Invention Grant
- Patent Title: Method and device for self-learning dynamic electrocardiography analysis employing artificial intelligence
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Application No.: US16651912Application Date: 2018-01-12
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Publication No.: US11234629B2Publication Date: 2022-02-01
- Inventor: Chang Liu , Chuanyan Hu , Weiwei Zhou , Haitao Lu , Jiayu Wang , Jun Cao
- Applicant: Shanghai Lepu CloudMed Co., Ltd
- Applicant Address: CN Shanghai
- Assignee: Shanghai Lepu CloudMed Co., Ltd
- Current Assignee: Shanghai Lepu CloudMed Co., Ltd
- Current Assignee Address: CN Shanghai
- Agency: TraskBritt
- Priority: CN201711203048.2 20171127
- International Application: PCT/CN2018/072359 WO 20180112
- International Announcement: WO2019/100565 WO 20190531
- Main IPC: A61B5/316
- IPC: A61B5/316 ; A61B5/00 ; A61B5/352 ; A61B5/364 ; A61B5/366

Abstract:
A self-learning dynamic electrocardiography analysis method employing artificial intelligence. The method comprises: pre-processing data, performing cardiac activity feature detection, interference signal detection and cardiac activity classification on the basis of a deep learning method, performing signal quality evaluation and lead combination, examining cardiac activity, performing analytic computations on an electrocardiogram event and parameters, and then automatically outputting report data. The method achieves an automatic analysis method for a quick and comprehensive dynamic electrocardiography process, and recording of modification information of an automatic analysis result, while also collecting and feeding back modification data to a deep learning model for continuous training, thereby continuously improving and enhancing the accuracy of the automatic analysis method. Also disclosed is a self-learning dynamic electrocardiography analysis device employing artificial intelligence.
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