A Breast Cancer Diagnosis System: A Combined Approach Using Rough Sets and Probabilistic Neural Networks

In this paper, we present a medical decision support system based on a hybrid approach utilizing rough sets and a probabilistic neural network. We utilized the ability of rough sets to perform dimensionality reduction to eliminate redundant attributes from a biomedical dataset. We then utilized a probabilistic neural network to perform supervised classification. Our results indicate that rough sets were able to reduce the number of attributes in the dataset by 67% without sacrificing classification accuracy. Our classification accuracy results yielded results on the order of 93%