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An Analytical Model for Prediction of Heart Disease using Machine Learning Classifiers.pdf (759.47 kB)

An Analytical Model for Prediction of Heart Disease using Machine Learning Classifiers

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posted on 30.06.2021, 23:12 by Diti Roy, Md. Ashiq Mahmood, Tamal Joyti Roy

Heart Disease is the most dominating disease which is taking a large number of deaths every year. A report from WHO in 2016 portrayed that every year at least 17 million people die of heart disease. This number is gradually increasing day by day and WHO estimated that this death toll will reach the summit of 75 million by 2030. Despite having modern technology and health care system predicting heart disease is still beyond limitations. As the Machine Learning algorithm is a vital source predicting data from available data sets we have used a machine learning approach to predict heart disease. We have collected data from the UCI repository. In our study, we have used Random Forest, Zero R, Voted Perceptron, K star classifier. We have got the best result through the Random Forest classifier with an accuracy of 97.69.

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Email Address of Submitting Author

tjroy13june@gmail.com

ORCID of Submitting Author

0000-0002-5319-2726

Submitting Author's Institution

Khulna University of Engineering & Technology

Submitting Author's Country

Bangladesh

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