Artificial Intelligence-Based Disease Activity Monitoring to Personalized Neovascular Age-Related Macular Degeneration Treatment: A Feasibility Study

Purpose: To evaluate the performance of a disease activity (DA) model developed to detect DA in participants with neovascular age-related macular degeneration (nAMD). Design: Post hoc analysis. Participants: Patient dataset from the phase III HAWK and HARRIER (H&H) studies. Methods: An artificial in...

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Hauptverfasser:	Zufar Mulyukov, PhD, Pearse A. Keane, FRCOphth, MD, Jayashree Sahni, FRCOphth, MD, Sandra Liakopoulos, MD, Katja Hatz, MD, Daniel Shu Wei Ting, MD, PhD, Roberto Gallego-Pinazo, MD, PhD, Tariq Aslam, PhD, DM(Oxon), Chui Ming Gemmy Cheung, FRCOphth, MD, Gabriella De Salvo, FRCOphth, MD, Oudy Semoun, MD, Gábor Márk Somfai, MD, PhD, Andreas Stahl, MD, Brandon J. Lujan, MD, Daniel Lorand, MSc
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2024-11-01
Schriftenreihe:	Ophthalmology Science
Schlagworte:	Artificial intelligence Deep learning Disease activity Neovascular age-related macular degeneration Optical coherence tomography
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2666914524001015
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