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AI in Glaucoma: Challenges and Future Directions by jaweb is a document available to read on EtoBox.

This review discusses the application of artificial intelligence (AI) in glaucoma detection, highlighting the effectiveness of machine learning (ML) and deep learning (DL) techniques in analyzing retinal data for diagnosis and progression assessment. It addresses the challenges of implementing AI models, such as the need for large, well-annotated datasets and the variability in clinical evaluations. The paper aims to provide insights into current AI models, their performance, and future directions for resea

Author

jaweb

Language

EN