Deep Learning-Based Automatic Diagnosis of Keratoconus with Corneal Endothelium Image
Author:
Publisher
Springer Science and Business Media LLC
Subject
Ophthalmology
Link
https://link.springer.com/content/pdf/10.1007/s40123-023-00795-w.pdf
Reference36 articles.
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3. Ferdi AC, Nguyen V, Gore DM, Allan BD, Rozema JJ, Watson SL. Keratoconus natural progression: a systematic review and meta-analysis of 11 529 eyes. Ophthalmology. 2019;126(7):935–45.
4. Silverman RH, Urs R, Roychoudhury A, Archer TJ, Gobbe M, Reinstein DZ. Epithelial remodeling as basis for machine-based identification of keratoconus. Invest Ophthalmol Vis Sci. 2014;55(3):1580–7.
5. Mas Tur V, MacGregor C, Jayaswal R, O’Brart D, Maycock N. A review of keratoconus: diagnosis, pathophysiology, and genetics. Surv Ophthalmol. 2017;62(6):770–83.
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1. Utility of artificial intelligence in the diagnosis and management of keratoconus: a systematic review;Frontiers in Ophthalmology;2024-05-17
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