TY - JOUR
T1 - Artificial Intelligence for Glaucoma
T2 - Creating and Implementing Artificial Intelligence for Disease Detection and Progression
AU - Collaborative Community for Ophthalmic Imaging Executive Committee and Glaucoma Workgroup
AU - Al-Aswad, Lama A.
AU - Ramachandran, Rithambara
AU - Schuman, Joel S.
AU - Medeiros, Felipe
AU - Eydelman, Malvina B.
AU - Abramoff, Michael D.
AU - Antony, Bhavna J.
AU - Boland, Michael V.
AU - Chauhan, Balwantray C.
AU - Chiang, Michael
AU - Goldberg, Jeffrey L.
AU - Hammel, Naama
AU - Pasquale, Louis R.
AU - Quigley, Harry A.
AU - Susanna, Remo
AU - Vianna, Jayme
AU - Zangwill, Linda
N1 - Publisher Copyright:
© 2022
PY - 2022/9/1
Y1 - 2022/9/1
N2 - On September 3, 2020, the Collaborative Community on Ophthalmic Imaging conducted its first 2-day virtual workshop on the role of artificial intelligence (AI) and related machine learning techniques in 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, OCT 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 of and challenges to its clinical application. The panelists’ discussion addressed AI and health equities from clinical, societal, and regulatory perspectives.
AB - On September 3, 2020, the Collaborative Community on Ophthalmic Imaging conducted its first 2-day virtual workshop on the role of artificial intelligence (AI) and related machine learning techniques in 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, OCT 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 of and challenges to its clinical application. The panelists’ discussion addressed AI and health equities from clinical, societal, and regulatory perspectives.
KW - Artificial intelligence
KW - Deep learning
KW - Glaucoma
KW - Imaging
UR - http://www.scopus.com/inward/record.url?scp=85129549669&partnerID=8YFLogxK
U2 - 10.1016/j.ogla.2022.02.010
DO - 10.1016/j.ogla.2022.02.010
M3 - Article
C2 - 35218987
AN - SCOPUS:85129549669
SN - 2589-4234
VL - 5
SP - e16-e25
JO - Ophthalmology Glaucoma
JF - Ophthalmology Glaucoma
IS - 5
ER -