Deep Learning Applications in Ophthalmology

Dear Colleagues, 

Deep learning approaches to big data and image analysis open new possibilities in ophthalmology and could have a substantial impact on clinical ophthalmology. However, further research on prospective validation and deep learning applications in real-world clinical settings are still warranted. Other hurdles, such as a lack of labelled data, patient privacy, and low generalizability, also need to be overcome in order to make deep learning implementation available in clinical practice. This Special Issue aims to gather a collection of cutting-edge research on deep learning methods in ophthalmology that have specific implications for ocular diseases screening, diagnosis, and management. We welcome submissions on, but not limited to, the following topics:

• Diagnostic deep learning applications in ophthalmology;
• Prognostic deep learning application in ophthalmology;
• Deep learning-based treatment outcome assessment and prediction in ophthalmology;
• Deep learning implementation in clinical practice.

Dr. Carol Y. L. Cheung
Prof. Dr. Haotian Lin
Dr. Anran Ran
Dr. Duoru Lin
Guest Editors

Manuscript Submission Information

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