Gillian J Knott, Martina F Mylrea, Beverley D Glass
Pharmacist and student evaluation of a preceptor training program in a regional Australian University: a multi-method study
BMC medical education
breast cancer leading cause mortality among women india globally prevalence breast masses notably common women aged 20 60 breast masses classified according breast imagingreporting data systems birads standard categories fibroadenoma breast cysts benign malignant masses aid diagnosis breast disorders imaging plays vital role mammography widely used modality detecting breast abnormalities years however process identifying breast diseases mammograms timeconsuming requiring experienced radiologists review significant volume images early detection breast masses crucial effective disease management ultimately reducing mortality rates address challenge advancements image processing techniques specifically utilizing artificial intelligence ai machine learning ml tiled way development decision support systems systems assist radiologists accurate identification classification breast disorders paper presents review various studies diverse machine learning approaches applied digital mammograms approaches aim identify breast masses classify distinct subclasses normal benign malignant additionally paper highlights advantages limitations existing techniques offering valuable insights benefit future research endeavors critical area medical imaging breast health