated influence factor.

[0024] Configure the medical reference indicators corresponding to the updated impact factors and generate a new data collection task.

[0025] In some embodiments of this application, the medical data indicators corresponding to the data acquisition task until adjustment are consistent with the medical reference indicators. After outputting the target medical data sample corresponding to the data acquisition task, the process includes...

[0026] Add data tags corresponding to the influencing factors and medical data indicators to the target medical data sample, and save it to a preset database;

[0027] In response to a data analysis request, obtain the target medical disease corresponding to the data analysis request, as well as the target impact factor and / or target medical data indicator corresponding to the target medical disease;

[0028] The preset database is queried to obtain the reference medical data corresponding to the target impact factor and / or the target medical data indicator. The diagnostic results in the reference medical data are feature extracted to obtain the diagnostic reference information of the target medical disease.

[0029] In some embodiments of this application, the influencing factors include at least one of: physical signs, anatomical parameters, clinical experience characteristics, and omics characteristics;

[0030] The vital signs parameters include at least one of the following: blood pressure, blood flow velocity, heart rate, and blood volume;

[0031] The anatomical parameters include at least one of the following: anatomical location, anatomical morphology, and anatomical volume;

[0032] The clinical experience characteristics refer to the characteristics of medical changes that occur in the body of a disease patient in the clinical record;

[0033] The omics features refer to features obtained through omics, proteomics, metabolomics, transcriptomics, lipidomics, immunoomics, glycomics, RNAmics, radiomics, and sonomics.

[0034] On the other hand, embodiments of this application also provide a medical data acquisition device, including:

[0035] The acquisition module is used to respond to medical data collection requests, acquire the influencing factors associated with the medical diseases to be collected, and the medical reference indicators corresponding to the influencing factors;

[0036] The data acquisition module is used to call a preset data acquisition device to execute the data acquisition task corresponding to the influencing factor to collect medical data samples, and input the medical data samples into a preset data analyzer to obtain medical data indicators.

[0037] The adjustment module is used to determine and adjust the data acquisition task to be adjusted based on the medical reference indicators and the medical data indicators.

[0038] The output module is used to iteratively collect data according to the adjusted data collection task until a target medical data sample that matches the medical reference index is collected and then output.

[0039] On the other hand, embodiments of this application also provide a computer device, which includes a processor, a memory, and a medical data acquisition program stored in the memory and executable on the processor. The processor executes the medical data acquisition program to implement the steps in the above-described medical data acquisition method.

[0040] On the other hand, embodiments of this application also provide a computer-readable storage medium storing a medical data acquisition program, which is executed by a processor to implement the steps in the above-described medical data acquisition method.

[0041] Compared to existing medical data acquisition methods, devices, computer equipment, and storage media, this method includes: responding to a medical data acquisition request, obtaining the influencing factors associated with the medical disease to be acquired, and the corresponding medical reference indicators; invoking a preset data acquisition device to execute the data acquisition task corresponding to the influencing factors to acquire medical data samples, and inputting the medical data samples into a preset data analyzer to obtain medical data indicators; determining and adjusting the data acquisition task to be adjusted based on the medical reference indicators and the medical data indicators; and iteratively acquiring data based on the adjusted data acquisition task until a target medical data sample whose medical data indicators match the medical reference indicators is acquired and output. In this embodiment, medical reference indicators for the medical disease are preset. Medical data samples are acquired first, and then the data acquisition task is adjusted based on the medical reference indicators and the medical data indicators of the acquired medical data samples. Iterative acquisition is then performed based on the adjusted data acquisition task until a target medical data sample whose medical data indicators match the medical reference indicators is acquired and output. This embodiment can automatically adjust the data acquisition task and continuously acquire medical data samples until the required medical data samples are obtained, achieving automatic and accurate acquisition of medical data. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram of a scenario for the medical data acquisition method provided in the embodiments of this application;

[0044] Figure 2 This application provides a schematic flowchart of a medical data acquisition method.

[0045] Figure 3 This application provides a detailed flowchart illustrating the steps of data indicator analysis in a medical data acquisition method.

[0046] Figure 4 A schematic diagram illustrating the process of adjusting the data acquisition task in a medical data acquisition method provided in this application embodiment;

[0047] Figure 5 This application provides a schematic flowchart illustrating the steps involved in generating a data acquisition task in a medical data acquisition method.

