Summary
This team’s literature review examines approaches to reducing automation bias in artificial intelligence medical imaging due to missing demographic data on race and sex. It explores how these biases impact clinician trust and diagnostic accuracy, particularly for women and racial minorities. The findings will guide future experimental designs to address these issues.