Comprehensive electrocardiographic diagnosis based on deep learning

作者：

Highlights：

• Deep learning techniques for classification of MI, CAD and CHF are discussed.

• First study to present deep learning technique for 4-class classification.

• CNN coupled with LSTM yielded a high accuracy of 98.51%.

• Future work using deep learning to detect early stages of CAD is proposed.

摘要

•Deep learning techniques for classification of MI, CAD and CHF are discussed.•First study to present deep learning technique for 4-class classification.•CNN coupled with LSTM yielded a high accuracy of 98.51%.•Future work using deep learning to detect early stages of CAD is proposed.

论文关键词：Cardiovascular diseases,Coronary artery disease,Myocardial infarction,Congestive heart failure,Deep learning,10-fold validation,Convolutional neural network,Long short-term memory

论文评审过程：Received 12 September 2019, Revised 6 November 2019, Accepted 31 December 2019, Available online 20 January 2020, Version of Record 27 January 2020.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.101789