Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab

Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab

Abstract Background Artificial intelligence (AI)-driven biomarker segmentation offers an objective and reproducible approach for quantifying key anatomical features in neovascular age-related macular degeneration (nAMD) using optical coherence tomography (OCT). Currently, Faricimab, a novel bispecif...

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Bibliographic Details
Main Authors: Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein
Format: Article
Language:English
Published: BMC 2025-04-01
Series:International Journal of Retina and Vitreous
Subjects:
Neovascular age-related macular degeneration
Deep learning
Optical coherence tomography
Faricimab
Artificial intelligence
Chorioretinal biomarkers
Online Access:https://doi.org/10.1186/s40942-025-00669-2
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https://doi.org/10.1186/s40942-025-00669-2

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