Cardiovascular Diseases Risk Prediction Based On Retinal Fundus Photography Zhihong Lin

Recent studies have validated the association between cardiovascular disease (CVD) risk and retinal fundus photography. Deep learning (DL) models have been employed to predict CVD risk from retinal fundus photography based on different tasks. In this thesis, we addressed the research topic from three subjects: 1) The fundus-based CVD risk score prediction, 2) The fundus-based CVD event prediction, and 3) The automatic ophthalmology report generation.