Artificial intelligence (AI) for breast cancer screening: BreastScreen population-based cohort study of cancer detection.

ABSTRACT:

Background

Artificial intelligence (AI) has been proposed to reduce false-positive screens, increase cancer detection rates (CDRs), and address resourcing challenges faced by breast screening programs. We compared the accuracy of AI versus radiologists in real-world population breast cancer screening, and estimated potential impacts on CDR, recall and workload for simulated AI-radiologist reading.

Methods

External validation of a commercially-available AI algorithm in a retrospective cohort of 108,970 consecutive mammograms from a population-based screening program, with ascertained outcomes (including interval cancers by registry linkage). Area under the ROC curve (AUC), sensitivity and specificity for AI were compared with radiologists who interpreted the screens in practi

SUBMITTER: Marinovich ML 

PROVIDER: S-EPMC9996220 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature