Aaron S Coyner, Tom Murickan, Minn A Oh, Benjamin K Young, Susan R Ostmo, Praveer Singh, R V Paul Chan, Darius M Moshfeghi, Parag K Shah, Narendran Venkatapathy, Michael F Chiang, Jayashree Kalpathy-Cramer, J Peter Campbell
IMPORTANCE: Retinopathy of prematurity (ROP) is a leading cause of blindness in children, with significant disparities in outcomes between high-income and low-income countries, due in part to insufficient access to ROP screening. OBJECTIVE: To evaluate how well autonomous artificial intelligence (AI)-based ROP screening can detect more-than-mild ROP (mtmROP) and type 1 ROP. DESIGN, SETTING, AND PARTICIPANTS: This diagnostic study evaluated the performance of an AI algorithm, trained and calibrated using 2530 examinations from 843 infants in the Imaging and Informatics in Retinopathy of Prematurity (i-ROP) study, on 2 external datasets (6245 examinations from 1545 infants in the Stanford University Network for Diagnosis of ROP [SUNDROP] and 5635 examinations from 2699 infants in the Aravind Eye Care Systems [AECS] telemedicine programs)...
March 7, 2024: JAMA Ophthalmology