The American Society of Retina Specialists Artificial Intelligence Task Force Report. (July 2020)

• Record Type: Journal Article
• Authors: Talcott, Katherine E.; Kim, Judy E.; Modi, Yasha; Moshfeghi, Darius M.; Singh, Rishi P.
• Is Part Of: Journal of vitreoretinal diseases. Volume 4:Number 4(2020)
• Page Start: 312
• Page End: 319
• Publication Date: 2020-07
• Subjects: age-related macular degeneration -- artificial intelligence -- deep learning -- diabetic macular edema -- diabetic retinopathy -- fundus photographs -- optical coherence tomography -- retinopathy of prematurity; Retina -- Diseases -- Periodicals; Vitreous body -- Diseases -- Periodicals; Retina -- Diseases; Vitreous body -- Diseases; Periodicals; 617.735005
• DOI: 10.1177/2474126420914168
• Languages: English
• ISSNs: 2474-1264

Abstract

Artificial intelligence (AI) is a growing area that relies on the heavy use of diagnostic imaging within the field of retina to offer exciting advancements in diagnostic capability to better understand and manage retinal conditions such as diabetic retinopathy, diabetic macular edema, age-related macular degeneration, and retinopathy of prematurity. However, there are discrepancies between the findings of these AI programs and their referral recommendations compared with evidence-based referral patterns, such as Preferred Practice Patterns by the American Academy of Ophthalmology. The overall focus of this task force report is to first describe the work in AI being completed in the management of retinal conditions. This report also discusses the guidelines of the Preferred Practice Pattern and how they can be used in the emerging field of AI.