Machine Learning Model for Predicting Visual Acuity Improvement After Intrastromal Corneal Ring Surgery in Patients With Keratoconus.

Journal: Cornea
Published Date:

Abstract

BACKGROUND: Keratoconus is a progressive, degenerative corneal disease that can lead to significant visual impairment. The intrastromal ring segment implantation procedure is effective in reshaping the cornea and improving vision. However, vision does not improve postoperatively in all operated eyes, and the results vary widely among patients, making it challenging to predict postoperative visual gain.

Authors

  • Eva Perez
    GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France; and.
  • Nassim Louissi
    GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France; and.
  • Sofiene Kallel
    GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France; and.
  • Quentin Hays
    GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France; and.
  • Nacim Bouheraoua
    Groupe de Recherche Clinique #32, Transplantation et Thérapies Innovantes de la Cornée, Sorbonne Université, Hôpital National des 15-20, Paris, France.
  • Malika Hamrani
    GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France; and.
  • Anatole Chessel
    LOB, Ecole Polytechnique, CNRS, INSERM, Université Paris-Saclay, 91128 Palaiseau cedex, France. Electronic address: anatole.chessel@polytechnique.edu.
  • Vincent Borderie
    GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France; and.

Keywords

No keywords available for this article.