Prediction of Resting Energy Expenditure in Children: May Artificial Neural Networks Improve Our Accuracy?

The inaccuracy of resting energy expenditure (REE) prediction formulae to calculate energy metabolism in children may lead to either under- or overestimated real caloric needs with clinical consequences. The aim of this paper was to apply artificial neural networks algorithms (ANNs) to REE predictio...

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Detalles Bibliográficos
Autores principales: De Cosmi, Valentina, Mazzocchi, Alessandra, Milani, Gregorio Paolo, Calderini, Edoardo, Scaglioni, Silvia, Bettocchi, Silvia, D’Oria, Veronica, Langer, Thomas, Spolidoro, Giulia C. I., Leone, Ludovica, Battezzati, Alberto, Bertoli, Simona, Leone, Alessandro, De Amicis, Ramona Silvana, Foppiani, Andrea, Agostoni, Carlo, Grossi, Enzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230279/
https://www.ncbi.nlm.nih.gov/pubmed/32260581
http://dx.doi.org/10.3390/jcm9041026

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230279/
https://www.ncbi.nlm.nih.gov/pubmed/32260581
http://dx.doi.org/10.3390/jcm9041026

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