Prediction of corneal back surface power - Deep learning algorithm versus multivariate regression.

Journal: Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
PMID: 34726283

Abstract

BACKGROUND: The corneal back surface is known to add some against the rule astigmatism, with implications in cataract surgery with toric lens implantation. This study aimed to set up and validate a deep learning algorithm to predict corneal back surface power from the corneal front surface power and biometric measures.

Authors

  • Achim Langenbucher
    Institut für Experimentelle Ophthalmologie, Universität des Saarlandes, Homburg/Saar, Deutschland.
  • Nóra Szentmáry
    Dr. Rolf M. Schwiete-Zentrum für Limbusstammzellforschung und kongenitale Aniridie, Universität des Saarlandes, Saarbrücken, Deutschland.
  • Alan Cayless
    School of Physical Sciences, The Open University, Milton Keynes, UK.
  • Johannes Weisensee
    Department of Experimental Ophthalmology, Saarland University, Homburg/Saar, Germany.
  • Jascha Wendelstein
    Abteilung für Augenheilkunde und Optometrie, Johannes-Kepler-Universität Linz, Österreich.
  • Peter Hoffmann
    Augen- und Laserklinik Castrop-Rauxel, Deutschland.

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