Artificial Intelligence–Driven Differentiation Between Uveal Melanoma and Nevus Based on Fundus Photographs: A Systematic Review and Meta-Analysis
Key Points
AI-based analysis effectively distinguishes uveal melanoma from nevi using fundus photographs, providing new diagnostic avenues.
The systematic review includes multiple studies, highlighting AI's potential accuracy in diagnosing ocular tumors.
Computational methods enhance clinical decision-making by offering an automated approach to fundus image interpretation.
These findings suggest AI could revolutionize the diagnosis of uveal melanoma, but implementation in clinical practice requires further validation.
Abstract
This work bridges computational research and ophthalmologic care by demonstrating the potential of AI-based analysis of fundus photographs to assist in differentiating uveal melanocytic tumors.
Artificial Intelligence–Driven Differentiation Between Uveal Melanoma and Nevus Based on Fundus Photographs: A Systematic Review and Meta-Analysis | Synapse