Background Improved breast cancer risk assessment models are needed to enable
personalized screening strategies that achieve better harm-to-benefit ratio based on earlier …

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 …

Background Artificial intelligence (AI) as an independent reader of screening mammograms
has shown promise, but there are few prospective studies. Our aim was to conduct a …

Importance A computer algorithm that performs at or above the level of radiologists in
mammography screening assessment could improve the effectiveness of breast cancer …

Background We examined the potential change in cancer detection when using an artificial
intelligence (AI) cancer-detection software to triage certain screening examinations into a no …

Improved breast cancer risk models enable targeted screening strategies that achieve
earlier detection and less screening harm than existing guidelines. To bring deep learning …

PURPOSE Accurate risk assessment is essential for the success of population screening
programs in breast cancer. Models with high sensitivity and specificity would enable …

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 …

Screening mammography reduces breast cancer mortality, but studies analyzing interval
cancers diagnosed after negative screens have shown that many cancers are missed …

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 …