C Kalyan 01 02 With breast cancer still among leading causes of death in women all over the world it is imperative thatan early detection will make treatment possible To enhance the rate of accuracy in diagnosis this research is inclinedto breast cancer mining through this approach in mammogram and by data mining and machine learning methodsThe mammograms that have been processed and examined are sought to identify the patterns and characteristics thatdenote malignant tumors To extract the features texture analysis and shape descriptors are applied whereas SupportVector Machines SVM and Convolutional Neural Networks CNN are applied as classification methods Theproposed approach aims to augment early detection as well as reduce the number of false positives The evidenceindicates that datadriven mammography analysis stands to be of great benefit to radiologists so they could makequicker and more accurate diagnoses of breast cancer in an effort to better the patient Copyright (c) Journal of Engineering Technology and Sciences. All rights reserved 2026