Oculomics using artificial intelligence derived retinal biomarkers for cardiovascular health. Download PDF Abstract 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. Explore related subjects Discover the latest articles and news in related subjects. Biomarkers Cardiology Computational biology and bioinformatics Diseases Engineering Medical research Acknowledgements The authors thank the scientific and clinical researchers whose work formed the basis of this review.
No additional individuals or organizations contributed to the preparation of this manuscript. Funding The authors received no specific funding for this work. Author information Authors and Affiliations Department of ITOM, College of Business, Florida Atlantic University, Boca Raton, FL, USA Harshal A.
Medical Disclaimer: This article is for informational purposes only and does not constitute medical advice. Always consult with qualified healthcare professionals for medical decisions and treatment options.
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