Artificial Immune Systems with Negative Selection Applied To Clinical Diagnosis of Breast Cancer Samples

Artificial Immune Systems with Negative Selection Applied To Clinical Diagnosis of Breast Cancer Samples

This paper uses an artificial immune systems with negative selection applied for diagnosing breast cancer samples. Taking as basis a biological process, the negative selection principle. This process is used to discriminate the samples, attaining a classification for benign or malignant cases. The main application of the method is 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 (99.77% of accuracy in the better configuration of methodology), when compared with the specialized literature, show accuracy, robustness and efficiency in the breast cancer diagnostic process.