Clinical Diagnosis of Breast Cancer Samples Using Negative Selection Algorithm

Abstract

This chapter uses an artificial immune system applied for diagnosing breast cancer samples. Taking as basis an immunological process, the Negative Selection Algorithm was used to discriminate the samples, attaining a classification for benign or malignant cases.The main application of the method is to assist professionals in the breast cancer diagnostic process, thereby providing decision-making agility, efficient treatment planning, reliability and the necessary intervention to save lives. To evaluate this method, the Wisconsin Breast Cancer Diagnosis database was used. This is an actual breast cancer database.The results obtained using the method, when compared with the specialized literature, show accuracy, robustness and efficiency in the breast cancer diagnostic process.