Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data.

Journal: Translational vision science & technology
Published Date:

Abstract

PURPOSE: Multiple clinical visits are necessary to determine progression of keratoconus before offering corneal cross-linking. The purpose of this study was to develop a neural network that can potentially predict progression during the initial visit using tomography images and other clinical risk factors.

Authors

  • Lennart M Hartmann
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Denna S Langhans
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Veronika Eggarter
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Tim J Freisenich
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Anna Hillenmayer
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Susanna F König
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Efstathios Vounotrypidis
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Armin Wolf
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.
  • Christian M Wertheimer
    Department of Ophthalmology, University Hospital Ulm, Ulm, Germany.