Machine Learning and Deep Learning Techniques on Accurate Risk Prediction of Coronary Heart Disease

Abstract

Coronary artery disorder is the heart disease that is prevalent across the globe today. It's a serious issue for the humans as it requires proper diagnosis. Coronary artery disease develops over time as a result of plaque build- up in coronary arteries results in partial blockage of blood flow as the, which is primarily composed of cholesterol, calcium, and fibrin. Coronary arteries help human heart to pump oxygen-rich blood throughout the body by supplying it. However, appropriate diagnosis and early prediction will lessen the likelihood of developing it. This study explores the possibility of foreseeing cardiac illness at an early stage using deep learning algorithms. This study's primary goal is to properly determine whether a person has heart problems or not. by using deep learning techniques, Deep learning and various machine learning algorithms can both be used to implement early-stage prediction. Data mining, Decision trees, Naive Bayes, Artificial Neural Networks (ANN) are some examples through which it can be implemented. The research is going to be done using ANN Model.