Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis
and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly …

Early detection decreases breast cancer death. The ACR recommends annual screening
beginning at age 40 for women of average risk and earlier and/or more intensive screening …

The potential of artificial intelligence (AI) to reduce health care disparities and inequities is
recognized, but it can also exacerbate these issues if not implemented in an equitable …

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

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

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

Breast density is an independent risk factor for breast cancer. In digital mammography and
digital breast tomosynthesis, breast density is assessed visually using the four-category …

Screening programs must balance the benefit of early detection with the cost of
overscreening. Here, we introduce a novel reinforcement learning-based framework for …

Background Inclusion of mammographic breast density (BD) in breast cancer risk models
improves accuracy, but accuracy remains modest. Interval cancer (IC) risk prediction may be …