Background The workflow of breast cancer screening programs could be improved given the
high workload and the high number of false-positive and false-negative assessments …

Background Use of artificial intelligence (AI) as a stand-alone reader for digital
mammography (DM) or digital breast tomosynthesis (DBT) breast screening could ease …

Background Digital breast tomosynthesis (DBT) has higher diagnostic accuracy than digital
mammography, but interpretation time is substantially longer. Artificial intelligence (AI) could …

Objectives Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is
increasingly implemented in breast cancer screening. However, the large volume of images …

Background The high volume of data in digital breast tomosynthesis (DBT) and the lack of
agreement on how to best implement it in screening programs makes its use challenging …

Background There is considerable interest in the potential use of artificial intelligence (AI)
systems in mammographic screening. However, it is essential to critically evaluate the …

Background Digital breast tomosynthesis (DBT) is replacing digital mammography (DM) in
the clinical workflow. Currently, there are limited prospective studies comparing the …

Purpose To evaluate the use of artificial intelligence (AI) to shorten digital breast
tomosynthesis (DBT) reading time while maintaining or improving accuracy. Materials and …

Purpose To compare screening recall rates and cancer detection rates of tomosynthesis
plus conventional digital mammography to those of conventional digital mammography …

Objectives To evaluate the potential of artificial intelligence (AI) to identify normal
mammograms in a screening population. Methods In this retrospective study, 9581 double …