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A recent study has shown that deep learning models can accurately estimate a person's biological age from a retinal image and offer new insights into the prediction of age-related diseases.
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De-identified retinal images from numerous primary care clinics were used to train a model to forecast chronological age for participants in a telemedicine-based programme to avoid blindness.
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Image source: Canva
This study demonstrates the potential of a retinal aging clock as a tool for studying aging and age-related diseases and quantitatively assessing aging on extremely short time scales.
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