Application of the Intelligent Techniques in Transplantation Databases: A Review of Articles Published in 2009 and 2010

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dc.contributor.authorSousa, Fernando Sequeira [UNIFESP]
dc.contributor.authorHummel, Anderson Diniz [UNIFESP]
dc.contributor.authorMaciel, Rafael Fabio [UNIFESP]
dc.contributor.authorCohrs, Frederico Molina [UNIFESP]
dc.contributor.authorFalcão, Alex Esteves Jaccoud [UNIFESP]
dc.contributor.authorTeixeira, Fabio Oliveira [UNIFESP]
dc.contributor.authorBaptista, Roberto Silva [UNIFESP]
dc.contributor.authorMancini, Felipe [UNIFESP]
dc.contributor.authorCosta, Thiago Martini da [UNIFESP]
dc.contributor.authorAlves, Domingos [UNIFESP]
dc.contributor.authorPisa, Ivan Torres [UNIFESP]
dc.contributor.institutionUniversidade Federal de São Paulo (UNIFESP)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2016-01-24T14:06:26Z
dc.date.available2016-01-24T14:06:26Z
dc.date.issued2011-05-01
dc.description.abstractThe replacement of defective organs with healthy ones is an old problem, but only a few years ago was this issue put into practice. Improvements in the whole transplantation process have been increasingly important in clinical practice. in this context are clinical decision support systems (CDSSs), which have reflected a significant amount of work to use mathematical and intelligent techniques. the aim of this article was to present consideration of intelligent techniques used in recent years (2009 and 2010) to analyze organ transplant databases. To this end, we performed a search of the PubMed and Institute for Scientific Information (ISI) Web of Knowledge databases to find articles published in 2009 and 2010 about intelligent techniques applied to transplantation databases. Among 69 retrieved articles, we chose according to inclusion and exclusion criteria. the main techniques were: Artificial Neural Networks (ANN), Logistic Regression (LR), Decision Trees (DT), Markov Models (MM), and Bayesian Networks (BN). Most articles used ANN. Some publications described comparisons between techniques or the use of various techniques together. the use of intelligent techniques to extract knowledge from databases of healthcare is increasingly common. Although authors preferred to use ANN, statistical techniques were equally effective for this enterprise.en
dc.description.affiliationUniversidade Federal de São Paulo, Programa Posgrad Informat Saude, São Paulo, Brazil
dc.description.affiliationUniv São Paulo, Fac Med Ribeirao Preto, Programa Posgrad Saude Coletiva, Ribeirao Preto, SP, Brazil
dc.description.affiliationUniv São Paulo, Fac Med Ribeirao Preto, Dept Social Med, Ribeirao Preto, SP, Brazil
dc.description.affiliationUniversidade Federal de São Paulo, Dept Informat Saude, São Paulo, Brazil
dc.description.affiliationUnifespUniversidade Federal de São Paulo, Programa Posgrad Informat Saude, São Paulo, Brazil
dc.description.affiliationUnifespUniversidade Federal de São Paulo, Dept Informat Saude, São Paulo, Brazil
dc.description.sourceWeb of Science
dc.format.extent1340-1342
dc.identifierhttp://dx.doi.org/10.1016/j.transproceed.2011.02.028
dc.identifier.citationTransplantation Proceedings. New York: Elsevier B.V., v. 43, n. 4, p. 1340-1342, 2011.
dc.identifier.doi10.1016/j.transproceed.2011.02.028
dc.identifier.fileWOS000291289400101.pdf
dc.identifier.issn0041-1345
dc.identifier.urihttp://repositorio.unifesp.br/handle/11600/33648
dc.identifier.wosWOS:000291289400101
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofTransplantation Proceedings
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.titleApplication of the Intelligent Techniques in Transplantation Databases: A Review of Articles Published in 2009 and 2010en
dc.typeinfo:eu-repo/semantics/article
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