Work-related overexertion injuries in cleaning occupations: an exploration of the factors to predict the days of absence by means of machine learning methodologies

dc.contributor.author	González Fuentes, Aroa
dc.contributor.author	Busto Serrano, Nelida María
dc.contributor.author	Sánchez Lasheras, Fernando
dc.contributor.author	Fidalgo Valverde, Gregorio
dc.contributor.author	Suárez Sánchez, Ana
dc.date.accessioned	2023-04-20T07:52:10Z
dc.date.available	2023-04-20T07:52:10Z
dc.date.issued	2022
dc.identifier.citation	Applied Ergonomics, 105 (2022); doi:10.1016/j.apergo.2022.103847
dc.identifier.issn	0003-6870
dc.identifier.uri	http://hdl.handle.net/10651/67341
dc.language.iso	eng	spa
dc.relation.ispartof	Applied Ergonomics	spa
dc.rights	Attribution 4.0 Internacional	*
dc.rights	© 2022 The authors
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.title	Work-related overexertion injuries in cleaning occupations: an exploration of the factors to predict the days of absence by means of machine learning methodologies	spa
dc.type	journal article	spa
dc.identifier.doi	10.1016/j.apergo.2022.103847
dc.local.notes	OA ATUO22
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.apergo.2022.103847	spa
dc.rights.accessRights	open access	spa
dc.type.hasVersion	VoR

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