[0048] Figure 6 This application provides a schematic flowchart of the data analysis steps in a medical data acquisition method.

[0049] Figure 7 This is a schematic diagram of an embodiment of the medical data acquisition device provided in this application.

[0050] Figure 8 This is a schematic diagram of an embodiment of the computer device provided in this application. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of the present invention.

[0052] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to implement and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be implemented without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in the embodiments of this application.

[0053] This application provides a medical data acquisition method, apparatus, device, and computer-readable storage medium, which will be described in detail below.

[0054] In this embodiment, the medical data acquisition method is deployed as a program on a medical data acquisition device, which is installed in a computer device as a processor. The medical data acquisition device in the computer device executes the following steps by running the program corresponding to the medical data acquisition method:

[0055] In response to a medical data collection request, obtain the influencing factors associated with the medical diseases to be collected, as well as the corresponding medical reference indicators for the influencing factors;

[0056] A preset data collector is invoked to execute the data collection task corresponding to the influencing factor to collect medical data samples, and the medical data samples are input into a preset data analyzer to obtain medical data indicators.

[0057] Based on the medical reference indicators and the medical data indicators, determine the data collection tasks to be adjusted and make adjustments accordingly;

[0058] Iterative data collection is performed based on the adjusted data collection task until a target medical data sample that matches the medical reference indicators is collected and output.

[0059] like Figure 1 As shown, Figure 1 This is a schematic diagram illustrating a medical data acquisition scenario according to an embodiment of this application. The schematic diagram of the implementation scenario provided in this application includes a medical data acquisition device 100 and an imaging device 200. The imaging device 200 is mainly used to capture ultrasound images, while the medical data acquisition device 100 runs a computer storage medium corresponding to the medical data acquisition method to execute the steps of medical data acquisition.

[0060] It should be noted that, Figure 1 The illustrated medical data acquisition scenario is merely an example. The medical data acquisition scenario described in this application embodiment is intended to more clearly illustrate the technical solution of this application embodiment and does not constitute a limitation on the technical solution provided in this application embodiment.

[0061] Based on the above schematic diagram of the medical data acquisition scenario, specific embodiments of the medical data acquisition method are proposed.

[0062] like Figure 2 As shown, Figure 2 This is a flowchart illustrating the steps of a medical data acquisition method provided in an embodiment of this application. The medical data acquisition in this embodiment includes steps 201-204:

[0063] 201. In response to the medical data collection request, obtain the influencing factors associated with the medical diseases to be collected, as well as the medical reference indicators corresponding to the influencing factors.

[0064] The medical data acquisition method in this embodiment is applied to a computer device. The computer device receives a medical data acquisition request. The triggering method of the medical data acquisition request is not specifically limited. The medical data acquisition request can be triggered actively by the user, for example, the user enters the name of a disease on the computer device to actively trigger the data acquisition request. In addition, the data acquisition request can also be triggered automatically by the computer device, for example, the computer device is pre-set to automatically trigger the data acquisition every time the medical data is updated. When the computer device detects that the medical data is updated, it automatically triggers the medical data acquisition request.

[0065] The computer equipment responds to the medical data collection request, obtaining the influencing factors associated with the medical diseases to be collected, as well as the corresponding medical reference indicators. It should be noted that the correspondence between the influencing factors and the medical reference indicators is pre-set. Generally speaking, the influencing factors contain a large number of medical features, and different reference instructions can be extracted from the medical features. For example, the influencing factors for heart disease include heart rate and blood pressure. For example, the medical reference indicators corresponding to heart rate are maximum heart rate and minimum heart rate; the medical reference indicators corresponding to blood pressure are maximum blood pressure value and minimum blood pressure value.

[0066] Among them, medical diseases are set according to specific scenarios, for example, the medical disease is the flu; influencing factors include at least one of the following: vital signs parameters, anatomical parameters, clinical experience characteristics, and omics characteristics; among them,

[0067] The vital signs parameters include at least one of blood pressure, blood flow velocity, heart rate, and blood flow rate. The medical reference indicators for blood pressure are the highest and lowest blood pressure values; the medical reference indicators for blood flow velocity are the highest and lowest blood flow velocities; the medical reference indicators for heart rate are the maximum and minimum heart rates; and the medical reference indicators for blood flow rate are the maximum and minimum blood flow rates. It is understood that the vital signs parameters in this embodiment may also include blood oxygen content, etc., but this embodiment does not specifically limit them.

