In the last couple of decades, many techniques have been introduced for medical support system. One alarming field in medical health care is cardiovascular disease as millions of deaths occur every year because of this. Thus, diagnosis of heart disease has always been one of the most important issues. For predicting and diagnosis of cardiovascular disease, skilled and experienced physicians are needed. As this is an era of technology, researchers have been proposed many algorithms and learning techniques for assisting the physicians. The aim of this research work is to thoroughly analyze these algorithms and methods. This article has explored the used datasets, feature selection techniques and missing value imputation methods, and finally compared their performances.