Optimized Artificial Intelligence for Enhanced Ectasia Detection Using Scheimpflug-Based Corneal Tomography and Biomechanical Data.

Purpose: To optimize artificial intelligence (AI) algorithms to integrate Scheimpflug-based corneal tomography and biomechanics to enhance ectasia detection.

Design: Multicenter cross-sectional case-control retrospective study.

Methods: A total of 3886 unoperated eyes from 3412 patients had Pentacam and Corvis ST (Oculus Optikgeräte GmbH) examinations.

Corneal ectasia detection by epithelial pattern standard deviation from OCT.

Purpose: To test the ability of the corneal epithelial pattern standard deviation (PSD) to distinguish between normal and cases with corneal ectatic condition.

Setting: Instituto de Olhos Renato Ambrósio, Rio de Janeiro, Brazil.

Design: Cross-sectional retrospective study.