Predicting eyes at risk for rapid glaucoma progression based on an initial visual field test using machine learning.

Abstract

Authors

• Scott R Shuldiner
  Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
• Michael V Boland
  Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland.
• Pradeep Y Ramulu
  Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
• C Gustavo De Moraes
  Department of Ophthalmology, Columbia University Medical Center, New York, NY, United States of America.
• Tobias Elze
  Schepens Eye Research Institute, Harvard Medical School, Boston, Massachusetts; Complex Structures in Biology and Cognition, Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany. Electronic address: tobias-elze@tobias-elze.de.
• Jonathan Myers
  Wills Eye Hospital, Thomas Jefferson University, Philadelphia, PA, United States of America.
• Louis Pasquale
  The Eye and Vision Research Institute of New York Eye and Ear Infirmary at Mount Sinai, Icahn School of Medicine at Mount Sinai School, New York, NY, United States of America.
• Sarah Wellik
  Bascom Palmer Eye Institute, University of Miami, Miami, FL, United States of America.
• Jithin Yohannan
  Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Keywords

External Resources