Screening for breast cancer with mammography has been introduced in various countries
over the last 30 years, initially using analog screen-film-based systems and, over the last 20 …

Despite its proven record as a breast cancer screening tool, mammography remains labor-
intensive and has recognized limitations, including low sensitivity in women with dense …

Accurate early detection of breast and cervical cancer is vital for treatment success. Here, we
conduct a meta-analysis to assess the diagnostic performance of deep learning (DL) …

Background Advances in computer processing and improvements in data availability have
led to the development of machine learning (ML) techniques for mammographic imaging …

Interpretability in machine learning models is important in high-stakes decisions such as
whether to order a biopsy based on a mammographic exam. Mammography poses …

Cancer is associated with significant morbimortality globally. Advances in screening,
diagnosis, management and survivorship were substantial in the last decades, however …

Mammography, or breast X-ray imaging, is the most widely used imaging modality to detect
cancer and other breast diseases. Recent studies have shown that deep learning-based …

Background Although several clinical breast cancer risk models are used to guide screening
and prevention, they have only moderate discrimination. Purpose To compare selected …

Retrospective studies have shown artificial intelligence (AI) algorithms can match as well as
enhance radiologist's performance in breast screening. These tools can facilitate tasks not …

Attempts to use computers to aid in the detection of breast malignancies date back more
than 20 years. Despite significant interest and investment, this has historically led to minimal …