Machine learning-assisted prediction of trabeculectomy outcomes among patients of juvenile glaucoma by using 5-year follow-up data.

Journal: Indian journal of ophthalmology
PMID: 38454857

Abstract

OBJECTIVE: To develop machine learning (ML) models, using pre and intraoperative surgical parameters, for predicting trabeculectomy outcomes in the eyes of patients with juvenile-onset primary open-angle glaucoma (JOAG) undergoing primary surgery.

Authors

  • Shweta Birla
    Translational Bioinformatics Group, International Center for Genetic Engineering and Biotechnology (ICGEB), Delhi, India.
  • Toshit Varshney
    Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
  • Abhishek Singh
    Department of Urology, Muljibhai Patel Urological Hospital, Nadiad, India.
  • Arun Sharma
    Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India.
  • Arnav Panigrahi
    Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
  • Shikha Gupta
    Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow, 226 001, India.
  • Dinesh Gupta
    Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India.
  • Viney Gupta
    Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences (AIIMS), New Delhi, India.

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