Chief Supervisor

Prof. HE Mingguang

Project Title

Synopsis

The integration of artificial intelligence (AI) in ophthalmology research has opened up new avenues for enhancing patient care and disease prediction. This project aims to explore the application of AI, particularly deep learning algorithms (DLA), in predicting cardiovascular diseases (CVD) risk through ocular examinations.

CVD is a significant global health concern, and its early identification plays a crucial role in preventive healthcare. Recent studies have shown a potential link between ocular characteristics and CVD risk, suggesting that the eyes can provide valuable insights into an individual's overall health. This project will involve the development of DLA that analyze various ocular parameters from diagnostic images, such as retinal scans, to predict the likelihood of an individual developing CVD.

By leveraging advanced AI techniques, this research seeks to establish a reliable method for early CVD risk assessment based on ocular features. The outcomes of this study could lead to a non-invasive, costeffective, and accessible approach for identifying individuals at higher risk of CVD, enabling timely interventions and personalized healthcare strategies.