Oculomics using artificial intelligence derived retinal biomarkers for cardiovascular health

This narrative review synthesizes evidence from retinal vascular morphology, structural and perfusion imaging, retinal aging, metabolomics, and artificial intelligence models linking retinal biomarkers with cardiovascular risk factors, subclinical disease, clinical events, and cardiorenal and metabolic outcomes. These biomarkers may complement conventional risk assessment, but clinical utility is unproven and integration into cardiovascular digital twins remains conceptual. Prospective validation, standardized acquisition, interoperability, interpretability, and equitable evaluation are required before implementation.