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).