Anterior segment biometric measurements explain misclassifications by a deep learning classifier for detecting gonioscopic angle closure.

Journal: The British journal of ophthalmology
PMID:

Abstract

BACKGROUND/AIMS: To identify biometric parameters that explain misclassifications by a deep learning classifier for detecting gonioscopic angle closure in anterior segment optical coherence tomography (AS-OCT) images.

Authors

  • Alice Shen
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern, California.
  • Michael Chiang
    Sol Price School of Public Policy, University of Southern California, Los Angeles, California, USA.
  • Anmol A Pardeshi
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, Los Angeles, California, USA.
  • Roberta McKean-Cowdin
    Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, California, USA.
  • Rohit Varma
    University of Southern California Gayle and Edward Roski Eye Institute, Los Angeles, California.
  • Benjamin Y Xu
    Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine at the University of Southern California, Los Angeles, California, USA. Electronic address: benjamin.xu@med.usc.edu.