dc.creatorSilva, Jesús
dc.creatorHerazo-Beltrán, Yaneth
dc.creatorMarín-González, Freddy
dc.creatorVarela Izquierdo, Noel
dc.creatorPineda, Omar
dc.creatorPalencia-Domínguez, Pablo
dc.creatorVargas Mercado, Carlos
dc.date2021-01-21T13:39:17Z
dc.date2021-01-21T13:39:17Z
dc.date2020
dc.date.accessioned2023-10-03T20:09:21Z
dc.date.available2023-10-03T20:09:21Z
dc.identifierhttps://hdl.handle.net/11323/7741
dc.identifierhttps://doi.org/10.1007/978-981-15-4875-8_16
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9174597
dc.descriptionThe construction of patient classification (or risk adjustment) systems allows comparison of the effectiveness and quality of hospitals and hospital services, providing useful information for management decision making and management of hospitals. Risk adjustment systems to stratify patients’ severity in a clinical outcome are generally constructed from care variables and using statistical techniques based on logistic regression (RL). The objective of this investigation is to compare the hospital mortality prediction capacity of an artificial neural network (RNA) with other methods already known.
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languageeng
dc.publisherCorporación Universidad de la Costa
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dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourceSmart Innovation, Systems and Technologies
dc.sourcehttps://link.springer.com/chapter/10.1007/978-981-15-4875-8_16
dc.subjectHospital mortality
dc.subjectRisk stratification
dc.subjectIntensive care unit
dc.subjectArtificial neural networks
dc.subjectBootstrap
dc.titleComparison of bio-inspired algorithms applied to the hospital mortality risk stratification
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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