Prospective evaluation of artificial intelligence integration into breast cancer screening in multiple workflow settings: the GEMINI study.

Clarisse Florence de Vries¹, Gerald Lip², Roger Todd Staff², Jaroslaw Artur Dymiter³, Benjamin Tse², Annie Ng⁴, Georgia Fox⁵, Cary Oberije⁵, Lesley Ann Anderson^6,7

¹Glasgow Lab for Data Science & AI, Public Health, School of Health and Wellbeing, University of Glasgow, Glasgow, UK. clarisse.devries@glasgow.ac.uk.

²National Health Service Grampian, Aberdeen, UK.

³Grampian Data Safe Haven (DaSH), University of Aberdeen, Aberdeen, UK.

⁴DeepHealth Inc., Somerville, MA, USA.

⁵Kheiron Medical Technologies Ltd., London, UK.

⁶Biostatistics and Health Data Science, Institute of Applied Health Sciences, School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, UK.

⁷Interdisciplinary Institute, University of Aberdeen, Aberdeen, UK.

PubMed PMC DOI PDF

Abstract

Artificial intelligence (AI) tools can improve breast screening performance but different screening sites have varying needs. Here the GEMINI prospective evaluation of 10,889 women, within one UK region, used both live AI integration and simulations to model 17 different ways AI could be used in breast screening. All women received routine care. One AI tool was assessed. When the AI tool recommend…

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