Hepatitis B Disease Diagnosis Using Rough Set

Abstract

This paper describes processing of the medical data by means of the prediction system based on Rough Set Theory (RST). The Rough Sets proved to be very useful for the analysis of the decision problems concerning objects described in a data table by a set of condition attributes as well as a set of decision attributes. In order to make efficient data analysis and suggestive predictions in a case of the data of patients suffering from viral hepatitis were used to predict a probability of their death or serious disability. This paper also demonstrates an extension of the Rough Set methodology for reducing number of input data in order to increase prediction accuracy without loss of knowledge.