Artificial intelligence techniques: predicting necessity for biopsy in renal transplant recipients suspected of acute cellular rejection or nephrotoxicity
| Autor: | Fabio Oliveira Teixeira, Rafael Fabio Maciel, Roberto Silva Baptista, Frederico Molina Cohrs, T. M. da Costa, Alex Esteves Jaccoud Falcão, Anderson Diniz Hummel, Felipe Mancini, R. Miranda, R.G.D.S. Rodrigues, Domingos Alves, Fernando Sequeira Sousa, Ivan Torres Pisa |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Graft Rejection
Acute cellular rejection Biopsy Nephrotoxicity Artificial Intelligence Predictive Value of Tests Medicine Humans Transplantation medicine.diagnostic_test business.industry Patient Selection Bayes Theorem medicine.disease Decision Support Systems Clinical Kidney Transplantation Support vector machine ROC Curve Renal transplant Predictive value of tests Acute Disease Surgery Kidney Diseases Artificial intelligence Neural Networks Computer business Immunosuppressive Agents Kidney disease |
| Zdroj: | Transplantation proceedings. 43(4) |
| ISSN: | 1873-2623 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect