Applications of Rough Sets in Health Sciences and Disease Diagnosis

Soft computing is a consortium of techniques that work together to setup flexible information processing capability for handling real-life ambiguous situations. It aims at solving problems involving uncertainty and imprecision mimicking the human like decision making. Fuzzy set theory is an approach that has been widely adopted in such situations. Rough Set Theory (RST) is another soft computing approach that uses sets to represent vague or incomplete knowledge and provide a framework for approximation of concepts. It has been widely used to deal with imprecision in health sciences such as in patient diagnosis and disease classification. In this paper we present a review of rough set theory and its applications in disease diagnosis with several examples using real data sets. Key-Words: Rough Set Theory, Soft Computing, Vague data, Imprecision, Health Sciences, Disease diagnosis