Breast cancer is the deadliest disease and the major cause of cancer deaths in women worldwide. The milestone in breast cancer diagnosis is to distinguish malignant tumour from benign breast tumour for which reliable diagnostic procedure is required by the physicians.Prognosis of breast cancer is to predict the recurrence in breast cancer patients for whom they had their excision already. Data mining techniques have revolutionized the diagnostic and prognostic procedure in breast cancer. One of the new research's in data mining application involves analyzing. This survey work analyses the various reviews and technical articles, on breast cancer diagnosis. The main goal of this research is to explore the overview of the current research being carried out using the data mining techniques to enhance the breast cancer diagnosis.
Keywords: Breast cancer, Naive Bayes, C4.5 classification decision tree algorithm, Bayesian Networks.