Prediction of postoperative visual acuity after vitrectomy for macular hole using deep learning-based artificial intelligence.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Published Date: Apr 1, 2022

Abstract

PURPOSE: To create a model for prediction of postoperative visual acuity (VA) after vitrectomy for macular hole (MH) treatment using preoperative optical coherence tomography (OCT) images, using deep learning (DL)-based artificial intelligence.

Authors

  • Shumpei Obata
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan. obata326@belle.shiga-med.ac.jp.
  • Yusuke Ichiyama
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan.
  • Masashi Kakinoki
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan.
  • Osamu Sawada
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan.
  • Yoshitsugu Saishin
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan.
  • Taku Ito
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan.
  • Mari Tomioka
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan.
  • Masahito Ohji
    Department of Ophthalmology, Shiga University of Medical Science, 520 - 2192, Seta Tsukinowacho, Otsu, Shiga, Japan.

Keywords

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