REVIEW ARTICLE


Review On Machine Learning and Deep Learning-based Heart Disease Classification and Prediction



S. Deepika1, N. Jaisankar2, *
1 Research Scholar, School of Computer Science and Engineering, VIT, Vellore, India
2 School of Computer Science and Engineering, VIT, Vellore, India


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Creative Commons License
© 2023 Deepika and Jaisankar

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the School of Computer Science and Engineering, VIT, Vellore, India; E-mail: njaisankar@vit.ac.in


Abstract

Coronary Heart disease is the major factor for people’s deaths throughout the world, and it is necessary to detect and predict the disease in the earlier stages because time plays a vital role to save the coronary patient. From this paper, the authors can conclude that authors have used most of the machine learning and deep learning ensemble algorithms so that they can predict heart disease at the early stage so that the patient’s life can be saved.

Keywords: Echocardiogram, Left ventricular ejection fraction, Cardiomyopathy classification, Low ejection, Ensembled algorithm, Transfer learning, Convolution neural network (CNN), Multilayer perceptron (MLP).