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A novel ANFIS application for prediction of post-dialysis blood urea concentration
by Ahmad Taher Azar
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 12, No. 2, 2013
Abstract: Dialysis dose (Kt/V) is mostly dependent on dialysis kinetic variables such as pre-dialysis and post-dialysis blood urea nitrogen concentration (Cpost), ultrafiltration (UF) volume, duration of the dialysis procedure, and urea distribution volume. Therefore, post-dialysis blood urea concentration is used to assess the dialysis efficiency. It gradually decreases to about 30% of the pre-dialysis value depending on the urea clearance rate during the period of dialysis. If the urea removal is inadequate, then dialysis is inadequate. This paper proposes a novel method, Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the post-dialysis blood urea concentration. The advantage of this neuro-fuzzy hybrid approach is that it does not require the model structure to be known a priori, in contrast to most of the urea kinetic modelling techniques. The accuracy of the ANFIS was prospectively compared with other traditional methods for predicting single pool dialysis dose (spKt/V). The results are highly promising, and a comparative analysis suggests that the proposed modelling approach outperforms other traditional urea kinetic models (UKM).
Online publication date: Fri, 30-Aug-2013
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