Objectives Artificial intelligence (AI) has shown promising results when used on
retrospective data from mammographic screening. However, few studies have explored the …

Introduction: Various factors are driving interest in the application of artificial intelligence (AI)
for breast cancer (BC) detection, but it is unclear whether the evidence warrants large-scale …

Background Artificial intelligence (AI) systems performing at radiologist-like levels in the
evaluation of digital mammography (DM) would improve breast cancer screening accuracy …

Background Mammography is the current standard for breast cancer screening. This study
aimed to develop an artificial intelligence (AI) algorithm for diagnosis of breast cancer in …

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

Accumulating evidence from retrospective studies demonstrate at least non-inferior
performance when using AI algorithms with different strategies versus double-reading in …

Background: The aim of this study is to systematically review the literature to summarize the
evidence surrounding the clinical utility of artificial intelligence (AI) in the field of …

Background Automation bias (the propensity for humans to favor suggestions from
automated decision-making systems) is a known source of error in human-machine …

Screening mammography aims to identify breast cancer at earlier stages of the disease,
when treatment can be more successful. Despite the existence of screening programmes …

Background Recent deep learning (DL) approaches have shown promise in improving
sensitivity but have not addressed limitations in radiologist specificity or efficiency. Purpose …