Artificial intelligence as an analytic approximation to evaluate associations between parental feeding behaviors and excess weight in Colombian preschoolers

dc.contributor.author	Gamboa Delgado, E. M.
dc.contributor.author	Amaya Castellanos, C. I.
dc.contributor.author	Bahamonde Rionda, Antonio
dc.date.accessioned	2021-06-01T09:40:39Z
dc.date.available	2021-06-01T09:40:39Z
dc.date.issued	2020
dc.identifier.citation	British Journal of Nutrition, 126(1) (2020); doi:10.1017/S0007114520003797
dc.identifier.issn	0007-1145
dc.identifier.uri	http://hdl.handle.net/10651/58592
dc.language.iso	eng
dc.relation.ispartof	British Journal of Nutrition
dc.rights	© Los autores 2020. Publicado por Cambridge University Press en nombre de The Nutrition Society
dc.rights	CC Reconocimiento - No Comercial - Sin Obra Derivada 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092407574&doi=10.1017%2fS0007114520003797&partnerID=40&md5=663c006d9d0c1ecfda67a684fbd2ef72
dc.title	Artificial intelligence as an analytic approximation to evaluate associations between parental feeding behaviors and excess weight in Colombian preschoolers
dc.type	journal article
dc.identifier.doi	10.1017/S0007114520003797
dc.relation.publisherversion	http://dx.doi.org/10.1017/S0007114520003797
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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