Big data analysis for heart disease detection system using map reduce technique

In today's world, the enormous information in health care is to be processed in order to identify, diagnose, detect and prevent the various diseases. Big data analysis is the challenging one because big data contain large amount of records. It is proposed to develop a centralized patient monitoring system using big data. In the proposed system, large set of medical records are taken as input. From this medical dataset, it is aimed to extract the needed information from the record of heart patients using map reduce technique. Heart disease is a major health problem and it is the leading causes of death throughout the world. Early detection of heart disease has become an important issue in the medical research fields. For heart disease detection, some features are analyzed such as RR interval, QRS interval and QT interval. The classification process states whether the patient is normal or abnormal and in the detection step using map reduce technique to detect the disease and reduce the dataset. Thus, the proposed system helps to classify a large and complex medical dataset and detect the heart disease.