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Analysis on Deep Learning methods for ECG based Cardio,vascular Disease prediction

Publication Type : Journal Article

Publisher : Scalable Computing: Practice and Experience

Source : Scalable Computing: Practice and Experience;Volume 21, Issue 1, pp. 127–136

Url : https://www.researchgate.net/publication/340041238_Analysis_on_Deep_Learning_methods_for_ECG_based_Cardiovascular_Disease_prediction

Keywords : Deep learning, Python, CVD, ECG

Campus : Amritapuri

School : School of Engineering

Center : Computer Vision and Robotics

Department : Computer Science

Year : 2020

Abstract : The cardiovascular related diseases can however be controlled through earlier detection as well as risk evaluationand prediction. In this paper the application of deep learning methods for CVD diagnosis using ECG is addressed and alsodiscussed the deep learning with Python. A detailed analysis of related articles has been conducted. The results indicate thatconvolutional neural networks are the most widely used deep learning technique in the CVD diagnosis. This research paper looksinto the advantages of deep learning approaches that can be brought by developing a framework that can enhance prediction ofheart related diseases using ECG.

Cite this Research Publication : Kusuma S, Divya Udayan J, 2020, "Analysis on Deep Learning methods for ECG based Cardio,vascular Disease prediction", Scalable Computing: Practice and Experience, Vol 21, No. 1, pp. 127-136 (SCOPUS, ESCI).

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