Large-scale classification of 12-lead ECG with deep learning

Yu Jhen Chen, Chien Liang Liu, Vincent S. Tseng, Yu Feng Hu, Shih Ann Chen

研究成果: Conference contribution同行評審

6 引文 斯高帕斯(Scopus)

摘要

The 12-lead Electrocardiography(ECG) is the gold standard in diagnosing cardiovascular diseases, but most previous studies focused on 1-lead or 2-lead ECG. This work uses a large data set, comprising 7,704 12-lead ECG samples, as the data source, and the goal is to develop a classification model for six common types of urgent arrhythmias. We consider the characteristics of multivariate time-series data to design a novel deep learning model, combining convolutional neural network (CNN) and long short-Term memory (LSTM) to learn feature representations as well as the temporal relationship between the latent features. The experimental results indicate that the proposed model achieves promising results and outperforms the other alternatives. We also provide brief analysis about the proposed model.

原文English
主出版物標題2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728108483
DOIs
出版狀態Published - 五月 2019
事件2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Chicago, United States
持續時間: 19 五月 201922 五月 2019

出版系列

名字2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings

Conference

Conference2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019
國家/地區United States
城市Chicago
期間19/05/1922/05/19

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