Application of Artificial Neural Networks in Renal Transplantation: Classification of Nephrotoxicity and Acute Cellular Rejection Episodes

dc.contributor.authorHummel, A. D. [UNIFESP]
dc.contributor.authorMaciel, R. F. [UNIFESP]
dc.contributor.authorRodrigues, R. G. S.
dc.contributor.authorPisa, I. T. [UNIFESP]
dc.contributor.institutionUniversidade Federal de São Paulo (UNIFESP)
dc.contributor.institutionUniv Ciencias Saude Alagoas
dc.date.accessioned2016-01-24T13:59:26Z
dc.date.available2016-01-24T13:59:26Z
dc.date.issued2010-03-01
dc.description.abstractComplications associated with kidney transplantation and immunosuppression can be prevented or treated effectively if diagnosed in the early stages by posttransplant monitoring. One of the major problems is diseases that occur during the first year after kidney transplantation. for this purpose, we used different classifiers to predict events of nephrotoxicity versus acute cellular rejection episodes. the classifiers were evaluated according to values of sensitivity, specificity and area under ROC curves (RCA). the classifier with better accuracy rate for nephrotoxicity achieved the value of 75.68% and RCA classifier reached the accuracy of 80.89%. These results are encouraging, with rates of accuracy and error consistent with work purpose.en
dc.description.affiliationUniversidade Federal de São Paulo, Programa Posgrad Informat Saude, São Paulo, Brazil
dc.description.affiliationUniversidade Federal de São Paulo, Programa Posgrad Saude Colet, São Paulo, Brazil
dc.description.affiliationUniv Ciencias Saude Alagoas, Lab Instrumentacao & Acust, Maceio, AL, 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, Programa Posgrad Saude Colet, São Paulo, Brazil
dc.description.affiliationUnifespUniversidade Federal de São Paulo, Dept Informat Saude, São Paulo, Brazil
dc.description.provenanceMade available in DSpace on 2016-01-24T13:59:26Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-03-01en
dc.description.sourceWeb of Science
dc.format.extent471-472
dc.identifierhttp://dx.doi.org/10.1016/j.transproceed.2010.01.051
dc.identifier.citationTransplantation Proceedings. New York: Elsevier B.V., v. 42, n. 2, p. 471-472, 2010.
dc.identifier.doi10.1016/j.transproceed.2010.01.051
dc.identifier.issn0041-1345
dc.identifier.urihttp://repositorio.unifesp.br/handle/11600/32356
dc.identifier.wosWOS:000276051400017
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofTransplantation Proceedings
dc.rightsAcesso restrito
dc.rights.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.titleApplication of Artificial Neural Networks in Renal Transplantation: Classification of Nephrotoxicity and Acute Cellular Rejection Episodesen
dc.typeArtigo
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