Purpose To summarize the literature regarding the performance of mammography-image
based artificial intelligence (AI) algorithms, with and without additional clinical data, for future …

Breast cancer remains the leading cause of cancer-related deaths in women worldwide.
Current screening regimens and clinical breast cancer risk assessment models use risk …

One of the most prevalent diseases affecting women in recent years is breast cancer. Early
breast cancer detection can help in the treatment, lower the infection risk, and worsen the …

Background Artificial intelligence (AI) may improve cancer detection and risk prediction
during mammography screening, but radiologists' preferences regarding its characteristics …

Dr Min Sun Bae is an associate professor of radiology at Inha University Hospital and
School of Medicine and serves on the editorial board in the breast imaging section of the …

This study proposes a deep convolutional neural network (DCNN) classification for the
quality control and validation of breast positioning criteria in mammography. A total of 1631 …

Breast cancer is the most common malignant tumor among women worldwide and remains
one of the leading causes of death among women. Its incidence and mortality rates are …

Background Artificial intelligence (AI) systems can be used to identify interval breast
cancers, although the localizations are not always accurate. Purpose To evaluate AI …

Background Novel artificial intelligence computer-assisted detection (AI-CAD) systems
based on deep learning (DL) promise to support screen reading. Purpose To test a DL-AI …

Simple Summary Cancer diagnosed in patients between the ages of 15 and 39 deserves
special consideration. Diagnoses within this cohort of adolescents and young adults include …