Prediction of Ischemic Heart Disease in Patients Diagnosed with Coronavirus Disease (Covid-19) or Showing Symptoms of the Same using Machine Learning Algorithms and Ensemble Techniques

Ischemic Heart Disease (IHD) refers to the problems of the heart occurring due to narrowed heart arteries. Ischemic Heart Disease is also called as Coronary Heart Disease (CHD) or Coronary Artery Disease (CAD). Coronary artery is responsible for supplying blood to the heart muscle. IHD is caused by blockages in the coronary artery due to fat deposits or thrombus. Early diagnosis of IHD is critical. This research involves prediction of IHD in patients diagnosed with Coronavirus disease (Covid-19) or showing symptoms of the same. The dataset used for this research has been collected from nine hospitals across the Indian state of Maharashtra. It is a dataset of patients diagnosed with Coronavirus disease (Covid-19) or showing symptoms of the same. Machine Learning algorithms and ensemble methods have been used for the prediction of IHD. The algorithms used are Decision Tree, Random Forest, AdaBoost, CatBoost, LightGBM and XGBoost. The ensemble methods used are the Majority Voting Ensemble and Stacking. Maximum accuracy of 90.14% is obtained by using Majority Voting Ensemble which is an ensemble of Random Forest, XGBoost and AdaBoost algorithms using voting type as soft voting. Google colab has been used for the implementation of the project and the programming language used is Python.