Identification of Coronary Artery Disease using Extra Tree Classification

Caused by a shortage of oxygen-rich blood, cardiac artery disease occurs when coronary arteries get blocked. Arterial occlusion decreases the heart's blood flow and hence its oxygen supply. Plaque buildup is the leading cause of arterial obstruction. Both cholesterol and calcium can be found in plaque. Atherosclerosis refers to the development of plaque within the arteries. It is possible to have total ischemia due to an arterial clot. As arterial plaque ruptures, blood clots form. A diet rich in cholesterol can contribute to the development of plaque in a person's arteries. Cholesterol is transported in the bloodstream via lipoproteins, which are protein complexes. Lipoproteins come in two main types, high-density (HDL) and low-density (LDL). Plaque builds up in the arteries when levels of LDL are too high. The term “bad cholesterol” (LDL) is also commonly used. HDL is responsible for transporting cholesterol from the blood to the liver. HDL is the “good” or “healthy” cholesterol. Maintaining healthy levels of LDL and HDL is crucial for avoiding CAD. This research study has developed a ETC (Extra Tree Classification) approach for CAD diagnosis. The proposed approach employed the Z-Alizadeh Sani CAD dataset and employed SMOTE to address the issue of class imbalance. Classification was carried out utilizing classifiers such as XGBoost (extreme gradient boosting), KNN (K-nearest neighbour), SVM-Linear (support vector machine - linear), and SVM-RBF (support vector machine - radial basis function). After employing the GridSearch optimization approach, the hyper-parameters were fine-tuned to an accuracy of 95.16 percent.