Ten years later: how is AI impacting retina care today?
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.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.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.
Duke Scholars
Published In
DOI
EISSN
ISSN
Publication Date
Related Subject Headings
- Ophthalmology & Optometry
- 3212 Ophthalmology and optometry
- 1113 Opthalmology and Optometry
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Related Subject Headings
- Ophthalmology & Optometry
- 3212 Ophthalmology and optometry
- 1113 Opthalmology and Optometry