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

Purpose To study the feasibility of automatically identifying normal digital mammography
(DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading …

Importance Chest radiography is the most common diagnostic imaging examination
performed in emergency departments (EDs). Augmenting clinicians with automated …

Although computers have had a role in interpretation of mammograms for at least two
decades, their impact on performance has not lived up to expectations. However, in the last …

Breast cancer screening has been shown to significantly reduce mortality in women. The
increased utilization of screening examinations has led to growing demands for rapid and …

Background To compare the breast cancer detection performance in digital mammograms of
a panel of three unaided human readers (HR) versus a stand-alone artificial intelligence (AI) …

Background Retrospective studies have shown promising results using artificial intelligence
(AI) to improve mammography screening accuracy and reduce screen-reading workload; …

During the past decade, researchers have investigated the use of computer-aided
mammography interpretation. With the application of deep learning technology, artificial …

Purpose To evaluate the benefits of an artificial intelligence (AI)–based tool for two-
dimensional mammography in the breast cancer detection process. Materials and Methods …

Importance Contemporary approaches to artificial intelligence (AI) based on deep learning
have generated interest in the application of AI to breast cancer screening (BCS). The US …