DocumentCode :
2737261
Title :
Support Vector Machine for Determining Dose of Dialysis
Author :
Ray, Monika ; Atray, Naveen
Author_Institution :
Electrical Engineering and Computer Science Washington University, St. Louis, MO 63130
Volume :
2
fYear :
2004
fDate :
1-5 Sept. 2004
Firstpage :
3186
Lastpage :
3189
Abstract :
Calculation of dose of haemodialysis using blood-based modelling is subject to controversies as it is based on unrealistic assumptions. This paper proposes the use of dialysate-based modelling by SVMs to calculate the delivered dose of dialysis. The authors use the solute removal index (SRI), which is correlated to the amount of urea removed, for calculating the dose. The SVM model was trained to recognise the evolution of weight, blood urea nitrogen concentration and solute removal index with respect to time and then used to predict the solute removal index. When the estimated SRI values were compared to the actual SRI values determined by the standard method, the prediction errors were small. This paper is the first demonstration that SVM regression can predict delivered dose of haemodialysis with a clinically acceptable accuracy. The result is an effective technique that will offer the physician a better guide to the monitoring and prescription of haemodialysis therapy thereby reducing the mortality rate among patients.
Keywords :
End-stage renal disease; clinical decision making; haemodialysis; solute removal index; support vector machine; Artificial intelligence; Biomedical engineering; Blood; Decision making; Diseases; Filters; Kinetic theory; Medical diagnostic imaging; Medical treatment; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Print_ISBN :
0-7803-8439-3
Type :
conf
DOI :
10.1109/IEMBS.2004.1403898
Filename :
1403898
Link To Document :
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