Comparative Study of Classification algorithms used for the Prediction of Non-communicable diseases

Quality of life is considered as an important outcome in health research. The information science and technological advances plays a major role in public healthcare. Clinical Decision Support System helps to healthcare professionals to give better diagnostic decisions. Diagnosing Non-Communicable Diseases (NCD) viz., Cardio Vascular Diseases (CVD) and Diabetes Mellitus (DM) required accurate analysis and prediction. To overcome the problems of knowledge based CDSS, machine learning techniques acquire knowledge automatically from the previous patient's clinical data. The techniques used for the diagnosis are depending on a one or more combination of classifiers. The proposed system uses ensemble based methods to give better performance of particular disease prediction. The current ensemble approaches are the enhancement techniques which are based on each stage of outputs.