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

ABSTRACT:

Introduction

Artificial intelligence (AI) algorithms for interpreting mammograms have the potential to improve the effectiveness of population breast cancer screening programmes if they can detect cancers, including interval cancers, without contributing substantially to overdiagnosis. Studies suggesting that AI has comparable or greater accuracy than radiologists commonly employ 'enriched' datasets in which cancer prevalence is higher than in population screening. Routine screening outcome metrics (cancer detection and recall rates) cannot be estimated from these datasets, and accuracy estimates may be subject to spectrum bias which limits generalisabilty to real-world screening. We aim to address these limitations by comparing the accuracy of AI and radiologists in a cohort of con

SUBMITTER: Marinovich ML 

PROVIDER: S-EPMC8724814 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature