Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.

Journal: Ophthalmology. Glaucoma
Published Date:

Abstract

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.

Authors

  • Lama A Al-Aswad
    Columbia University Medical Center, Harkness Eye Institute, New York, New York, USA. Electronic address: laa2003@cumc.columbia.edu.
  • Rithambara Ramachandran
    Department of Ophthalmology, NYU Langone Health, NYU Grossman School of Medicine, New York, New York.
  • Joel S Schuman
    Department of Ophthalmology, NYU Langone Health, NYU Eye Center, New York, New York.
  • Felipe Medeiros
    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.
  • Malvina B Eydelman
    Center for Devices and Radiological Health, Office of Health Technology 1, United States Food and Drug Administration, Silver Springs, Maryland.