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dc.creatorSanz Delgado, José Antonioes_ES
dc.creatorFernández Fernández, Francisco Javieres_ES
dc.creatorBustince Sola, Humbertoes_ES
dc.creatorGradín Purroy, Carloses_ES
dc.creatorBelzunegui Otano, Tomáses_ES
dc.date.accessioned2020-10-15T11:31:40Z
dc.date.available2020-10-15T11:31:40Z
dc.date.issued2017
dc.identifier.issn1875-6883
dc.identifier.urihttps://hdl.handle.net/2454/38426
dc.description.abstractSurvival prediction of poly-trauma patients measure the quality of emergency services by comparing their predictions with the real outcomes. The aim of this paper is to tackle this problem applying C4.5 since it achieves accurate results and it provides interpretable models. Furthermore, we use sampling techniques because, among the 378 patients treated at the Hospital of Navarre, the number of survivals excels that of deaths. Logistic regressions are used in the comparison, since they are an standard in this domain.en
dc.description.sponsorshipThis work was supported in part by the Spanish Ministry of Science and Technology under Projects TIN2016-77356-P and by the Health Department of the Navarre Government under Project PI-019/11.en
dc.format.extent16 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherAtlantis Pressen
dc.relation.ispartofInternational Journal of Computational Intelligence Systems, 2017, 10(1), 440-455en
dc.rights© 2017, the Authors. This is an open access article under the CC BY-NC license.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectTrauma patientsen
dc.subjectSurvival predictionen
dc.subjectDecision treesen
dc.subjectImbalanced classification problemsen
dc.subjectSampling Techniquesen
dc.titleA decision tree based approach with sampling techniques to predict the survival status of poly-trauma patientsen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentAutomática y Computaciónes_ES
dc.contributor.departmentAutomatika eta Konputazioaeu
dc.contributor.departmentCiencias de la Saludes_ES
dc.contributor.departmentOsasun Zientziakeu
dc.contributor.departmentInstitute of Smart Cities - ISCes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.identifier.doi10.2991/ijcis.2017.10.1.30
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/TIN2016-77356-Pen
dc.relation.publisherversionhttps://doi.org/10.2991/ijcis.2017.10.1.30
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.type.versionVersión publicada / Argitaratu den bertsioaes
dc.contributor.funderGobierno de Navarra / Nafarroako Gobernua, PI-019/11es


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© 2017, the Authors. This is an open access article under the CC BY-NC license.
Except where otherwise noted, this item's license is described as © 2017, the Authors. This is an open access article under the CC BY-NC license.

El Repositorio ha recibido la ayuda de la Fundación Española para la Ciencia y la Tecnología para la realización de actividades en el ámbito del fomento de la investigación científica de excelencia, en la Línea 2. Repositorios institucionales (convocatoria 2020-2021).
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