[0068] Anatomical parameters include at least one of anatomical location, anatomical morphology, and anatomical volume; in the embodiments of this application, the medical reference index corresponding to the anatomical location is the anatomical location coordinates; the medical reference index corresponding to the anatomical morphology is the anatomical state value; and the medical reference index corresponding to the anatomical volume is the anatomical volume value. It is understood that the anatomical parameters in the embodiments of this application may also include anatomical size, etc., but are not specifically detailed in the embodiments of this application.

[0069] Clinical experience features refer to a series of medical changes observed in a patient's body as recorded in clinical practice; these features are often used as important criteria for disease diagnosis. For example, symptoms such as cough, fever, headache, and weakness can all be considered clinical experience features of a cold or fever, while cough and hemoptysis are also clinical manifestations of tuberculosis. A single disease may have multiple clinical manifestations, and many diseases share the same clinical manifestations (i.e., the same clinical manifestation can appear in multiple diseases. For example, cough can be a clinical manifestation of pharyngitis, a cold or fever, tuberculosis, pneumonia, bronchitis, and many other diseases).

[0070] Omics features refer to characteristics obtained through omics, proteomics, metabolomics, transcriptomics, lipidomics, immunoomics, glycomics, RNAmics, radiomics, and ultrasoundmics. For example, radiomics refers to the high-throughput extraction of large amounts of image information from images to achieve tumor segmentation, feature extraction, and model building. By conducting deeper mining, prediction, and analysis of massive amounts of data, it assists physicians in making the most accurate diagnoses. The corresponding medical reference index for radiomics is image feature value.

[0071] 202. Call the preset data collector to execute the data collection task corresponding to the influencing factor to collect medical data samples, and input the medical data samples into the preset data analyzer to obtain medical data indicators.

[0072] The computer equipment invokes a pre-defined data acquisition unit. This data acquisition unit utilizes a deep learning algorithm trained on a neural network. The model structure of the data acquisition unit is not specifically limited. It can analyze different types of medical data samples. For example, the data analyzer may include an image recognition module to analyze medical data samples corresponding to image types; it may also include a text recognition module to analyze character-based medical data samples. Specifically, the data acquisition unit is used to extract features from medical data samples, thereby collecting medical data samples corresponding to influencing factors.

[0073] The computer equipment invokes a preset data acquisition device to execute the data acquisition task corresponding to the influencing factor, collects medical data samples, and inputs the medical data samples into a preset data analyzer to obtain medical data indicators, specifically including:

[0074] 1. Input the target medical data (image type) from the preset medical data into the image recognition module of the preset data acquisition device to obtain the second medical feature of the target medical data; and / or,

[0075] 2. Input the target medical data (text type) from the preset medical data into the character recognition module of the preset data acquisition device to obtain the second medical feature of the target medical data;

[0076] 3. Obtain target medical features that match the preset medical features of the influencing factors, and set the target medical data corresponding to the target medical features as medical data samples.

[0077] That is, the computer device inputs the target medical data of image type from the preset medical data into the image recognition module of the preset data collector to obtain the second medical feature of the target medical data; and / or, the computer device inputs the target medical data of text type from the preset medical data into the character recognition module of the preset data collector to obtain the second medical feature of the target medical data; the computer device obtains the preset medical features of the influence factor, the computer device compares the second medical feature with the preset medical features, the computer device obtains the target medical feature that is the same as or more similar than the preset medical features of the influence factor, and the computer device sets the target medical data corresponding to the target medical feature as a medical data sample.

[0078] Furthermore, the computer device inputs medical data samples into a preset data analyzer to obtain medical data indicators. In this embodiment, a data acquisition device first performs preliminary feature extraction on a large amount of medical data to obtain target medical features that match the preset medical features of the influencing factors, and sets the target medical data corresponding to the target medical features as medical data samples. Then, the computer device inputs the medical data samples into the preset data analyzer, and analyzes each medical data sample through the feature extraction module in the data analyzer to obtain more detailed medical features of each medical data sample. The computer device extracts medical data indicators from the medical features through the indicator extraction module in the data analyzer.

