Chief Supervisor

Prof. HE Mingguang

Project Title

Synopsis

Visual impairment is a major global public-health challenge, yet evidence concerning disease burden, eye-care capacity and access to services remains fragmented across countries and healthcare systems. This project will develop Global Ophthalmic Intelligence, an AI-enabled framework that integrates epidemiological, clinical, demographic, socioeconomic, health-system and geospatial data to generate comparable and actionable intelligence on global eye health.

The research will establish a standardised data pipeline for multimodal ophthalmic information; apply statistical and machine-learning methods to estimate disease burden, identify underserved populations and forecast future eye-care demand; and develop interactive visualisation and decision-support tools for resource allocation, screening strategies and policy evaluation. Selected regional and country-level case studies will be used to validate the framework and assess its reliability, fairness, transparency and applicability across diverse populations.

Expected outcomes include reproducible data infrastructure, validated analytical models and policy-relevant tools for researchers, clinicians and decision-makers. By transforming fragmented evidence into timely and interpretable intelligence, the project aims to support earlier intervention, reduce avoidable vision loss and improve equity in eye-care delivery worldwide.