Importance Artificial intelligence (AI)–based retinopathy of prematurity (ROP) screening may
improve ROP care, but its cost-effectiveness is unknown. Objective To evaluate the relative …

OBJECTIVES: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a
result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial …

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 …

Importance Retinopathy of prematurity (ROP) is a leading cause of preventable blindness
that disproportionately affects children born in low-and middle-income countries (LMICs). In …

Real-world implementation of artificial intelligence for ROP diagnosis will require massive
efforts targeted at developing standards for data acquisition, true external validation, and …

PURPOSE: Neonatal care in middle-income countries has improved over the last decade,
leading to a “third epidemic” of retinopathy of prematurity (ROP). Without concomitant …

Importance Retinopathy of prematurity (ROP) telemedicine screening programs have been
found to be effective, but they rely on widefield digital fundus imaging (WDFI) cameras …

Objective To evaluate the cost-effectiveness of telemedicine and standard ophthalmoscopy
for retinopathy of prematurity (ROP) management. Methods Models were developed to …

Retrospective evaluation of a deep learning–derived retinopathy of prematurity (ROP)
vascular severity score in an operational ROP screening program demonstrated high …

Purpose To evaluate the performance of a deep learning (DL) algorithm for retinopathy of
prematurity (ROP) screening in Nepal and Mongolia. Design Retrospective analysis of …