A Case for the Use of Artificial Intelligence in Glaucoma Assessment

Joel S Schuman; Maria De Los Angeles Ramos Cadena; Rebecca McGee; Lama A Al-Aswad; Felipe A Medeiros; Collaborative Community on Ophthalmic Imaging Executive Committee and Glaucoma Workgroup

doi:10.1016/j.ogla.2021.12.003

A Case for the Use of Artificial Intelligence in Glaucoma Assessment

Ophthalmol Glaucoma. 2022 May-Jun;5(3):e3-e13. doi: 10.1016/j.ogla.2021.12.003. Epub 2021 Dec 22.

Authors

Joel S Schuman¹, Maria De Los Angeles Ramos Cadena², Rebecca McGee², Lama A Al-Aswad³, Felipe A Medeiros⁴; Collaborative Community on Ophthalmic Imaging Executive Committee and Glaucoma Workgroup

Collaborators

Collaborative Community on Ophthalmic Imaging Executive Committee and Glaucoma Workgroup:
Michael Abramoff, Mark Blumenkranz, Emily Chew, Michael Chiang, Malvina Eydelman, David Myung, Carol Shields, Bhavna J Antony, Tin Aung, Michael Boland, Tom Brunner, Robert T Chang, Balwantray Chauhan, D Hunter Cherwek, David Garway-Heath, Adrienne Graves, Jeffrey L Goldberg, Minguang He, Naama Hammel, Donald Hood, Hiroshi Ishikawa, Chris Leung, Louis Pasquale, Harry A Quigley, Calvin W Roberts, Alan L Robin, Elena Sturman, Remo Susanna, Jayme Vianna, Linda Zangwill

Affiliations

¹ Department of Ophthalmology, NYU Langone Health, NYU Grossman School of Medicine, New York, New York; Departments of Biomedical Engineering and Electrical and Computer Engineering, New York University Tandon School of Engineering, Brooklyn, New York; Center for Neural Science, NYU, New York, New York; Neuroscience Institute, NYU Langone Health, New York, New York. Electronic address: joel.schuman@nyu.edu.
² Department of Ophthalmology, NYU Langone Health, NYU Grossman School of Medicine, New York, New York.
³ Department of Ophthalmology, NYU Langone Health, NYU Grossman School of Medicine, New York, New York; Department of Population Health, NYU Langone Health, NYU Grossman School of Medicine, New York, New York.
⁴ Department of Ophthalmology, Duke University School of Medicine, Durham, North Carolina; Department of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina.

Abstract

We hypothesize that artificial intelligence (AI) applied to relevant clinical testing in glaucoma has the potential to enhance the ability to detect glaucoma. This premise was discussed at the recent Collaborative Community on Ophthalmic Imaging meeting, "The Future of Artificial Intelligence-Enabled Ophthalmic Image Interpretation: Accelerating Innovation and Implementation Pathways," held virtually September 3-4, 2020. The Collaborative Community on Ophthalmic Imaging (CCOI) is an independent self-governing consortium of stakeholders with broad international representation from academic institutions, government agencies, and the private sector whose mission is to act as a forum for the purpose of helping speed innovation in healthcare technology. It was 1 of the first 2 such organizations officially designated by the Food and Drug Administration in September 2019 in response to their announcement of the collaborative community program as a strategic priority for 2018-2020. Further information on the CCOI can be found online at their website (https://www.cc-oi.org/about). Artificial intelligence for glaucoma diagnosis would have high utility globally, because access to care is limited in many parts of the world and half of all people with glaucoma are unaware of their illness. The application of AI technology to glaucoma diagnosis has the potential to broadly increase access to care worldwide, in essence flattening the Earth by providing expert-level evaluation to individuals even in the most remote regions of the planet.

Keywords: Artificial intelligence; Deep learning; Glaucoma; Neural networks; OCT.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Artificial Intelligence*
Diagnostic Imaging
Glaucoma* / diagnosis
Humans

Grants and funding

R01 EY013178/EY/NEI NIH HHS/United States