Artificial Intelligence Detection of Diabetic Retinopathy: Subgroup Comparison of the EyeArt System with Ophthalmologists' Dilated Examinations.

Jennifer Irene Lim¹, Carl D Regillo², SriniVas R Sadda³, Eli Ipp⁴, Malavika Bhaskaranand⁵, Chaithanya Ramachandra⁵, Kaushal Solanki⁵

¹Department of Ophthalmology, University of Illinois, Illinois Eye and Ear Infirmary, Chicago, Illinois.

²Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania.

³Doheny Eye Center, Arcadia, California.

⁴The Lundquist Institute, Harbor-University of California, Los Angeles Medical Center, Torrance, California.

⁵Eyenuk, Inc., Los Angeles, California.

PubMed PMC DOI PDF

Abstract

OBJECTIVE: To compare general ophthalmologists, retina specialists, and the EyeArt Artificial Intelligence (AI) system to the clinical reference standard for detecting more than mild diabetic retinopathy (mtmDR). DESIGN: Prospective, pivotal, multicenter trial conducted from April 2017 to May 2018. PARTICIPANTS: Participants were aged ≥ 18 years who had diabetes mellitus and underwent dilated op…

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Mentioned Companies

Eyenuk, Inc.
affiliation

Other Funding

NEI NIH HHS(P30 EY001792)
United States
NEI NIH HHS(R44 EY026864)
United States
NEI NIH HHS(SB1 EY027241)
United States

Keywords

AI, artificial IntelligenceArtificial intelligence, Diabetic retinopathy, ScreeningCI, confidence intervalCSDME, clinically significant diabetic macular edemaDME, diabetic macular edemaDR, diabetic retinopathyFDA, Food and Drug AdministrationNPDR, nonproliferative diabetic retinopathyPDR, proliferative diabetic retinopathyWFPRC, Wisconsin Fundus Photograph Reading CentermtmDr, more than mild diabetic retinopathyvtDR, vision-threatening diabetic retinopathy

Article Info

PMID: 36345378
PMCID: PMC9636573
DOI: 10.1016/j.xops.2022.100228
Received: January 3, 2022
Accepted: September 22, 2022

How to Cite

Lim JI et al. Artificial Intelligence Detection of Diabetic Retinopathy: Subgroup Comparison of the EyeArt System with Ophthalmologists' Dilated Examinations. Ophthalmol Sci2023;3(1):100228. doi:10.1016/j.xops.2022.100228

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