Outcome prediction for salivary gland cancer using Multivariate Adaptative Regression Splines (MARS) and Self-Organizing Maps (SOM)

dc.contributor.author	Lequerica Fernández, Paloma
dc.contributor.author	Peña González, Ignacio
dc.contributor.author	Sánchez Lasheras, Fernando
dc.contributor.author	Iglesias Rodríguez, Francisco Javier
dc.contributor.author	González Gutiérrez, Carlos
dc.contributor.author	de Vicente, Juan C.
dc.date.accessioned	2018-02-06T10:11:01Z
dc.date.available	2018-02-06T10:11:01Z
dc.date.issued	2018
dc.identifier.isbn	978-3-319-67179-6
dc.identifier.issn	2194-5357
dc.identifier.uri	http://hdl.handle.net/10651/45353
dc.description.sponsorship	This work was supported by a grant for scientific research from the Ministry of Health, Spain (Instituto de Salud Carlos III, PI070675)
dc.format.extent	p. 361-370
dc.language.iso	eng
dc.relation.ispartof	Advances in Intelligent Systems and Computing, 649
dc.rights	©,
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028658908&doi=10.1007%2f978-3-319-67180-2_35&partnerID=40&md5=8748a9b6c1becdfefa9d8d34c2f8e4b3
dc.title	Outcome prediction for salivary gland cancer using Multivariate Adaptative Regression Splines (MARS) and Self-Organizing Maps (SOM)
dc.type	conference output	spa
dc.identifier.doi	10.1007/978-3-319-67180-2_35
dc.relation.projectID	Instituto de Salud Carlos III/PI070675
dc.relation.publisherversion	http://dx.doi.org/10.1007/978-3-319-67180-2_35

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