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Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Azar AT and Wahba K (2008) Association between Neural Network and System Dynamics to Predict Dialysis Dose During Hemodialysis. 26th International Conference of the System Dynamics Society, July 20 – 24, Athens, Greece
Authors: Not Available
Year: 2008
Keywords: Not Available
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Issue: Not Available
Pages: Not Available
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Local/International: International
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Abstract:

The total dialysis dose, expressed as Kt/V, has been widely recognized to be a major determinant of morbidity and mortality in hemodialyzed patients. Many different factors influence the correct determination of Kt/V, such as urea sequestration in different body compartments, access and cardiopulmonary recirculation. These factors are responsible for urea rebound after the end of the hemodialysis session, causing poor Kt/ V estimation. In this work, system dynamics model was combined with a neural network (NN) method for early prediction of the Kt/V dose. Two different portions of the urea concentration-time profile provided by the system dynamics (on-line urea monitor) were analyzed: the entire curve A and the first half B, using an NN to predict the Kt/V and compare this with that provided by the system dynamics model. The NN was able to predict Kt/V is the middle of the 4h session (B data) without a significant increase in the percentage error (B data: 6.65%±2.51%; A data: 5.62%±8.65%) compared with the system dynamics Kt/ V.

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