[0079] In this embodiment, the computer device first collects medical data samples by calling a preset data collector to perform data collection tasks corresponding to the influencing factors. Then, the medical data samples are input into a preset data analyzer, and secondary feature extraction is performed by the data analyzer to obtain medical data indicators. This reduces the performance requirements of the computer device while achieving accurate analysis and collection of medical data.

[0080] 203. Based on the medical reference indicators and the medical data indicators, determine the data collection task to be adjusted and make the adjustment.

[0081] Since the influencing factor can correspond to multiple different types of medical reference indicators, the computer equipment acquires the first type of medical reference indicator and the second type of medical data indicator. The computer equipment compares the medical reference indicators and medical data indicators of the same type. If the medical data indicator is within the range corresponding to the medical reference indicator, the computer equipment determines that the target medical data sample that matches the medical reference indicator can be output and does not need to be collected repeatedly. If the medical data indicator is not within the range corresponding to the medical reference indicator, the computer equipment acquires the target medical feature corresponding to the medical reference indicator. The computer equipment takes the data acquisition task corresponding to the target medical feature as the data acquisition task to be adjusted, and adjusts the data acquisition volume and data ratio of the data acquisition task to be adjusted to obtain the adjusted data acquisition task.

[0082] That is, in the embodiments of this application, the computer device adjusts the data acquisition task, which can adjust the amount of medical data collected corresponding to different medical characteristics, making the data acquisition more targeted, reducing the collection of invalid data, and improving the data acquisition efficiency.

[0083] 204. Iteratively collect data according to the adjusted data collection task until a target medical data sample that matches the medical reference index is collected and output.

[0084] The computer device iteratively collects data according to the adjusted data acquisition task until a target medical data sample whose medical data indicators match the medical reference indicators is collected and output. In this embodiment, the computer device pre-sets medical reference indicators for medical diseases, first collects medical data samples, and then adjusts the data acquisition task according to the medical reference indicators and the medical data indicators of the collected medical data samples. Iteratively collects data according to the adjusted data acquisition task until a target medical data sample whose medical data indicators match the medical reference indicators is collected and output. In this embodiment, the data acquisition task can be automatically adjusted to continuously collect medical data samples until the required medical data sample is obtained, thus realizing the automatic and accurate collection of medical data.

[0085] As shown in Figure 3 Figure 3 This is a detailed flowchart illustrating the steps of data indicator analysis in a medical data acquisition method provided in this application embodiment. The medical data acquisition method in this application embodiment includes steps 301-303:

[0086] 301. Obtain the medical features associated with the influencing factors and generate data collection tasks corresponding to each medical feature.

[0087] The computer device acquires medical features associated with influencing factors and generates data acquisition tasks corresponding to each medical feature. That is, in this embodiment of the application, the computer device creates different data acquisition tasks for different medical features. In this way, different acquisition tasks collect medical data for different features in a targeted manner, making the data acquisition more comprehensive and facilitating the comparison and analysis of medical data collected by different data acquisition tasks in the later stage.

[0088] 302, respectively call the preset data acquisition device corresponding to each data acquisition task to analyze the preset medical data and obtain the medical data sample corresponding to each data acquisition task.

[0089] The computer device calls the preset data acquisition device corresponding to each data acquisition task to analyze the preset medical data. The preset medical data refers to the massive medical data samples stored in the database. The computer device obtains the medical data samples corresponding to each data acquisition task. In this embodiment, different data acquisition devices are pre-created in the computer device, and data is collected through different data acquisition devices, making the data collection more targeted.

[0090] 303. Input the medical data samples corresponding to each data acquisition task into the data analyzer corresponding to the data acquisition task to obtain the first medical feature, and extract medical data indicators from each of the first medical features.

[0091] The computer device inputs the medical data samples corresponding to each data acquisition task into the data analyzer corresponding to the data acquisition task to obtain the first medical feature, and extracts medical data indicators from each first medical feature. In this embodiment, different data acquisition tasks correspond to different data analyzers, so that the first medical feature can be accurately acquired and medical data indicators can be extracted from the first medical feature. That is to say, in this embodiment of the application, multiple data acquisition devices and data analyzers are sampled for data acquisition and analysis, making the data acquisition and analysis more accurate.

