Keratoconus Disease

Keratoconus, a progressive corneal disorder leading to vision impairment, is a focus of intense research aimed at improving early diagnosis and treatment. Current efforts leverage deep learning, particularly convolutional neural networks (CNNs) like DenseNet, Inception, MobileNet, and VGG architectures, to analyze corneal topography images from both traditional and smartphone-based devices for automated detection. These AI-driven approaches show promise in increasing diagnostic accuracy and accessibility, especially in resource-limited settings, by assisting clinicians or enabling wider screening. Furthermore, research is exploring methods to enhance the interpretability of these models, fostering greater trust and collaboration between AI and clinicians in the diagnostic process.