A Survey on Machine Learning Algorithms for Cardiovascular Diseases Prediction

Authors: Mrs J Amutha, Dr K Ruba Soundar, Mrs M Piramu, Dr K Murugesan

DOI: https://doi.org/10.5281/zenodo.4740277

Short DOI: https://doi.org/gjv5pg

Country: India

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Abstract: Heart is the most important part in all living organisms. Cardiovascular diseases or heart related diseases are at its peak in today’s world. Cardiovascular diseases prediction in a living being is a critical challenge analysis in the medical field. Machine learning algorithms are used in effective decision making, perfection and correctness because of little fatigue problem. In this work a survey has been done among various machine learning algorithms such as SVM, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN) and Random Forest with linear model to predict out of this heart disease. In performance level 92% is achieved through Support Vector Machine prediction model for heart diseases. Support Vector Machine method aims at finding large amount of feature by applying machine learning algorithm to improve the accuracy in the prediction of cardiovascular diseases.

Keywords: Heart Disease Classification, Support Vector Machine, Decision Tree, K-Nearest Neighbor, Artificial Neural Networks, Random Forest

Paper Id: 884

Published On: 2021-04-17

Published In: Volume 9, Issue 2, March-April 2021

Cite This: A Survey on Machine Learning Algorithms for Cardiovascular Diseases Prediction - Mrs J Amutha, Dr K Ruba Soundar, Mrs M Piramu, Dr K Murugesan - IJIRMPS Volume 9, Issue 2, March-April 2021. DOI 10.5281/zenodo.4740277

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