[0092] like Figure 4 As shown, Figure 4 This is a flowchart illustrating the adjustment of data acquisition tasks in a medical data acquisition method according to an embodiment of this application. The medical data acquisition method in this embodiment includes steps 401-402:

[0093] 401. Compare the medical data indicators of the same type with the medical reference indicators. If the medical data indicators do not match the medical reference indicators, then obtain the difference data indicators.

[0094] The computer device compares medical data indicators of the same type with medical reference indicators. For example, if the medical reference indicator is blood pressure, the computer device compares the first blood pressure value corresponding to the medical data indicator with the maximum and minimum blood pressure values ​​in the medical reference indicator. If the first blood pressure value is within the range of the maximum and minimum blood pressure values, then the medical data indicator matches the medical reference indicator; if the medical data indicator does not match the medical reference indicator, then the difference data indicator is obtained.

[0095] In this application embodiment, there are many types of medical data indicators and medical reference indicators. The computer device acquires specific types of discrepancy data indicators that do not match the medical data indicators and medical reference indicators, so as to facilitate the adjustment of the corresponding data acquisition tasks. Specifically:

[0096] 402. For the data collection task corresponding to the difference data indicator, increase the number of samples and the proportion of the number of samples in the data collection task to obtain a new data collection task.

[0097] The computer device determines that the medical data corresponding to the discrepancy data indicators does not meet the requirements and needs to be re-collected. For the data collection task corresponding to the discrepancy data indicators, the computer device increases the sample size and proportion of the data collection task to obtain a new data collection task. The computer device re-collects data according to the new data collection task. In this embodiment of the application, the computer device adjusts the data collection task according to the collected medical data samples so that the collected data samples are more in line with the set medical reference indicators, thereby accurately performing medical data analysis.

[0098] like Figure 5As shown, Figure 5 This is a flowchart illustrating the steps involved in generating a data acquisition task in a medical data acquisition method according to an embodiment of this application. The medical data acquisition method in this embodiment includes steps 501-503:

[0099] 501. Obtain medical data samples corresponding to each of the data acquisition tasks, and extract the medical features of the medical data samples.

[0100] The computer device acquires medical data samples corresponding to each data acquisition task and extracts medical features from the medical data samples. In this embodiment, the medical features can be extracted through a deep neural network, and the extraction method is not specifically limited.

[0101] 502. Compare the medical features of the medical data sample with the preset medical features of the influence factor. If there is a target medical feature that is different from the preset medical features, add the target medical feature to the influence factor to obtain an updated influence factor.

[0102] The computer device compares the medical characteristics of the medical data sample with the preset medical characteristics of the influence factor. If the medical characteristics of the medical data sample are all in the preset medical characteristics of the influence factor, no processing is performed. If there is a target medical characteristic that is different from the preset medical characteristics, the computer device adds the target medical characteristic to the influence factor to obtain an updated influence factor.

[0103] 503. Configure the medical reference indicators corresponding to the updated impact factors and generate a new data collection task.

[0104] The computer device outputs configuration prompts to allow users to configure the medical reference indicators corresponding to the new and updated impact factors, and generates new data collection tasks according to the updated impact factors, thus re-collecting medical data. In this embodiment, the computer device updates the impact factors associated with medical diseases in real time and updates the data collection tasks to call the preset data collector to collect new medical data samples, realizing comprehensive collection and analysis of medical data samples.

[0105] like Figure 6 As shown, Figure 6 This is a flowchart illustrating the data analysis steps in a medical data acquisition method provided in this application embodiment. The medical data acquisition method in this application embodiment includes steps 601-603:

[0106] 601. Add data tags corresponding to the impact factor and the medical data indicator to the target medical data sample, and save it to a preset database.

[0107] The computer device adds data tags corresponding to the influencing factors and medical data indicators of the target medical data sample and saves them to a preset database to facilitate quick data retrieval later.

[0108] 602, responding to the data analysis request, obtaining the target medical disease corresponding to the data analysis request, as well as the target impact factor and / or target medical data indicator corresponding to the target medical disease.

[0109] The computer device responds to the data analysis request and obtains the target medical disease corresponding to the data analysis request, as well as the target impact factor and / or target medical data indicator corresponding to the target medical disease.

[0110] 603. Query the preset database to obtain the reference medical data corresponding to the target impact factor and / or the target medical data indicator, extract features from the diagnostic results in the reference medical data, and obtain diagnostic reference information for the target medical disease.

