Comparison of different corneal imaging modalities using artificial intelligence for diagnosis of keratoconus: a systematic review and meta-analysis.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PMID: 37418053

Abstract

PURPOSE: This review was designed to compare different corneal imaging modalities using artificial intelligence (AI) for the diagnosis of keratoconus (KCN), subclinical KCN (SKCN), and forme fruste KCN (FFKCN).

Authors

  • Hassan Hashemi
    Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Radiology Department, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, No. 1419733141, Iran.
  • Farideh Doroodgar
    Translational Ophthalmology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
  • Sana Niazi
    Research Institute for Ophthalmology and Vision Science, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Mehdi Khabazkhoob
    Department of Medical Surgical Nursing, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Zahra Heidari
    Department of Endocrinology and Metabolism, Zahedan University of Medical Sciences, Zahedan, Iran.

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