Application of Data Mining for high accuracy prediction of breast tissue biopsy results

In today's world where awareness for Breast Cancer is being carried out at a large scale, we still lack the diagnostic tools to suggest whether a person is suffering from Breast Cancer or not. Mammography remains the most significant method of diagnosing someone with Breast Cancer. However, mammograms sometimes are not definite due to which a radiologist cannot pronounce his/her decision based solely on them and has to resort to a biopsy. This paper proposes a data mining technique based on Ensemble of classifiers following data pre-processing, to predict the outcomes of the biopsy using the features extracted from the mammograms. The results achieved in this paper on the Mammographic Masses dataset are highly promising and have an accuracy of 83.5% and an ROC (Receiver Operating Characteristics) area of 0.907 which is higher than the existing approaches.