Supervised classification by filter methods and recursive feature elimination predicts risk of radiotherapy-related fatigue in patients with prostate cancer

dc.contributor.author	Saligan, Leorey N.
dc.contributor.author	Fernández Martínez, Juan Luis
dc.contributor.author	Andrés Galiana, Enrique Juan de
dc.contributor.author	Sonis, Stephen T.
dc.date.accessioned	2015-02-04T10:33:07Z
dc.date.available	2015-02-04T10:33:07Z
dc.date.issued	2014
dc.identifier.citation	Cancer Informatics, 13 (1), p. 141-152 (2014); doi: 10.4137/CIN.S19745
dc.identifier.issn	1176-9351
dc.identifier.uri	http://hdl.handle.net/10651/29528
dc.format.extent	p. 141-152	spa
dc.language.iso	eng	spa
dc.publisher	Libertas Academica
dc.relation.ispartof	Cancer Informatics, 13 (1)	spa
dc.rights	© L. Saligan et al., publisher and licensee Libertas Academica Limited.
dc.rights	CC Reconocimiento - No comercial - Sin obras derivadas 3.0 España
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Cancer-related fatigue	spa
dc.subject	Fisher’s linear discriminant analysis (LDA)	spa
dc.subject	Prostate cancer	spa
dc.subject	Radiation therapy	spa
dc.title	Supervised classification by filter methods and recursive feature elimination predicts risk of radiotherapy-related fatigue in patients with prostate cancer	spa
dc.type	journal article
dc.identifier.doi	10.4137/CIN.S19745
dc.relation.publisherversion	http://dx.doi.org/10.4137/CIN.S19745
dc.rights.accessRights	open access

Este ítem está sujeto a una licencia Creative Commons