Abstract: In todays era prediction of diseases is made in the way of data mining that is providing big deal of finding hidden patterns in large data bases. This prediction is made on the basis of association rules which are large in number and consists of many looping of rules. This increases the complexity of the whole system to arrive a simple result. This association rules compares the parameters of tested data of a patient such as risk factors and arrives results of presence of disease by following some predictive rules which consists of branches in decision tree structure. So, researchers generate system that work on entropy weighted deviation approach having effective resource allocation and utilization of data in minimum cost. In future, the system provides an adept methods disease prediction in various bio-medical applications.
B. Gomathy, A. Shanmugam and S.M. Ramesh, 2013. An Efficient Entropy Weighted Deviation Approach to Simplify Weighted Association Rules in Bio Medical Applications. Asian Journal of Information Technology, 12: 228-235.