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Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow
Published on: May 26, 2023
A clinical perspective on the expanding role of artificial intelligence in age-related macular degeneration
Himeesh Kumar1, Kai Lyn Goh1, Robyn H Guymer1
1Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Victoria, Australia.
Abstract:
In recent years, there has been intense development of artificial intelligence (AI) techniques, which have the potential to improve the clinical management of age-related macular degeneration (AMD) and facilitate the prevention of irreversible vision loss from this condition. Such AI techniques could be used as clinical decision support tools to: (i) improve the detection of AMD by community eye health practitioners, (ii) enhance risk stratification to enable personalised monitoring strategies for those with the early stages of AMD, and (iii) enable early detection of signs indicative of possible choroidal neovascularisation allowing triaging of patients requiring urgent review. This review discusses the latest developments in AI techniques that show promise for these tasks, as well as how they may help in the management of patients being treated for choroidal neovascularisation and in accelerating the discovery of new treatments in AMD.
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