ABSTRACT Objective: To identify corneal epithelial thickness profiles for early keratoconus diagnosis with the aid of Artificial Intelligence. Methods: A total of 496 eyes (306 normal and 190 with keratoconus) were analyzed using optical coherence tomography images. Results: Epithelial segmentation revealed distinct patterns between groups, highlighting early changes in epithelial thickness in keratoconus eyes. The findings reinforce the potential of artificial intelligence in disease screening, enabling a more precise and objective diagnostic approach. Conclusion: Implementing algorithms such as k-means can […]