Heart Disease Detection -A Machine Learning Approach

Abstract

One of the human body's most important organs is the heart. It helps the body's blood to circulate and become cleaner. The global leading cause of death is heart attack. Chest discomfort, a faster heartbeat, and breathing problems were a few indications. The accuracy of this data was regularly checked. This publication presented a broad summary of heart attacks and current treatments. Additionally, a quick overview of the important machine learning methods for heart attack prediction that are available in the literature is provided. The machine learning techniques described include Decision Tree, Logistic Regression, SVM, Naive Bayes, Random Forest, KNN, and XG Boost Classifier. The algorithms are contrasted based on the braced of characteristics.