Artificial neural networks have been widely used in the field of engineering forecasting. This paper attempts to predict glomerular filtration rate (GFR) in Chinese patients with chronic kidney disease (CKD) by radial basis function (RBF) neural network. Our data indicated that when serum creatinine (SC) was measured by the enzymatic method, based on both overall performance as well as performance in different CKD stages, this RBF network model is suitable for the specific Chinese population tested.
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Xun et al. (2010) studied this question.
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