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Obtaining Better Accuracy Using Fusion of Two Machine Learning Algorithms for Prediction of Heart Attack

Authors: Soumyashree M; A R S Bhaargav; Prashanth B K; S Ajith Kumar Reddy;

Obtaining Better Accuracy Using Fusion of Two Machine Learning Algorithms for Prediction of Heart Attack

Abstract

There are numerous terms and labels for heart illness. The effects and processes of a cardiac condition can be very complicated, especially for those who are experiencing them themselves or through a loved one of the victim. Therefore, the goal of this paper is to understand why heart disease plays a factor in nearly half of all reported fatalities in society. This paper will start by outlining the fundamental concepts of what a cardiac illness is and how people typically view it. Additionally, this paper will explore the most prevalent risk factors for developing heart disease, and we'll do it by employing ML algorithms using a hybrid model.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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