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Recommendation and distribution method and device for electrocardiogram data annotations

A technology of ECG data and data, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve the problems of heavy workload and low efficiency of ECG data labeling, improve labeling accuracy and labeling efficiency, and accurately deliver , the effect of accurate labeling

Active Publication Date: 2020-05-29
WUHAN ZHONGQI BIOLOGICAL MEDICAL ELECTRONICS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the above-mentioned technical deficiencies, provide a recommended distribution method, device and computer storage medium for ECG data labeling, and solve the technical problems of large workload and low efficiency of ECG data labeling in the prior art

Method used

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  • Recommendation and distribution method and device for electrocardiogram data annotations
  • Recommendation and distribution method and device for electrocardiogram data annotations
  • Recommendation and distribution method and device for electrocardiogram data annotations

Examples

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Embodiment 1

[0016] like figure 1 As shown, Embodiment 1 of the present invention provides a recommended distribution method for ECG data labeling, hereinafter referred to as the method, comprising the following steps:

[0017] S1. Establish an ECG sample data set, label each ECG sample data in the ECG sample data set, and obtain standard label data of all ECG sample data;

[0018] S2. According to the standard label data, it is judged whether the labeling results of each expert for each of the ECG sample data are accurate, and the labeling accuracy rate of each expert for each disease type is calculated to obtain an accuracy rate matrix;

[0019] S3. Using the ECG sample data as input data and the standard label data as output data, train the neural network to obtain a prediction model;

[0020] S4. Predict the electrocardiographic data to be labeled according to the prediction model to obtain its predicted disease type;

[0021] S5. Perform expert recommendation according to the predic...

Embodiment 2

[0053] Embodiment 2 of the present invention provides a device for recommending and distributing ECG data annotations, including a processor and a memory, and a computer program is stored in the memory. When the computer program is executed by the processor, the method provided in Embodiment 1 is realized. Recommended distribution method for ECG data annotation.

[0054] The recommended distribution device for ECG data annotation provided by the embodiment of the present invention is used to realize the recommended distribution method for ECG data annotation. The device is also available, and will not be repeated here.

Embodiment 3

[0056] Embodiment 3 of the present invention provides a computer storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for recommending distribution of ECG data annotation provided in Embodiment 1 is realized.

[0057] The computer storage medium provided by the embodiment of the present invention is used to implement the recommended distribution method for ECG data labeling. Therefore, the technical effects of the recommended distribution method for ECG data labeling are also provided by the computer storage medium, and will not be repeated here.

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Abstract

The invention relates to the technical field of electrocardiosignal labeling, and discloses a recommendation and distribution method for electrocardiogram data annotations. The method comprises the following steps: establishing an electrocardiogram sample data set, and annotating each piece of electrocardiogram sample data in the electrocardiogram sample data set to obtain standard label data of all the electrocardiogram sample data; judging whether the annotating result of each expert on each piece of electrocardiogram sample data is accurate or not according to the standard label data, and counting the annotation accuracy of each expert on each disease type to obtain an accuracy matrix; with the electrocardiogram sample data as input data and the standard label data as output data, training a neural network to obtain a prediction model; predicting to-be-annotated electrocardiogram data according to the prediction model to obtain a predicted disease type of the electrocardiogram data;and performing expert recommendation according to the predicted disease type and the accuracy matrix, and distributing the to-be-annotated electrocardiogram data to recommended experts for annotating. The method and the system have the technical effect of accurate electrocardiogram data annotation and delivery.

Description

technical field [0001] The present invention relates to the technical field of electrocardiographic data labeling, in particular to a recommended distribution method, device and computer storage medium for electrocardiographic data labeling. Background technique [0002] The method of deep learning in artificial intelligence is based on the training of a large number of sample data, and data plays a decisive role in deep learning. High-quality data that has been accurately labeled is what deep learning needs. If the wrongly labeled or incompletely labeled data participates in training, it will be harmful to the algorithm. Therefore, the accurate labeling of data has become the top priority in the work after data acquisition. The labeling of ECG data has the characteristics of heavy workload and low efficiency, which undoubtedly limits the application of deep learning methods in intelligent ECG diagnosis. Contents of the invention [0003] The purpose of the present inven...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0402A61B5/00
CPCA61B5/7267A61B5/7275A61B5/7235A61B5/318Y02A90/10
Inventor 罗伟朱涛
Owner WUHAN ZHONGQI BIOLOGICAL MEDICAL ELECTRONICS
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