Enhancement of Health Care System for Patient's Survival with Heart Failure Using Machine Learning

Abstract

Heart is one of the main organs in Human body that siphons the blood and supplies it to all the body parts. In clinical field, forecast of coronary illness at a beginning phase can be of most extreme significance. Coronary illness can be anticipated proficiently utilizing AI (ML) procedures. Accordingly, in this paper, we proposed three machines learning models viz., Random woodland (RF), Decision tree (DT) and Gaussian Naïve Bayes (GNB) classifier and assesses their exhibitions for the forecast of coronary illness at a beginning phase. The proposed models (for example RF and GNB) accomplished the exactness of 88.52% and 85.52%, separately that shows the adequacy of these ML models concerning forecast of coronary infections in patients before the sickness becomes deadly.

Laxman Singh, Prasanna Singh, Shikha Singh

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