Please use this identifier to cite or link to this item:
|Title:||Artificial Intelligence Techniques: Predicting Necessity for Biopsy in Renal Transplant Recipients Suspected of Acute Cellular Rejection or Nephrotoxicity|
|Authors:||Hummel, A. D. [UNIFESP]|
Maciel, R. F. [UNIFESP]
Sousa, F. S. [UNIFESP]
Cohrs, Frederico Molina [UNIFESP]
Falcao, A. E. J. [UNIFESP]
Teixeira, F. [UNIFESP]
Baptista, R. [UNIFESP]
Mancini, F. [UNIFESP]
Costa, Thiago Martini da [UNIFESP]
Rodrigues, R. G. D. S.
Pisa, I. T. [UNIFESP]
Universidade Federal de São Paulo (UNIFESP)
Universidade de São Paulo (USP)
Univ Ciencias Saude Alagoas
Univ Fed Rural Pernambuco
|Citation:||Transplantation Proceedings. New York: Elsevier B.V., v. 43, n. 4, p. 1343-1344, 2011.|
|Abstract:||The gold standard for nephrotoxicity and acute cellular rejection (ACR) is a biopsy, an invasive and expensive procedure. More efficient strategies to screen patients for biopsy are important from the clinical and financial points of view. the aim of this study was to evaluate various artificial intelligence techniques to screen for the need for a biopsy among patients suspected of nephrotoxicity or ACR during the first year after renal transplantation. We used classifiers like artificial neural networks (ANN), support vector machines (SVM), and Bayesian inference (BI) to indicate if the clinical course of the event suggestive of the need for a biopsy. Each classifier was evaluated by values of sensitivity and area under the ROC curve (AUC) for each of the classifiers. the technique that showed the best sensitivity value as an indicator for biopsy was SVM with an AUC of 0.79 and an accuracy rate of 79.86%. the results were better than those described in previous works. the accuracy for an indication of biopsy screening was efficient enough to become useful in clinical practice.|
|Appears in Collections:||Em verificação - Geral|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.