Developing machine learning models that achieve higher diagnostic precision for retinal and anterior segment diseases

Prospective, real-world validation of models to ensure safety and efficacy

Building AI-assisted systems that streamline workflows and reduce diagnostic variability

Embedding AI tools within existing ophthalmology pathways for usability and impact

Empovering clinicians with analytics-driven insights for personalized patient care

Responsible AI practices, transparency and bias mitigation for equitable care