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Updated: Jul 21, 2025

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使用非线性技术的机器学习模型改善了在接受血液透析的个体中休息能量消耗的预测

Alainn Bailey1, Mohamed Eltawil2, Suril Gohel2

  • 1Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Rutgers University, New Brunswick, NJ, USA.

Annals of medicine
|July 28, 2023
PubMed
概括

机器学习 (ML) 显著提高了透析患者估计休息能量消耗 (eREE) 的计算精度,特别是那些高风险的蛋白质能量浪费 (PEW) 患者. 这一进步为这个弱势群体提供了更好的治疗策略.

关键词:
休息的能量支出 休息的能量支出慢性脏疾病 慢性脏疾病透析是通过透析进行的.血液透析是血液透析的方法之一.瘦体质量 瘦体质量 瘦体质量机器学习是机器学习.预测方程是一个预测方程.

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