Implementation of Artificial Intelligence in Retinopathy of Prematurity Care: Challenges and Opportunities

作者：Andrew Tsai, Michelle Yip, Amy Song, Gavin Siew Wei Tan, Daniel Ting, J. Peter Campbell, Aaron S. Coyner, R.V. Paul Chan · 发表于：International Ophthalmology Clinics · 年份：2024 · DOI：10.1097/iio.0000000000000532 · 被引用次数：8 · 研究领域：Retinopathy of Prematurity Studies、Neonatal and fetal brain pathology、Neonatal Respiratory Health Research

The diagnosis of retinopathy of prematurity (ROP) is primarily image-based and suitable for implementation of artificial intelligence (AI) systems. Increasing incidence of ROP, especially in low and middle-income countries, has also put tremendous stress on health care systems. Barriers to the implementation of AI include infrastructure, regulatory, legal, cost, sustainability, and scalability. This review describes currently available AI and imaging systems, how a stable telemedicine infrastructure is crucial to AI implementation, and how successful ROP programs have been run in both low and middle-income countries and high-income countries. More work is needed in terms of validating AI systems with different populations with various low-cost imaging devices that have recently been developed. A sustainable and cost-effective ROP screening program is crucial in the prevention of childhood blindness.