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Artificial intelligence in retinal disease: clinical application, challenges, and future directions

Daich Varela, Malena; Sen, Sagnik; De Guimaraes, Thales Antonio Cabral; Kabiri, Nathaniel; Pontikos, Nikolas; Balaskas, Konstantinos; Michaelides, Michel; (2023) Artificial intelligence in retinal disease: clinical application, challenges, and future directions. Graefe's Archive for Clinical and Experimental Ophthalmology 10.1007/s00417-023-06052-x. (In press). Green open access

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Abstract

Retinal diseases are a leading cause of blindness in developed countries, accounting for the largest share of visually impaired children, working-age adults (inherited retinal disease), and elderly individuals (age-related macular degeneration). These conditions need specialised clinicians to interpret multimodal retinal imaging, with diagnosis and intervention potentially delayed. With an increasing and ageing population, this is becoming a global health priority. One solution is the development of artificial intelligence (AI) software to facilitate rapid data processing. Herein, we review research offering decision support for the diagnosis, classification, monitoring, and treatment of retinal disease using AI. We have prioritised diabetic retinopathy, age-related macular degeneration, inherited retinal disease, and retinopathy of prematurity. There is cautious optimism that these algorithms will be integrated into routine clinical practice to facilitate access to vision-saving treatments, improve efficiency of healthcare systems, and assist clinicians in processing the ever-increasing volume of multimodal data, thereby also liberating time for doctor-patient interaction and co-development of personalised management plans.

Type: Article
Title: Artificial intelligence in retinal disease: clinical application, challenges, and future directions
Location: Germany
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s00417-023-06052-x
Publisher version: https://doi.org/10.1007/s00417-023-06052-x
Language: English
Additional information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Age-related macular dystrophy, Artificial intelligence, Diabetic retinopathy, Inherited retinal disease, Retina
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology
URI: https://discovery.ucl.ac.uk/id/eprint/10170184
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