Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/54470
Full metadata record
DC FieldValueLanguage
dc.contributor.authorChushig-Muzo, David-
dc.contributor.authorSoguero-Ruiz, Cristina-
dc.contributor.authorde Miguel Bohoyo, Pablo-
dc.contributor.authorMORA JIMENEZ, INMACULADA-
dc.date.accessioned2021-11-18T13:01:36Z-
dc.date.available2021-11-18T13:01:36Z-
dc.date.issued2021-11-16-
dc.identifier.citationChushig-Muzo D, Soguero-Ruiz C, Miguel Bohoyo P, Mora-Jiménez I. Interpreting clinical latent representations using autoencoders and probabilistic models. Artificial Intelligence in Medicine. 2021;122:102211.es_ES
dc.identifier.issn0933-3657-
dc.identifier.urihttps://hdl.handle.net/20.500.12530/54470-
dc.language.isoenes_ES
dc.publisherElsevier BVes_ES
dc.relation.isversionofPreprintes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.meshModels, Statistical-
dc.subject.meshLatent Class Analysis-
dc.titleInterpreting clinical latent representations using autoencoders and probabilistic modelses_ES
dc.typeArtículoes_ES
dc.format.volume122es_ES
dc.format.page102211es_ES
dc.description.peerreviewedes_ES
dc.identifier.journalArtificial Intelligence in Medicinees_ES
dc.contributor.authoraffiliationDirección Económica-Financiera. Hospital Universitario de Fuenlabradaes_ES
dc.subject.decsAnálisis de Clases Latentes-
dc.subject.decsModelos Estadísticos-
Appears in Collections:Hospitales > H. U. de Fuenlabrada > Artículos

Files in This Item:
File Description SizeFormat 
Artifical Intelligence Medicine.pdf2,11 MBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons