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GeroScience

Deep learning-derived retinal age gap and its associations with lifestyle, systemic, and ocular health in a health screening cohort

Using 29,530 fundus images from a health screening cohort, this study trained a multi-task model to predict retinal age and evaluated the retinal age gap (RAG) in two sub-cohorts, finding that higher RAG was significantly associated with smoking (ex-smokers beta = +0.46 years; current smokers beta = +0.50 years) and clinical diabetes (+2.52 years), and that RAG was significantly higher in eyes with age-related macular degeneration (+0.60 years) and cataract (+1.86 years) than in normal controls.