Explainable machine learning framework for biomarker discovery by combining biological age and frailty prediction.

ABSTRACT: Biological age (BA) and frailty represent two distinct health measures that offer valuable insights into the aging process. Comparing and analyzing blood-based biomarkers from the machine learning (ML) predictors of BA and frailty helps deepen our understanding of aging. This study aimed to develop a novel framework to identify biomarkers of aging by combining BA and frailty ML predictors with eXplainable Artificial Intelligence (XAI) techniques. We utilized data from middle-aged and older Chinese adults (≥ 45 years) in the 2011/2012 wave (n = 9702) and the 2015/2016 wave (n = 9455, as test set validation) of the China Health and Retirement Longitudinal Study (CHARLS). Sixteen blood-based biomarkers were used to predict BA and frailty. Four tree-based ML algorithms were employed in the tra

SUBMITTER: Wang X 

PROVIDER: S-EPMC12015418 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature