Prediction of Cardiac Diseases with Dobutamine Stress Echocardiography

The heart is one of the essential organs in the human body. People are suffering from ‘Myocardial Infraction’, ‘Angioplasty’ and ‘Bypass surgery’ or sudden death. Stress Echocardiography involves raising patients’ heart rates through exercise. Then, take various measurements by pressuring the heart. Dobutamine can be used to pressure the heart, called Dobutamine Stress Echocardiography. Therefore, the main objective of this study is to propose models to predict cardiac diseases that can happen after giving the Dobutamine drug. This study was performed on a sample of 558 patients. This sample was taken by the Adult Cardiac Imaging and Hemodynamics Laboratories officers at the University of California, Los Angeles (UCLA). The study fits the statistical and machine learning models such as K-Nearest Neighbors (KNN), Naïve Bayes, Support Vector Machine (SVM), Decision Tree, Random Forest, Bagging methods with SVM, Gradient Boost, Extreme Gradient Boost (XG Boost), and Feedforward Neural Network (FFNN). Moreover, the hyperparametric tuning with the help of K-Fold Cross Validation techniques and Boosting methods were used to validate the fitted models and obtain better predictions. Furthermore, scaling methods such as Min-Max Scaling, Standard Scaling, and Quantile Scaling were used and handled the outliers to get better predictions without wasting much time. This study proposed five models corresponding to three diseases, sudden death, and any of these events. Myocardial infarction, angioplasty, bypass surgery, cardiac death, and any of these events can predict with 94.98%, 96.43%, 94.27%, 95.7%, and 84.44% accuracies.