Deep Aging Clocks: The emergence of AI-based biomarkers of aging and longevity

Summary: Combining multiple artificial intelligence agents sheds light on the aging process and can help further understanding of what contributes to healthy aging. There are two kinds of age: chronological age, which is the number of years one has lived, and biological age, which is influenced by our genes, lifestyle, behavior, the environment, and other factors. Biological age is the superior measure of true age and is the most biologically relevant feature, as it closely correlates with mortality and health status. The search for reliable predictors of biological age has been ongoing for several decades, and until recently, largely without success. Since 2016 the use of deep learning techniques to find predictors of chronological and biological age has been gaining popularity in the aging research community.