基于可解释的机器学习方法,肌肉质量指数对成年男性丸素缺乏的预测作用
Lisheng Yu1,2, Shunshun Cao3, Botian Song4
1Neurosurgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
BMC public health
|August 27, 2025
概括
肌肉质量指数 (MQI) 是男性缺乏症的可靠预测指标. 较高的MQI与较低的TD风险有关,这表明肌肉质量
科学领域:
- 内分泌学
- 雄性学
- 运动医学
背景情况:
- 在老年男性和代谢综合征患者中,缺乏症 (TD) 很普遍.
- 肌肉质量指数 (MQI) 和TD之间的关联存在有限的研究.
- 这项研究调查了MQI在TD中的作用,并开发了一个预测机器学习模型.
研究的目的:
- 研究美国成年男性的MQI和TD之间的关联.
- 创建一个可解释的机器学习 (ML) 模型,用于使用SHapley添加式扩展 (SHAP) 预测TD风险.
主要方法:
- 通过加权多变量逻辑回归和子组分析进行横截面研究.
- 开发和评估6个ML模型用于TD风险预测.
- 模型性能使用AUC,F1得分和SHAP来评估特征的重要性.
主要成果:
- 发现了一个显著的反向关系:MQI的每一个单位增加都将TD风险降低52%.
- 光梯度增强机 (LGBM) 模型显示出最好的预测性能 (AUC = 0.746).
- 身体质量指数 (BMI),HDL和MQI是关键预测指标;较低的MQI与较高的TD风险相关.
结论:
- 在男性中,MQI是TD的独立和显著预测指标.
- 一个可解释的LGBM模型为早期的TD风险评估提供了一个实用的工具.
- 肌肉质量对的调节至关重要,
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