Significance of Data Mining in Disease Classification and Prediction for Mining Clinical Data : A Review

Abstract

Data Mining is a well established area of research that has become increasingly popular in health domain in recent years. It plays a vital role the health care towards uncovering latest trends specifically in early disease predictions. Data Mining is now becoming helpful for researchers and scientist towards gaining novel and deep insights of any large biomedical datasets. Uncovering new biomedical and healthcare related knowledge in order to support clinical decision making, is another dimension of data mining. Early disease prediction has now become the most demanding area of research in health care sector. As health care domain is bit wider domain and having different disease characteristics, different techniques have their own prediction efficiencies, which can be increased and tuned in order to get into most optimize way. In this research work, authors have comprehensively compared different data mining techniques and their prediction capability on different set of diseases datasets. Authors also have discussed different Data Mining Techniques such as classification, clustering, association, regression and their applicability and prediction efficiency specifically in health domain.