Heart Disease Prediction System by Using Machine Learning Methodologies

Abstract

There is a saying that “Health is wealth”. In the modern Modern world, being healthy is indeed a blessing. Our lives get easier as we evolve each day, but it also makes us lethargic and more susceptible to bad habits. Heart disease is a serious problem facing the world today. It caused death, and anyone can deal with it. Modern heart failure is also a disease that affects young people because of their unhealthy lifestyles. They are more susceptible to the disease because of high sugar intake, long screening times, and early morning awakenings. Most people are unable to recognize symptoms in the early stages, and by the time the patient reaches the hospital it is too late. Therefore, developing systems that can detect the early signs of disease is essential to stem the problem. The primary objective of this study is to provide physicians with mechanisms that accurately aid early diagnosis of heart disease using six machine learning (ML) models on performance parameter confusion metrics, accuracy, precision, f1 measure, and retrieval. to provide.