ARTIFICIAL INTELLIGENCE IN RETINA: Edited by Judy E. Kim and Ehsan RahimySystemic retinal biomarkersRanchod, Tushar M.Author Information Bay Area Retina Associates, Walnut Creek, California, USA Correspondence to Tushar M. Ranchod, MD, Bay Area Retina Associates, 365 Lennon Lane, Suite 250, Walnut Creek, CA 94598, USA. Tel: +1 925 943 6800; e-mail: [email protected] Current Opinion in Ophthalmology: September 2021 - Volume 32 - Issue 5 - p 439-444 doi: 10.1097/ICU.0000000000000784 Buy Metrics Abstract Purpose of review Systemic retinal biomarkers are biomarkers identified in the retina and related to evaluation and management of systemic disease. This review summarizes the background, categories and key findings from this body of research as well as potential applications to clinical care. Recent findings Potential systemic retinal biomarkers for cardiovascular disease, kidney disease and neurodegenerative disease were identified using regression analysis as well as more sophisticated image processing techniques. Deep learning techniques were used in a number of studies predicting diseases including anaemia and chronic kidney disease. A virtual coronary artery calcium score performed well against other competing traditional models of event prediction. Summary Systemic retinal biomarker research has progressed rapidly using regression studies with clearly identified biomarkers such as retinal microvascular patterns, as well as using deep learning models. Future systemic retinal biomarker research may be able to boost performance using larger data sets, the addition of meta-data and higher resolution image inputs. Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.