Application of Rough Set Based Models in Medical Diagnosis

Abstract

Modeling intelligent system in the field of medical diagnosis is still a challenging work. Intelligent systems in medical diagnosis can be utilized as a supporting tool to the medical practitioner, mainly country like India with vast rural areas and absolute shortage of physicians. Intelligent systems in the field of medical diagnosis can also able to reduce cost and problems for the diagnosis like dynamic perturbations, shortage of physicians, etc. An intelligent system may be considered as an information system that provides answer to queries relating to the information stored in the Knowledge Base (KB), which is a repository of human knowledge. Rough set theory is an efficient model to capture uncertainty in data and the processing of data using rough set techniques is easy and convincing. Rule generation is an inherent component in rough set analysis. So, medical systems which have uncertainty inherent can be handled in a better way using rough sets and its variants. The objective of this chapter is to discuss on several such applications of rough set theory in medical diagnosis.