FP20

The Significance of Artificial Intelligence in Ophthalmology for clinical practice, academic & research purposes & surgical procedures. 

Purpose: The impact of AI in ophthalmology across clinical, research, and surgical domains.

Methods: Narrative synthesis of recent studies evaluating AI applications in retinal imaging, natural language processing for literature synthesis, and surgical systems.

Results: AI algorithms demonstrate high diagnostic accuracy for retinal disease detection and comparable performance to specialists in identifying ARMD and glaucoma. Natural language processing and machine‑learning data‑mining accelerate evidence synthesis and biomarker discovery. In surgical practice, AI-guided and robotic platforms improve intraoperative guidance, reduce operative time, and enhance IOL placement accuracy, contributing to better postoperative outcomes.

Conclusions: AI integration enhances diagnostic precision, streamlines research workflows, and refines surgical performance. Continued validation and investment are required to translate these gains into widespread clinical practice.