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dc.contributor.authorCuriel Herrera, Leticia Elena 
dc.contributor.authorBaruque Zanón, Bruno 
dc.contributor.authorDueñas, Carlos
dc.contributor.authorCorchado, Emilio 
dc.contributor.authorPérez-Tárrago, Cristina
dc.date.accessioned2024-02-05T08:13:13Z
dc.date.available2024-02-05T08:13:13Z
dc.date.issued2011
dc.identifier.isbn978-3-642-23878-9
dc.identifier.urihttp://hdl.handle.net/10259/8572
dc.descriptionTrabajo presentado en: 12th International Conference, Norwich, UK, September 7-9, 2011. Proceedingsen
dc.description.abstractThis ongoing interdisciplinary research is based on the application of genetic algorithms to simplify the process of predicting the mortality of a critical illness called endocarditis. The goal is to determine the most relevant features (symptoms) of patients (samples) observed by doctors to predict the possible mortality once the patient is in treatment of bacterial endocarditis. This can help doctors to prognose the illness in early stages; by helping them to identify in advance possible solutions in order to aid the patient recover faster. The results obtained using a real data set, show that using only the features selected by employing a genetic algorithm from each patient’s case can predict with a quite high accuracy the most probable evolution of the patient.en
dc.description.sponsorshipWe would like to extend our thanks to Complejo Hospitalario Asistencial Universitario de Burgos (SACYL). This research has been partially supported through projects TIN2010-21272-C02-01 from the Spanish Ministry of Science and Innovation and Grupo Antolin Ingenieria, S.A., within the framework of project MAGNO2008 - 1028.- CENIT.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherSpringeres
dc.relation.ispartofIntelligent Data Engineering and Automated Learning -- IDEAL 2011, p. 454–462en
dc.subjectGenetic algorithmsen
dc.subjectSupport vector machineen
dc.subjectInfective endocarditisen
dc.subjectFeature selection algorithmen
dc.subjectImperialist competitive algorithmen
dc.subject.otherInformáticaes
dc.subject.otherComputer scienceen
dc.subject.otherMedicinaes
dc.subject.otherMedicineen
dc.titleGenetic Algorithms to Simplify Prognosis of Endocarditisen
dc.typeinfo:eu-repo/semantics/bookPartes
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-642-23878-9_54es
dc.identifier.doi10.1007/978-3-642-23878-9_54
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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