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Abstract #98965 Published in IGR 22-4
Artificial Intelligence for Glaucoma: Creating and Implementing AI for Disease Detection and Progression
Al-Aswad LA; Ramachandran R; Schuman JS; Medeiros F; Eydelman MB; Eydelman MB;Ophthalmology. Glaucoma 2022; 5: e16-e25
On September 3, 2020, the Collaborative Community on Ophthalmic Imaging (CCOI) conducted its first two-day virtual workshop on the role of artificial intelligence (AI) and related machine learning (ML) techniques for the diagnosis and treatment of various ophthalmic conditions. In a session entitled, "Artificial Intelligence For Glaucoma", a panel of glaucoma specialists, researchers, industry experts, and patients convened to share current research on the application of AI to commonly used diagnostic modalities including fundus photography, optical coherence tomography imaging, standard automated perimetry, and gonioscopy. The conference participants focused on the use of AI as a tool for disease prediction, highlighted its ability to address inequalities, and presented the limitations and challenges to its real-world clinical application. The panelists' discussion addressed AI and health equities from the clinical, societal and regulatory perspectives.
Department of Ophthalmology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA; Department of Population Health, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA. Electronic address: Lama.al-aswad@nyulangone.org.
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