Measuring the blood urea nitrogen concentration

is crucial to uate dialysis dose (Kt/V) in patients

with renal failure. Although frequent measurement is needed

to avoid inadequate dialysis efficiency, artificial intelligence

can repeatedly perform the forecasting tasks and

may be a satisfactory substitute for laboratory tests. Artificial

neural networks represent a promising alternative to

classical statistical and mathematical methods to solve

multidimensional nonlinear problems. It also represents a

promising forecasting application in nephrology. In this

study, multilayer perceptron (MLP) neural network with

fast learning algorithms is used for the accurate prediction

of the post-dialysis blood urea concentration-Measuring the blood urea nitrogen concentration

is crucial to　uate dialysis dose (Kt/V) in patients

with renal failure. Although frequent measurement is needed

to avoid inadequate dialysis efficiency, artificial intelligence

can repeatedly perform the forecasting tasks and

may be a satisfactory substitute for laboratory tests. Artificial

neural networks represent a promising alternative to

classical statistical and mathematical methods to solve

multidimensional nonlinear problems. It also represents a

promising forecasting application in nephrology. In this

study, multilayer perceptron (MLP) neural network with

fast learning algorithms is used for the accurate prediction

of the post-dialysis blood urea concentration