Fuzzy Analysis of Breast Cancer Disease using Fuzzy c-means and Pattern Recognition

Abstract

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. The automatic diagnosis of breast cancer is an important, real-world medical problem. In this article is introduced a new approach for diagnosis of breast cancer. The proposed approach uses Fuzzy c-means (FCM) algorithm and pattern recognition method. Algorithm has been applied to breast cancer clinic instances obtained from the University of Wisconsin. Using FCM algorithm clinic instances are grouped into two clusters, one with benign instances and other with malign instances. Further, input data are divided in train data and test data and success of each is evaluated. In pattern recognition method each input test data is assigned to one of the clusters obtained from the process of FCM classification. The proposed system has showed that the recommended system has a high accuracy.