DEEP LEARNING-BASED PREDICTION OF OUTCOMES FOLLOWING NONCOMPLICATED EPIRETINAL MEMBRANE SURGERY.

Journal: Retina (Philadelphia, Pa.)
Published Date: Aug 1, 2022

Abstract

PURPOSE: We used deep learning to predict the final central foveal thickness (CFT), changes in CFT, final best corrected visual acuity, and best corrected visual acuity changes following noncomplicated idiopathic epiretinal membrane surgery.

Authors

  • Soo Han Kim
    Department of Ophthalmology, Wonju Severance Christian Hospital, Wonju, Republic of Korea.
  • Honggi Ahn
    Department of Biomedical Engineering, Yonsei University, Wonju, Republic of Korea; and.
  • Sejung Yang
    Medical Physics Division, Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, United States of America.
  • Sung Soo Kim
    Department of Ophthalmology, Institute of Vision Research, Severance Hospital, Seoul, Republic of Korea.
  • Jong Hyuck Lee
    Department of Ophthalmology, Wonju Severance Christian Hospital, Wonju, Republic of Korea.

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