Machine Learning in the Detection of the Glaucomatous Disc and Visual Field.

Journal: Seminars in ophthalmology
Published Date: Jan 1, 2019

Abstract

Glaucoma is the leading cause of irreversible blindness worldwide. Early detection is of utmost importance as there is abundant evidence that early treatment prevents disease progression, preserves vision, and improves patients' long-term quality of life. The structure and function thresholds that alert to the diagnosis of glaucoma can be obtained entirely via digital means, and as such, screening is well suited to benefit from artificial intelligence and specifically machine learning. This paper reviews the concepts and current literature on the use of machine learning for detection of the glaucomatous disc and visual field.

Authors

  • David J Smits
    a Department of Ophthalmology , Massachusetts Eye and Ear Infirmary, Harvard Medical School , Boston , USA.
  • 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.
  • Haobing Wang
    c Harvard Medical School , Massachusetts Eye and Ear Infirmary , Boston , USA.
  • Louis R Pasquale
    Eye and Vision Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

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