Fuzzy C-Means Algorithm to Diagnose Breast Cancer

Abstract

The automatic diagnosis of breast cancer is an important, real-world medical problem. A major class of problems in Medical Science involves the diagnosis of disease, based upon various tests performed upon the patient. When several tests are involved, the ultimate diagnosis may be difficult to obtain, even for a medical expert. This has given rise, over the past few decades, to computerized diagnostic tools, intended to aid the Physician in making sense out of the confusion of data. This Paper carried out to generate and evaluate fuzzy model to predict malignancy of breast tumor, using Wisconsin Diagnosis Breast Cancer Database (WDBC). Our objectives in this Paper are: (i) to find the diagnostic performance of fuzzy model in distinction between malignance and benign patterns, (ii) to reduce the number of benign cases sent for biopsy using this model as a supportive tool, and (iii) to validate the capability of this model to recognize new cases.