Predictive Analysis for the Detection of Human Diseases CVD, CKD, DM Based on Supervised and Ensemble Machine Learning Classification Algorithms

Because of the high risk globally in the health care sector, the Chronic kidney disease (CKD), Cardio Vascular Disease (CVD), Diabetes Mellitus (DM) are the major burden because of its increasing pervasiveness. Cardio Vascular Disease (CVD), Chronic Kidney Disease (CKD) and Diabetes Mellitus are from the most active disease and the leading causes of death worldwide in the health care sector. Machine learning is playing an essential role in the medical side. In this paper, ensemble learning methods are used to enhance the performance of predicting heart disease, kidney disease and also diabetes disease. In this paper, we have shown some real time analysis by the help of supervised and ensemble machine learning classification algorithms. We have found the accuracy rate of approx. 90% in the early stage of prediction of disease, which is much better from the previous research papers.