A Survey on Machine learning and Mining Techniques for heart disease prediction
DOI:
https://doi.org/10.61841/ams8jz68Keywords:
Heart disease, Classification, Decision tree, Random Forest, Naive Bayes, K-Nearest Neighbours, Super Vector Machine.Abstract
It is important to save lives by detecting the heart disease earlier. Machine Learning then Data Mining is used as a aid contraptions by using providing the essential data and classification in accordance with diagnose a heart disease, primarily based on concerning the given input data. This survey paper analyse a systematic literature review based on journal articles published since 2012. This study significantly analyse the chosen papers and finds gaps between the current literature yet is helpful because researchers anybody want in accordance with apply machine learning algorithms among clinical domains, especially concerning heart disease datasets. This survey finds oversee that prediction exactness beyond most popular machine learning algorithms permanency like Random Forest, Decision Trees, and K-Nearest Neighbours.
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