[0111] The computer device queries a preset database and obtains reference medical data corresponding to the target influencing factor and / or the target medical data indicator based on data tags. The computer device then extracts features from the diagnostic results in the reference medical data to obtain diagnostic reference information for the target medical disease. In this embodiment, the method of extracting features from the reference medical data is not limited. The computer device can quickly query the reference medical data, then extract features from the diagnostic results in the reference medical data to obtain diagnostic reference information for the target medical disease, enabling accurate analysis of medical data and the generation of online diagnostic reference information.

[0112] To better implement the medical data acquisition method in the embodiments of this application, a medical data acquisition device is also provided in the embodiments of this application, based on the medical data acquisition method. For example... Figure 7 As shown, Figure 7 This is a schematic diagram of the structure of a medical data acquisition device provided in an embodiment of this application.

[0113] The medical data acquisition device includes:

[0114] The acquisition module 701 is used to respond to medical data acquisition requests, acquire the medical disease-related influencing factors to be acquired, and the medical reference indicators corresponding to the influencing factors.

[0115] The acquisition module 702 is used to call a preset data acquisition device to execute the data acquisition task corresponding to the influencing factor to collect medical data samples, and input the medical data samples into a preset data analyzer to obtain medical data indicators.

[0116] The adjustment module 703 is used to determine and adjust the data acquisition task to be adjusted based on the medical reference indicators and the medical data indicators.

[0117] The output module 704 is used to iteratively collect data according to the adjusted data collection task until a target medical data sample whose medical data indicators match the medical reference indicators is collected and then output.

[0118] In some embodiments of this application, the acquisition module 702 in the medical data acquisition device is further used for:

[0119] Obtain the medical features associated with the influencing factors, and generate data collection tasks corresponding to each of the medical features;

[0120] Each data acquisition task is assigned a preset data acquisition device to analyze the preset medical data and obtain the medical data sample corresponding to each data acquisition task.

[0121] The medical data samples corresponding to each of the data acquisition tasks are input into the data analyzer corresponding to the data acquisition task to obtain the first medical feature, and medical data indicators are extracted from each of the first medical features.

[0122] In some embodiments of this application, the acquisition module 702 in the medical data acquisition device is further used for:

[0123] Inputting target medical data of image type from preset medical data into the image recognition module of a preset data acquisition device to obtain the second medical feature of the target medical data; and / or,

[0124] Input the target medical data (text type) into the character recognition module of the preset data acquisition device to obtain the second medical feature of the target medical data;

[0125] Obtain target medical features that match the preset medical features of the influencing factors, and set the target medical data corresponding to the target medical features as medical data samples.

[0126] In some embodiments of this application, the adjustment module 703 in the medical data acquisition device is further used for:

[0127] The medical data indicators of the same type are compared with the medical reference indicators. If the medical data indicators do not match the medical reference indicators, the difference data indicators are obtained.

[0128] For the data collection task corresponding to the aforementioned difference data indicator, increase the sample size and proportion of the data collection task to obtain a new data collection task.

[0129] In some embodiments of this application, the medical data acquisition device is also used for:

[0130] Obtain medical data samples corresponding to each of the data acquisition tasks, and extract the medical features of the medical data samples;

[0131] The medical characteristics of the medical data sample are compared with the preset medical characteristics of the influence factor. If there is a target medical characteristic that is different from the preset medical characteristics, the target medical characteristic is added to the influence factor to obtain an updated influence factor.

[0132] Configure the medical reference indicators corresponding to the updated impact factors and generate a new data collection task.

[0133] In some embodiments of this application, the medical data acquisition device is also used for:

[0134] Add data tags corresponding to the influencing factors and medical data indicators to the target medical data sample, and save it to a preset database;

[0135] In response to a data analysis request, obtain the target medical disease corresponding to the data analysis request, as well as the target impact factor and / or target medical data indicator corresponding to the target medical disease;

[0136] The preset database is queried to obtain the reference medical data corresponding to the target impact factor and / or the target medical data indicator. The diagnostic results in the reference medical data are feature extracted to obtain the diagnostic reference information of the target medical disease.

