AI foundation models show promise for universal eye care but face real-world deployment barriers
A systematic review published in Advances in Ophthalmology Practice and Research examines how AI foundation models are shifting ophthalmology from single-purpose algorithms to flexible systems that connect images, clinical language, and patient data. Models like RETFound and VisionFM demonstrate strong diagnostic performance across multiple eye diseases, but challenges including algorithmic bias, limited interpretability, and insufficient clinical validation must be addressed before widespread adoption.