Optimized Deep Learning Model for Early Detection of Breast Cancer in Mammograms Using Vision Transformer

Breast cancer (BC) is a major global health issue and one of the leading causes of cancer-related mortality for women. A
timely and precise diagnosis using mammography analysis is essential for increasing survival rates. With the use of
Vision Transformers' (ViTs) potent representational capabilities, this research presents an improved deep learning (DL)
framework for the early identification and classification of BC in mammograms.