Deep Learning Algorithm for Keratoconus Detection from Tomographic Maps and Corneal Biomechanics: A Diagnostic Study

Deep Learning Algorithm for Keratoconus Detection from Tomographic Maps and Corneal Biomechanics: A Diagnostic Study

Purpose To develop an artificial intelligence (AI) approach for differentiating between normal cornea, subclinical, and keratoconus (KC) using tomographic maps from Pentacam (Oculus) and corneal biomechanics from Corvis ST (Oculus). Methods A total of 1,668 tomographic (769 patients) and 611 biomech...

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Bibliographic Details
Main Authors: Wiyada Quanchareonsap, Ngamjit Kasetsuwan, Usanee Reinprayoon, Yonrawee Piyacomn, Thitima Wungcharoen, Monthira Jermjutitham
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2024-10-01
Series:Journal of Current Ophthalmology
Subjects:
artificial intelligence
forme fruste keratoconus
keratoconus
keratoconus suspect
machine learning
subclinical keratoconus
Online Access:https://journals.lww.com/10.4103/joco.joco_18_24
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