Population-specific deep biomarkers of aging

(InSilico Medicine, Inc.) Insilico Medicine and its' collaborators just present a novel deep-learning based hematological human aging clock using a large dataset of fully anonymized Canadian, South Korean and Eastern European blood test records to train an aging clock. The developed model predicts the age better than models tailored to the specific populations highlighting the differences of subregion-specific patterns of aging. In addition, the developed clocks were shown to be a better predictor of all-cause mortality than chronological age.
Source: EurekAlert! - Biology - Category: Biology Source Type: news