Analysis on deep learning methods for ECG based cardiovascular disease prediction

被引:0
|
作者
Kusuma S. [1 ]
Divya Udayan J. [2 ]
机构
[1] School of Computer Science and Engineering, Vellore Institute of Technology VIT, Vellore
[2] School of Information Technology and Engineering, Vellore Institute of Technology VIT, Vellore
来源
Scalable Computing | 2020年 / 21卷 / 01期
关键词
CVD; Deep learning; ECG; !text type='Python']Python[!/text;
D O I
10.12694/SCPE.V21I1.1640
中图分类号
学科分类号
摘要
The cardiovascular related diseases can however be controlled through earlier detection as well as risk evaluation and prediction. In this paper the application of deep learning methods for CVD diagnosis using ECG is addressed and also discussed the deep learning with Python. A detailed analysis of related articles has been conducted. The results indicate that convolutional neural networks are the most widely used deep learning technique in the CVD diagnosis. This research paper looks into the advantages of deep learning approaches that can be brought by developing a framework that can enhance prediction of heart related diseases using ECG. © 2020 SCPE.
引用
收藏
页码:127 / 136
页数:9
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