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

David J. Smits, Tobias Elze, Haobing Wang, Louis R. Pasquale

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

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.

Original languageEnglish
Pages (from-to)232-242
Number of pages11
JournalSeminars in Ophthalmology
Volume34
Issue number4
DOIs
StatePublished - 19 May 2019

Keywords

  • Glaucoma
  • artificial intelligence
  • machine learning
  • optic nerve photos
  • teleophthalmology
  • visual fields

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