Abstract
An individual blood glucose control model (IBGCM) based on the Mixture of Experts (MOE) neural networks algorithm was designed to improve the diabetic care. MOE was first time used to integrate multiple individual factors to give suitable decision advice for diabetic therapy. The principle of MOE, design and implementation of IBGCM were described in details. The blood glucose value (BGV) from IBGCM extremely approximated to training data (r=0.97± 0.05, n=14) and blood glucose control aim (r=0.95± 0.06, n=7).
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© 2004 Springer-Verlag Berlin Heidelberg
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Wang, W., Bian, ZZ., Yan, LF., Su, J. (2004). A Novel Individual Blood Glucose Control Model Based on Mixture of Experts Neural Networks. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_72
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DOI: https://doi.org/10.1007/978-3-540-28648-6_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
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