Abstract
This paper addresses the important intelligent predicting problem of peritoneal absorption rate in the peritoneal dialysis treatment process of renal failure. As the index of dialysis adequacy, KT/V and Ccr are widely used and accepted. However, growing evidence suggests that the fluid balance may play a critical role in dialysis adequacy and patient outcome. Peritoneal fluid absorption decreases the peritoneal fluid removal. Understanding the peritoneal fluid absorption rate will help clinicians to optimize the dialysis dwell time. The neural network approach is applied to the prediction of peritoneal absorption rate. Compared with multivariable regression method, the experimental results showed that neural network method has an advantage over multivariable regression. The application of this predicting method based-on neural network in clinic is instructive.
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This work was supported in part by the guangdong Province Scientific and Technological key Research Program (No.2002C3021l) and the South China University of Technology.
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Zhang, M., Hu, Y. & Wang, T. Intelligent predicting approach of peritoneal fluid absorption rate based-on neural network. J. Control Theory Appl. 1, 82–85 (2003). https://doi.org/10.1007/s11768-003-0013-3
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DOI: https://doi.org/10.1007/s11768-003-0013-3