Jun Bu and Kun Qian Teams Publish AI-Driven Metabolic Aging and Mortality Clocks Study in Science Translational Medicine

Teams led by Jun Bu and Kun Qian published a study in Science Translational Medicine using ensemble learning to develop whole-life-span metabolic aging and mortality clocks based on 18,476 individuals; the paper was selected as the cover article. The study maps the whole-life-span metabolome of a Chinese population and uses it to identify systemic aging risk across the human life span.