Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network

作者：

Highlights：

• Classification of normal and CAD ECG segments.

• Two and five seconds ECG segments are considered.

• Convolutional neural network is used.

• QRS detection is not required.

• Accuracy of 94.95% and 95.11% are obtained for two and five seconds ECG segments respectively.

摘要

•Classification of normal and CAD ECG segments.•Two and five seconds ECG segments are considered.•Convolutional neural network is used.•QRS detection is not required.•Accuracy of 94.95% and 95.11% are obtained for two and five seconds ECG segments respectively.

论文关键词：CAD,ECG,CNN,Feature,Heart,Training,Testing

论文评审过程：Received 2 May 2017, Revised 31 May 2017, Accepted 2 June 2017, Available online 3 June 2017, Version of Record 24 July 2017.

论文官网地址：https://doi.org/10.1016/j.knosys.2017.06.003