Deep Learning for Predicting Refractive Error From Retinal Fundus Images.

Journal: Investigative ophthalmology & visual science
PMID: 30025129

Abstract

PURPOSE: We evaluate how deep learning can be applied to extract novel information such as refractive error from retinal fundus imaging.

Authors

  • Avinash V Varadarajan
    Google Research, Google, Mountain View, CA, USA.
  • Ryan Poplin
    Google Research, Google, Mountain View, CA, USA.
  • Katy Blumer
    Google Research, Google, Mountain View, CA, USA.
  • Christof Angermueller
    Google Research, Google, Inc., Mountain View, California, United States.
  • Joe Ledsam
    Google DeepMind, Google, Inc., London, United Kingdom.
  • Reena Chopra
    NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom.
  • Pearse A Keane
    National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
  • Greg S Corrado
    Google Health, Palo Alto, CA USA.
  • Lily Peng
    Google Inc, Mountain View, California.
  • Dale R Webster
    Google Inc, Mountain View, California.

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