An observational study to assess if automated diabetic retinopathy image assessment software can replace one or more steps of manual imaging grading and to determine their cost-effectiveness

Tufail, Adnan; Kapetanakis, Venediktos V; Salas-Vega, Sebastian; Egan, Catherine; Rudisill, Caroline; Owen, Christopher G; Lee, Aaron; Louw, Vern; Anderson, John; Liew, Gerald; Bolter, Louis; Bailey, Clare; Sadda, SriniVas; Taylor, Paul; Rudnicka, Alicja R

doi:10.3310/hta20920

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Two automated retinal image analysis systems achieved acceptable sensitivity and false positive rates for referable retinopathy, compared to human graders, and were cost saving.

Adnan Tufail, Venediktos V Kapetanakis, Sebastian Salas-Vega, Catherine Egan, Caroline Rudisill, Christopher G Owen, Aaron Lee, Vern Louw, John Anderson, Gerald Liew, Louis Bolter, Clare Bailey, SriniVas Sadda, Paul Taylor & Alicja R Rudnicka.

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Adnan Tufail ^1,^*, Venediktos V Kapetanakis ², Sebastian Salas-Vega ³, Catherine Egan ¹, Caroline Rudisill ³, Christopher G Owen ², Aaron Lee ¹, Vern Louw ¹, John Anderson ⁴, Gerald Liew ¹, Louis Bolter ⁴, Clare Bailey ⁵, SriniVas Sadda ⁶, Paul Taylor ⁷, Alicja R Rudnicka ²

¹ National Institute for Health Research Moorfields Biomedical Research Centre, Moorfields Eye Hospital, London, UK
² Population Health Research Institute, St George’s, University of London, London, UK
³ Department of Social Policy, LSE Health, London School of Economics and Political Science, London, UK
⁴ Homerton University Hospital Foundation Trust, London, UK
⁵ Bristol Eye Hospital, Bristol, UK
⁶ Doheny Eye Institute, Los Angeles, CA, USA
⁷ Centre for Health Informatics & Multiprofessional Education (CHIME), Institute of Health Informatics, University College London, London, UK
^* Corresponding author Email: adnan.tufail@moorfields.nhs.uk

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