Mammography Report

Mammography reports are crucial for breast cancer diagnosis, and research focuses on improving their analysis using computer-aided detection (CAD) systems. Current efforts leverage deep learning models, including convolutional neural networks (CNNs) and transformers, often incorporating multi-view and multi-instance learning techniques to analyze mammograms and associated textual reports, aiming to improve diagnostic accuracy and reduce false positives. These advancements hold significant promise for enhancing breast cancer screening, potentially leading to earlier detection and improved patient outcomes by assisting radiologists and increasing the efficiency of screening programs.