Artificial intelligence is increasingly being investigated for the assessment of corneal structure, ocular surface health, and related disorders. Advanced imaging and computational analysis can provide detailed information about corneal morphology and surface characteristics, creating opportunities for more objective and automated assessment.
This session will explore AI applications in corneal imaging, keratoconus detection, corneal ectasia assessment, dry eye evaluation, ocular surface disease classification, and refractive screening. Discussions will focus on automated image analysis and the identification of subtle clinical features that may support earlier diagnosis.
The session will also consider the challenges associated with dataset diversity, imaging quality, algorithm performance, and clinical validation. Researchers and clinicians will discuss how AI-based approaches can complement conventional examination techniques and contribute to more personalized corneal and ocular surface care.