Comparison of different corneal imaging modalities using artificial intelligence for diagnosis of keratoconus: a systematic review and meta-analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cellular and Molecular Neuroscience,Sensory Systems,Ophthalmology
Link
https://link.springer.com/content/pdf/10.1007/s00417-023-06154-6.pdf
Reference89 articles.
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2. Siganos CS, Tsiklis NS, Miltsakakis DG, Georgiadis NS, Georgiadou IN, Kymionis GD, Pallikaris IG (2010) Changing indications for penetrating keratoplasty in Greece, 1982–2006: a multicenter study. Cornea 29:372–374. https://doi.org/10.1097/ICO.0b013e3181bd44a1
3. Hashemi H, Heydarian S, Yekta A, Ostadimoghaddam H, Aghamirsalim M, Derakhshan A, Khabazkhoob M (2018) High prevalence and familial aggregation of keratoconus in an Iranian rural population: a population-based study. Ophthalmic Physiol Opt 38:447–455. https://doi.org/10.1111/opo.12448
4. Özalp O, Atalay E, Yıldırım N (2021) Prevalence and risk factors for keratoconus in a university-based population in Turkey. J Cataract Refract Surg 47(12):1524–1529. https://doi.org/10.1097/j.jcrs.0000000000000669
5. Reeves SW, Ellwein LB, Kim T, Constantine R, Lee PP (2009) Keratoconus in the Medicare population. Cornea 28:40–42. https://doi.org/10.1097/ICO.0b013e3181839b06
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