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Please use this identifier to cite or link to this item: http://ri.uaemex.mx/handle20.500.11799/79830
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dc.contributor.authorELAYNE RUBIO DELGADOen_EU
dc.contributor.authorLisbeth Rodríguez Mazahuaen_EU
dc.contributor.authorJOSE ANTONIO PALET GUZMANen_EU
dc.contributor.authorJair Cervantes Canalesen_EU
dc.contributor.authorJOSE LUIS SANCHEZ CERVANTESen_EU
dc.contributor.authorSILVESTRE GUSTAVO SERGIO PELAEZ CAMARENAen_EU
dc.contributor.authorASDRUBAL LOPEZ CHAUen_EU
dc.creatorELAYNE RUBIO DELGADO-
dc.creatorLisbeth Rodríguez Mazahua-
dc.creatorJOSE ANTONIO PALET GUZMAN-
dc.creatorJair Cervantes Canales-
dc.creatorJOSE LUIS SANCHEZ CERVANTES-
dc.creatorSILVESTRE GUSTAVO SERGIO PELAEZ CAMARENA-
dc.creatorASDRUBAL LOPEZ CHAU-
dc.date2018-01-12-
dc.date.accessioned2019-03-12T23:44:10Z-
dc.date.available2019-03-12T23:44:10Z-
dc.identifierhttp://hdl.handle.net/20.500.11799/79830-
dc.identifier.urihttp://ri.uaemex.mx/handle20.500.11799/79830-
dc.descriptionThis research identifies the factors influencing the reduction of autopsies in a hospital of Veracruz. The study is based on the application of data mining techniques such as association rules and Bayesian networks in data sets obtained from opinions of physicians. We analyzed, for the exploration and extraction of the knowledge, algorithms like Apriori, FPGrowth, PredictiveApriori, Tertius, J48, NaiveBayes, MultilayerPerceptron, and BayesNet, all of them provided by the API of WEKA. To generate mining models and present the new knowledge in natural language, we also developed a web application. The results presented in this study are those obtained from the best-evaluated algorithms, which have been validated by specialists in the field of pathology-
dc.languageeng-
dc.publisherHindawi-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0-
dc.source1058-9244-
dc.subjectbayesian-
dc.subjectmedical options-
dc.subjectautopsies-
dc.subjectinfo:eu-repo/classification/cti/3-
dc.titleAnalysis of medical opinions about the nonrealization of autopsies in a Mexican hospital using association rules and bayesian networks-
dc.typearticle-
dc.audiencestudents-
dc.audienceresearchers-
item.fulltextNo Fulltext-
item.grantfulltextnone-
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