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Annals of Medicine Volume 54, 2022 - Issue 1
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Nutrition

Current methods for developing predictive energy equations in maintenance dialysis are imprecise

Alainn Baileya Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Rutgers University, Newark, NJ, USAView further author information
,
Rebecca Brodya Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Rutgers University, Newark, NJ, USAView further author information
,
Joachim Sackeya Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Rutgers University, Newark, NJ, USAView further author information
,
J. Scott Parrottb Department of Interdisciplinary Studies, School of Health Professions, Rutgers University, Newark, NJ, USAView further author information
,
Emily Petersa Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Rutgers University, Newark, NJ, USAView further author information
&
Laura Byham-Graya Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Rutgers University, Newark, NJ, USACorrespondence[email protected]
View further author information
Pages 909-920 | Received 14 Oct 2021, Accepted 18 Mar 2022, Published online: 31 Mar 2022

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Read on this site (1)

Alainn Bailey, Mohamed Eltawil, Suril Gohel & Laura Byham-Gray. (2023) Machine learning models using non-linear techniques improve the prediction of resting energy expenditure in individuals receiving hemodialysis. Annals of Medicine 55:2.
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Articles from other publishers (1)

Si Chen, Xiaoyan Ma, Xun Zhou, Yi Wang, WeiWei Liang, Liang Zheng, Xiujuan Zang, Xiaobin Mei, Yinghui Qi, Yan Jiang, Shanbao Zhang, Jinqing Li, Hui Chen, Yingfeng Shi, Yan Hu, Min Tao, Shougang Zhuang & Na Liu. (2022) An updated clinical prediction model of protein-energy wasting for hemodialysis patients. Frontiers in Nutrition 9.
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