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

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

Autor Hummel, A. D. Autor UNIFESP Google Scholar
Maciel, R. F. Autor UNIFESP Google Scholar
Rodrigues, R. G. S. Google Scholar
Pisa, I. T. Autor UNIFESP Google Scholar
Instituição Universidade Federal de São Paulo (UNIFESP)
Univ Ciencias Saude Alagoas
Resumo Complications 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.
Idioma Inglês
Data de publicação 2010-03-01
Publicado em Transplantation Proceedings. New York: Elsevier B.V., v. 42, n. 2, p. 471-472, 2010.
ISSN 0041-1345 (Sherpa/Romeo, fator de impacto)
Publicador Elsevier B.V.
Extensão 471-472
Fonte http://dx.doi.org/10.1016/j.transproceed.2010.01.051
Direito de acesso Acesso restrito
Tipo Artigo
Web of Science WOS:000276051400017
Endereço permanente http://repositorio.unifesp.br/handle/11600/32356

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