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Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/25108
DC FieldValueLanguage
dc.contributor.authorCárdenas, J.en_US
dc.contributor.authorOrjuela-Cañón, A.en_US
dc.contributor.authorCerquera, A.en_US
dc.contributor.authorRavelo García, Antonio G.en_US
dc.date.accessioned2018-01-13T03:32:57Z-
dc.date.accessioned2018-02-21T14:36:10Z-
dc.date.available2018-01-13T03:32:57Z-
dc.date.available2018-02-21T14:36:10Z-
dc.date.issued2017en_US
dc.identifier.isbn9781510616332-
dc.identifier.issn0277-786Xen_US
dc.identifier.otherWoS-
dc.identifier.urihttp://hdl.handle.net/10553/25108-
dc.description13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017; San Andres Island; Colombia; 5-7 October 2017; Code 132645-
dc.description.abstractDifferent studies have used Transfer Entropy (TE) and Granger Causality (GC) computation to quantify interconnection between physiological systems. These methods have disadvantages in parametrization and availability in analytic formulas to evaluate the significance of the results. Other inconvenience is related with the assumptions in the distribution of the models generated from the data.en_US
dc.formatapplication/pdf-
dc.languageengen_US
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineeringen_US
dc.rightsby-nc-nd-
dc.sourceProceedings of SPIE - The International Society for Optical Engineering [ISSN 0277-786X] v. 10572, article number 1057219en_US
dc.subject3314 Tecnología médicaen_US
dc.subject120304 Inteligencia artificialen_US
dc.subject.otherArtificial neural networken_US
dc.subject.otherGranger causalityen_US
dc.subject.otherObstructive sleep apnea syndromeen_US
dc.subject.otherBrain-heart networksen_US
dc.subject.otherCPAPen_US
dc.titleCharacterization of physiological networks in sleep apnea patients using artificial neural networks for Granger causality computationen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.typeArticleen_US
dc.relation.conference13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017en_US
dc.identifier.doi10.1117/12.2284957en_US
dc.identifier.scopus85038423580-
dc.identifier.isi000419981400044-
dc.contributor.authorscopusid57199834308-
dc.contributor.authorscopusid55320341500-
dc.contributor.authorscopusid55887852300-
dc.contributor.authorscopusid57199855886-
dc.identifier.crisid-;-;-;--
dc.identifier.eissn1996-756X-
dc.relation.volume10572en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess-
dc.type2Artículoen_US
dc.contributor.daisngid16907198-
dc.contributor.daisngid2962836-
dc.contributor.daisngid3173925-
dc.contributor.daisngid16945488-
dc.description.numberofpages7en_US
dc.utils.revisionSíen_US
dc.contributor.wosstandardWOS:Cardenas, J-
dc.contributor.wosstandardWOS:Orjuela-Canon, AD-
dc.contributor.wosstandardWOS:Cerquera, A-
dc.contributor.wosstandardWOS:Ravelo, A-
dc.date.coverdateEnero 2017en_US
dc.identifier.supplement-;-;-;--
dc.identifier.supplement-;-;-;--
dc.identifier.conferenceidevents121621-
dc.identifier.ulpgcSíen_US
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.event.eventsstartdate05-10-2017-
crisitem.event.eventsenddate07-10-2017-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-8512-965X-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameRavelo García, Antonio Gabriel-
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