PURPOSE: To evaluate the screening potential of a deep learning algorithm-derived severity score by determining its ability to detect clinically significant severe retinopathy of prematurity (ROP).
BACKGROUND AND OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. Screening and treatment reduces this risk, but requires multiple examinations of infants, most of whom will not develop severe disease. Previous wo...
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 intelligence (AI)-based screening in an Indian ROP telemedicine pr...
PURPOSE OF REVIEW: In this article, we review the current state of artificial intelligence applications in retinopathy of prematurity (ROP) and provide insight on challenges as well as strategies for bringing these algorithms to the bedside.
Retinopathy of prematurity (ROP) is the leading cause of childhood blindness in very-low-birthweight and very preterm infants in the United States. With improved survival of smaller babies, more infants are at risk for ROP, yet there is an increasing...
Retinal diseases affect an increasing number of patients worldwide because of the aging population. Request for diagnostic imaging in ophthalmology is ramping up, while the number of specialists keeps shrinking. Cutting-edge technology embedding arti...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.