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Analysis on Deep Learning methods for ECG based Cardiovascular Disease prediction
Author(s) -
S. Kusuma,
J. Divya Udayan
Publication year - 2020
Publication title -
scalable computing practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.192
H-Index - 18
ISSN - 1895-1767
DOI - 10.12694/scpe.v21i1.1640
Subject(s) - deep learning , artificial intelligence , convolutional neural network , computer science , machine learning , disease , artificial neural network , medicine
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.

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