[0137] In some embodiments of this application, the medical data acquisition device is also used for:

[0138] The influencing factors include at least one of the following: physical signs, anatomical parameters, clinical experience characteristics, and omics characteristics;

[0139] The vital signs parameters include at least one of the following: blood pressure, blood flow velocity, heart rate, and blood volume;

[0140] The anatomical parameters include at least one of the following: anatomical location, anatomical morphology, and anatomical volume;

[0141] The clinical experience characteristics refer to the characteristics of medical changes that occur in the body of a disease patient in the clinical record;

[0142] The omics features refer to features obtained through omics, proteomics, metabolomics, transcriptomics, lipidomics, immunoomics, glycomics, RNAmics, radiomics, and sonomics.

[0143] In this embodiment, medical reference indicators for medical diseases are pre-set. First, medical data samples are collected. Then, based on the medical reference indicators and the medical data indicators of the collected medical data samples, the data collection task is adjusted. Iterative collection is performed according to the adjusted data collection task until a target medical data sample whose medical data indicators match the medical reference indicators is collected and output. In this embodiment, the data collection task can be automatically adjusted to continuously collect medical data samples until the required medical data sample is obtained, thus realizing the automatic and accurate collection of medical data.

[0144] This application also provides a computer device, such as... Figure 8 As shown, Figure 8 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application.

[0145] The computer device includes a memory, a processor, and a medical data acquisition program stored in the memory and executable on the processor. When the processor executes the medical data acquisition program, it implements the steps of the medical data acquisition method provided in any embodiment of this application.

[0146] Specifically, a computer device may include components such as a processor 801 with one or more processing cores, a memory 802 with one or more storage media, a power supply 803, and an input unit 804. Those skilled in the art will understand that... Figure 8 The computer device structure shown does not constitute a limitation on the computer device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0147] The processor 801 is the control center of the computer device. It connects various parts of the computer device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 802, and by calling data stored in the memory 802, it performs various functions of the computer device and processes data, thereby providing overall monitoring of the computer device. Optionally, the processor 801 may include one or more processing cores; preferably, the processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 801.

[0148] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing by running the software programs and modules stored in the memory 802. The memory 802 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.

[0149] The computer device also includes a power supply 803 that supplies power to the various components. Preferably, the power supply 803 can be logically connected to the processor 801 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 803 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0150] The computer device may also include an input unit 804, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0151] Although not shown, the computer device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 801 in the computer device loads the executable files corresponding to the processes of one or more application programs into the memory 802 according to the following instructions, and the processor 801 runs the application programs stored in the memory 802, thereby implementing the steps in the medical data acquisition method provided in any embodiment of this application.

[0152] Therefore, embodiments of this application provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc. The computer-readable storage medium stores a medical data acquisition program, which, when executed by a processor, implements the steps of the medical data acquisition method provided in any embodiment of this application.

[0153] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the detailed descriptions of other embodiments above, which will not be repeated here.

[0154] In practice, each of the above units or structures can be implemented as an independent entity or can be arbitrarily combined to be implemented as the same or several entities. For the specific implementation of each of the above units or structures, please refer to the previous method embodiments, which will not be repeated here.

[0155] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0156] The above provides a detailed description of a medical data acquisition method provided by the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for acquiring medical data, characterized in that, The medical data acquisition method includes: In response to a medical data collection request, obtain the influencing factors associated with the medical diseases to be collected, as well as the corresponding medical reference indicators for the influencing factors; A preset data collector is invoked to execute the data collection task corresponding to the influencing factor to collect medical data samples, and the medical data samples are input into a preset data analyzer to obtain medical data indicators. The medical data indicators of the same type are compared with the medical reference indicators. If the medical data indicators do not match the medical reference indicators, the difference data indicators are obtained. For the data collection task corresponding to the difference data indicator, increase the sample size and proportion of the data collection task to obtain the adjusted data collection task; Iterative data collection is performed based on the adjusted data collection task until a target medical data sample that matches the medical reference index is collected and output. Obtain medical data samples corresponding to each of the data acquisition tasks, and extract the medical features of the medical data samples; The medical characteristics of the medical data sample are compared with the preset medical characteristics of the influence factor. If there is a target medical characteristic that is different from the preset medical characteristics, the target medical characteristic is added to the influence factor to obtain an updated influence factor. Configure the medical reference indicators corresponding to the updated impact factors and generate a new data collection task; Add data tags corresponding to the influencing factors and medical data indicators to the target medical data sample, and save it to a preset database; In response to a data analysis request, obtain the target medical disease corresponding to the data analysis request, as well as the target impact factor and / or target medical data indicator corresponding to the target medical disease; The preset database is queried to obtain the reference medical data corresponding to the target impact factor and / or the target medical data indicator. The diagnostic results in the reference medical data are feature extracted to obtain the diagnostic reference information of the target medical disease.

