Cognitive Analysis of Data Mining Tools Application in Health Care Services

Advances in the health care industry leads to collection of huge amounts of health care data in the form of electronic health records, wearable sensor device and using data recorded on smart gadgets. These data contain some hidden information for making effective decision. Health care data sets are need to be mined to extract useful information for a medical expert to take early detection of disease. Open source tools are used to predict detection of disease. This paper presents the features of existing simulators like Weka, RapidMiner, Spyder, Orange, R tool, KNIME. It explores on divers practical, functional, cognitive features of each tool used. Performance analysis of data mining classification techniques using two simulation tools over the health care data sets are presented to predict chances of heart disease. Various data mining algorithm’s accuracy, precision, F1 score are analyzed. Paper suggests the selection of tool and algorithm for the predictive data analytics in health care sector.