Predictive analytics is transforming ophthalmic research by enabling clinicians and researchers to identify patterns associated with disease development, progression, treatment response, and long-term outcomes. By combining clinical records, imaging data, demographic information, and other relevant datasets, advanced analytical models can support more proactive approaches to vision care.
This session will explore predictive models across glaucoma, retinal diseases, diabetic eye disease, myopia, and other ophthalmic conditions. Discussions will examine risk prediction, disease progression modelling, treatment-response prediction, and the integration of multimodal patient information into individualized clinical assessment.
The session will also address model validation, data quality, generalizability, interpretability, and responsible implementation. Experts will discuss how predictive analytics can contribute to precision ophthalmology while maintaining clinical oversight and evidence-based decision-making.