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Conference 12035 > Paper 12035-28
Paper 12035-28

Test accuracy of artificial intelligence for examining breast screening mammograms: systematic review of current technologies in comparison to clinical requirements

In person: 21 February 2022 • 10:10 AM - 10:30 AM PST

Abstract

This systematic review reports the accuracy of artificial intelligence (AI) for detection of breast cancer in digital mammography. AI to replace or augment the radiologist performed well in smaller studies (1,086 women, 520 cancers, 5/5 AI systems more accurate than single radiologist in laboratory), but this has not yet translated to larger studies (79,910 women, 1,878 cancer, 94% of AI systems evaluated were less accurate than a single radiologist). AI to triage out normal cases screened out 53%, 45% and 50% of low-risk women but also 10%, 4% and 0% of cancers detected by radiologists. Prospective studies are needed.

Presenter

The Univ. of Warwick (United Kingdom)
Professor Sian Taylor-Phillips specialises in evidence review and synthesis for national policy-makers, and sits on the UK National Screening Committtee Adult Reference Group and AI Task Group. She also undertakes primary research specialising in breast cancer screening.
Presenter/Author
The Univ. of Warwick (United Kingdom)
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The Univ. of Warwick (United Kingdom)
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Chris Stinton
The Univ. of Warwick (United Kingdom)
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The Univ. of Warwick (United Kingdom)
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Aileen Clarke
The Univ. of Warwick (United Kingdom)
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The Univ. of Warwick (United Kingdom)
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The Univ. of Warwick (United Kingdom)