Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee.

Anne Mackie, Alicja R Rudnicka, Steve Halligan, Catherine Egan, Adnan Tufail, Xiaoxuan Liu, Alastair K Denniston, Peter Scanlon, Zhivko Zhelev, Christopher Hyde, Trystan Macdonald, Jiri Fajtl, Bethany Shinkins, Rosalind Given-Wilson, J Kevin Dunbar, Sian Taylor-Philips

Journal: The Lancet. Digital health 2025;7(5):100840

PMID: 40185647

Abstract

Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automating parts of this process through artificial intelligence, commonly known as automated retinal imaging analysis software (ARIAS). A number of such products are now on the market. In the UK, Scotland has used a rules-based autograder since 2011, but the diabetic eye screening programmes in the rest of the UK rely solely on human graders. With more sophisticated machine learning-based ARIAS now available and greater challenges in terms of human grader capacity, in 2019 the UK's National Screening Committee (NSC) was asked to consider the modification of diabetic eye screening in England with ARIAS. Following up on a review of ARIAS research highlighting the strengths and limitations of existing evidence, the NSC here sets out their considerations for evaluating evidence to support the introduction of ARIAS into the diabetic eye screening programme.

Copyright © 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Address: College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHSFT, Birmingham, UK.; Exeter Test Group, College of Medicine and Health, University of Exeter Medical School, Exeter, UK.; School of Computer Science and Mathematics, Kingston University London, London, UK.; NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK; Institute of Ophthalmology, University College London, London, UK.; Population Health Research Institute, St George's University of London, London, UK.; Warwick Medical School, University of Warwick, Coventry, UK.; St George's University Hospitals NHS Foundation Trust, London, UK.; Vaccination and Screening Directorate, NHS England, London, UK.; Centre for Medical Imaging, Division of Medicine, University College London, London, UK.; Gloucestershire Hospitals NHS Foundation Trust, Cheltenham, UK.; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.; Warwick Medical School, University of Warwick, Coventry, UK; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.; College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHSFT, Birmingham, UK. Electronic address: [email protected].
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