A Novel Approach for Heart Disease Prediction Based on Risk Factors Using Machine Learning
Lecture Notes in Networks and SystemsProceedings of the 2nd International Conference on Computational and Bio Engineering(2021)
Abstract
In the world, one of the most critical diseases that affect human life is heart disease. This disease occurs due to an insufficient amount of blood circulated to other parts of the body. The disease occurs due to many risk factors, such as age, diabetes, blood sugar, gender, cholesterol, and coronary heart disease, etc. Generally, this disease is diagnosed using medical history; in many aspects, this is not a reliable solution. So prevention of this disease using an accurate and efficient algorithm is needed. This paper developed a novel approach to prevent heart disease by considering two risk factors: coronary heart disease and diabetes. The performance of the proposed method has been validated on different machine learning algorithms. The proposed method can also assist the doctors in diagnosing patients suffering from heart attacks efficiently.
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Key words
SVM, Naive bayesian, Random forest, Heart disease, Sampling
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