Forme fruste keratoconus detection with OCT corneal topography using artificial intelligence algorithms.

Journal: Journal of cataract and refractive surgery

PMID: 39223730

Abstract

PURPOSE: To differentiate a normal cornea from a forme fruste keratoconus (FFKC) with the swept-source optical coherence tomography (SS-OCT) topography CASIA 2 using machine learning artificial intelligence algorithms.

Authors

Eugénie Mourgues

From the Ophthalmology Unit, University Hospital Bordeaux, Bordeaux, France (Mourgues, Saunier, Touboul, Valentine Saunier); Department of Ophthalmology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel (Smadja).
Virgile Saunier
David Smadja
David Touboul
Valentine Saunier

Keywords

Adult Algorithms Artificial Intelligence Case-Control Studies Cornea Corneal Topography Female Humans Keratoconus Male Middle Aged Retrospective Studies ROC Curve Tomography, Optical Coherence Young Adult

External Resources

View on PubMed Access via DOI PubMed (39223730)

Forme fruste keratoconus detection with OCT corneal topography using artificial intelligence algorithms.

Abstract

Authors

Keywords

External Resources

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