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Retinal pigment score to assess diabetic retinopathy detection across multiple artificial intelligence vendors in a large diverse cohort

Olvera-Barrios, A; Shakespeare, R; Rajesh, A; Warwick, A; Chambers, R; Bolter, L; Anderson, JV; Fajtl, J; Barman, S; Stuart, KV; et al. Olvera-Barrios, A; Shakespeare, R; Rajesh, A; Warwick, A; Chambers, R; Bolter, L; Anderson, JV; Fajtl, J; Barman, S; Stuart, KV; Biradar, M; Luben, R; Khawaja, A; Owen, CG; Rudnicka, A; Tufail, A; Wu, Y; Lee, AY; Egan, CA (2025) Retinal pigment score to assess diabetic retinopathy detection across multiple artificial intelligence vendors in a large diverse cohort. In: ARVO 2025, INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, May 4-8 2025, Salt Lake City, USA.
SGUL Authors: Owen, Christopher Grant Rudnicka, Alicja Regina

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Item Type: Conference or Workshop Item (Paper)
Additional Information: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0).
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE
Article Number: 5483
ISSN: 0146-0404
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Publisher License: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Dates:
Date Event
2025-06 Published
URI: https://openaccess.sgul.ac.uk/id/eprint/118279

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