Artificial Neural Network Algorithms to Predict Resting Energy Expenditure in Critically Ill Children

Artificial Neural Network Algorithms to Predict Resting Energy Expenditure in Critically Ill Children

Introduction: Accurate assessment of resting energy expenditure (REE) can guide optimal nutritional prescription in critically ill children. Indirect calorimetry (IC) is the gold standard for REE measurement, but its use is limited. Alternatively, REE estimates by predictive equations/formulae are o...

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Autores principales: Giulia C. I. Spolidoro, Veronica D’Oria, Valentina De Cosmi, Gregorio Paolo Milani, Alessandra Mazzocchi, Alireza Akhondi-Asl, Nilesh M. Mehta, Carlo Agostoni, Edoardo Calderini, Enzo Grossi
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
energy expenditure
metabolism
nutrition
children
pediatrics
critical care
Nutrition. Foods and food supply
TX341-641
Acceso en línea:https://doaj.org/article/dea44dbd8ee1489487fc373d4b760e2e
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https://doaj.org/article/dea44dbd8ee1489487fc373d4b760e2e

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