Ten years later: how is AI impacting retina care today?

Curr Opin Ophthalmol. 2025 Aug 27. doi: 10.1097/ICU.0000000000001167. Online ahead of print.

Abstract

Purpose of review: Artificial intelligence (AI) is transforming retina care, with deep learning (DL) models shaping a new era of improved screening accessibility, diagnostic precision, and personalized disease monitoring. This review highlights recent AI-powered clinical applications in diabetic retinopathy (DR), and age-related macular degeneration (AMD) care.

Recent findings: Since the FDA's authorization of the first autonomous AI system for DR screening in 2018, multiple platforms have emerged, expanding access to diabetic eye care. Real-world studies have confirmed a significant improvement in screening adherence and diagnostic accuracy, illustrating AI's tangible impact on public health. Meanwhile, newly certified AI technologies that meet European regulatory standards are increasingly guiding clinical decision-making in the management of AMD and diabetic macular edema through automated analysis of optical coherence tomography (OCT) images. Most recently, FDA-authorized home OCT platforms are transforming AMD monitoring, enabling proactive and remote management of retinal fluid.

Summary: As AI increasingly empowers patients and providers, its widespread success still depends on ongoing work, including thorough validation, outcome-based metrics, and improved workflow integration. The next decade will reveal whether AI in retina care transitions from a promising innovation to an essential and indispensable tool in modern retina.

Keywords: age-related macular degeneration; artificial intelligence; diabetic retinopathy; imaging; retina.