Breast Cancer Diagnosis Through Soft Computing Approaches: A Survey

Breast cancer is one of the deadly diseases; it is the cause of major fatality among women. The survival rate can be increased by early detection of the breast cancer. Typical diagnosis procedure of breast cancer involves biopsy, which is a painful process and that itself leads to some other problems. Technological development of soft computing and artificial intelligence contributed a lot towards disease diagnosis in medical sciences. There are number of soft computing techniques like Data mining, Machine learning, Neural networks, Fuzzy logic, Support vector machine, Wavelet based feature extraction, etc. are used in breast cancer diagnosis. Each method has its novelty, advantages and limitations. The soft computing approaches involved in breast cancer diagnosis has been reviewed in this paper.