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Health resources in developing countries are limited. So, efficient utilization of these resources is necessary. Limited medical staff is a challenge faced by many countries. Heart Disease is a critical disease that is usually not detected in the initial stages. Using the Decision Support System (DSS), heart disease can be diagnosed in a cost-effective way and in a timely manner. Several researchers have proposed different methods for prediction of heart disease using machine learning techniques. This paper provides an insight into the need and a variety of issues and challenges to use decision support systems to predict heart disease.