Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.

Journal: American journal of ophthalmology
PMID: 33577789

Abstract

PURPOSE: To compare the achieved vault using the conventional manufacturer's nomogram and the predicted vault using machine learning, in a large cohort of eyes undergoing posterior chamber phakic intraocular lens (EVO implantable collamer lens [ICL]; STAAR Surgical) implantation.

Authors

  • Kazutaka Kamiya
    Visual Phisiology, School of Allied Health Sciences, Kitasato University, Sagamihara, Japan kamiyak-tky@umin.ac.jp.
  • Ik Hee Ryu
    B&VIIt Eye Center, Seoul, South Korea.
  • Tae Keun Yoo
  • Jung Sub Kim
    B&VIIt Eye Center, Seoul, South Korea.
  • In Sik Lee
    B&VIIt Eye Center, Seoul, South Korea.
  • Jin Kook Kim
    Kitasato University, Kanagawa, Japan; B&VIIT Eye Center, Seoul, South Korea.
  • Wakako Ando
    the Department of Ophthalmology, School of Medicine.
  • Nobuyuki Shoji
    Department of Ophthalmology, School of Medicine, Kitasato University, Kanagawa, Japan.
  • Tomofusa Yamauchi
    Department of Ophthalmology, Tsukazaki Hospital, Himeji, Japan.
  • Hitoshi Tabuchi
    Department of Ophthalmology, Tsukazaki Hospital, Himeji, Japan.

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