The integration of artificial intelligence with genomic and clinical information is creating new possibilities for understanding individual variations in ocular disease risk and treatment response. Computational methods can help researchers analyze complex biological datasets and identify relationships between genetic characteristics, environmental factors, and ophthalmic outcomes.
This session will explore the application of AI and genomic technologies across inherited retinal diseases, glaucoma, AMD, corneal disorders, and other conditions with genetic components. Discussions will focus on genomic data interpretation, disease-risk prediction, molecular biomarkers, and personalized approaches to diagnosis and treatment.
The session will also consider ethical, regulatory, and data-governance challenges associated with genomic information. Experts will discuss how AI-enabled precision medicine may contribute to more individualized ophthalmic care while emphasizing responsible data use, clinical validation, and patient-centered implementation.