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该论文提出一个临床可解释的机器学习框架，使用CatBoost和自动化的SHAP依赖图定量分析，从NHANES的44个异构临床特征中估计生物年龄。研究发现模型估计的生物年龄与实际年龄高度相关，并识别出血尿素氮、血糖和剧烈运动等关键预测因子。
A six-month contest called Younger, founded by neuroscientist Christin Glorioso of NeuroAge Therapeutics, pits around 500 participants against each other to reverse their biological age as measured by a variety of aging clocks, aiming to build the world's most comprehensive biological age dataset.
Scientists found that machine-perfused donated livers become biologically younger, potentially enhancing organ transplantation success and utilization.