2. The medical data acquisition method according to claim 1, characterized in that, The process involves calling a preset data collector to execute the data collection task corresponding to the influencing factor, collecting medical data samples, and inputting the medical data samples into a preset data analyzer to obtain medical data indicators, including: Obtain the medical features associated with the influencing factors, and generate data collection tasks corresponding to each of the medical features; Each data acquisition task is assigned a preset data acquisition device to analyze the preset medical data and obtain the medical data sample corresponding to each data acquisition task. The medical data samples corresponding to each of the data acquisition tasks are input into the data analyzer corresponding to the data acquisition task to obtain the first medical feature, and medical data indicators are extracted from each of the first medical features.

3. The medical data acquisition method according to claim 1, characterized in that, The step of calling a preset data collector to execute the data collection task corresponding to the impact factor and collect medical data samples includes: Inputting target medical data of image type from preset medical data into the image recognition module of a preset data acquisition device to obtain the second medical feature of the target medical data; and / or, Input the target medical data (text type) into the character recognition module of the preset data acquisition device to obtain the second medical feature of the target medical data; Obtain target medical features that match the preset medical features of the influencing factors, and set the target medical data corresponding to the target medical features as medical data samples.

4. The medical data acquisition method according to any one of claims 1-3, characterized in that, The influencing factors include at least one of the following: physical signs, anatomical parameters, clinical experience characteristics, and omics characteristics; The vital signs parameters include at least one of the following: blood pressure, blood flow velocity, heart rate, and blood volume; The anatomical parameters include at least one of the following: anatomical location, anatomical morphology, and anatomical volume; The clinical experience characteristics refer to the characteristics of medical changes that occur in the body of a disease patient in the clinical record; The omics features refer to features obtained through omics, proteomics, metabolomics, transcriptomics, lipidomics, immunoomics, glycomics, RNAmics, radiomics, and sonomics.

5. A medical data acquisition device, characterized in that, The medical data acquisition device includes: The acquisition module is used to respond to medical data collection requests, acquire the influencing factors associated with the medical diseases to be collected, and the medical reference indicators corresponding to the influencing factors; The data acquisition module is used to call a preset data acquisition device to execute the data acquisition task corresponding to the influencing factor to collect medical data samples, and input the medical data samples into a preset data analyzer to obtain medical data indicators. The adjustment module is used to compare the medical data indicators of the same type with the medical reference indicators. If the medical data indicators do not match the medical reference indicators, the difference data indicators are obtained. For the data collection tasks corresponding to the difference data indicators, the sample size and proportion of the data collection tasks are increased to obtain the adjusted data collection tasks. The output module is used to iteratively collect data according to the adjusted data collection task until a target medical data sample that matches the medical reference index is collected and then output. The output module is further configured to acquire medical data samples corresponding to each data acquisition task, extract medical features from the medical data samples; compare the medical features of the medical data samples with preset medical features of the impact factors; if there are target medical features different from the preset medical features, add the target medical features to the impact factors to obtain updated impact factors; configure medical reference indicators corresponding to the updated impact factors and generate new data acquisition tasks; add data tags corresponding to the impact factors and medical data indicators to the target medical data samples and save them to a preset database; respond to data analysis requests, acquire the target medical disease corresponding to the data analysis request, and the target impact factors and / or target medical data indicators corresponding to the target medical disease; query the preset database to acquire reference medical data corresponding to the target impact factors and / or target medical data indicators, extract features from the diagnostic results in the reference medical data, and obtain diagnostic reference information for the target medical disease.

6. A computer device, characterized in that, The computer device includes: a processor, a memory, and a medical data acquisition program stored in the memory and executable on the processor, wherein the processor executes the medical data acquisition program to implement the steps of the medical data acquisition method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a medical data acquisition program, which is executed by a processor to implement the steps of the medical data acquisition method according to any one of claims 1 to 4.

Images