Deep learning for diagnosing and grading pterygium: A systematic review and meta-analysis.

Journal: Computers in biology and medicine
Published Date: Jul 11, 2025

Abstract

TOPIC: A systematic review and meta-analysis evaluating the accuracy of DL models in pterygium detection and severity assessment against clinical experts.

Authors

  • Ethan W W Tiong
    , School of Medical Sciences, University of Manchester, UK.
  • Carine Y S Soon
    , School of Medical Sciences, University of Manchester, UK.
  • Zun Zheng Ong
    Department of Ophthalmology, Queen's Medical Centre, Nottingham, UK.
  • Su-Hsun Liu
    Department of Ophthalmology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
  • Riaz Qureshi
    University of Colorado Anschutz Medical Campus, Aurora, CO, USA. riaz.qureshi@cuanschutz.edu.
  • Saaeha Rauz
    Birmingham and Midland Eye Centre, Sandwell and West Birmingham NHS Trust, Birmingham, UK; Academic Unit of Ophthalmology, Department of Inflammation and Ageing, School of Immunity, Infection, and Inflammation, College of Medicine and Health, University of Birmingham, UK.
  • Darren S J Ting
    Academic Unit of Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom.

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