Name
Title | ||
|---|---|---|
A Novel Individual Blood Glucose Control Model Based on Mixture of Experts Neural Networks |
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 (t=0.97+/-0.05, n=14) and blood glucose control aim (r=0.95+/-0.06, n=7). |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-28648-6_72 | ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 2 |
Keywords | Field | DocType |
neural network | Training set,Softmax function,Computer science,Mixture of experts,Artificial intelligence,Diabetic care,Artificial neural network,Mixture model,Machine learning | Conference |
Volume | ISSN | Citations |
3174 | 0302-9743 | 2 |
PageRank | References | Authors |
0.47 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Wang | 1 | 81 | 12.64 |
| Zhengzhong Bian | 2 | 9 | 4.42 |
| Lan-Feng Yan | 3 | 3 | 1.29 |
| Jing Su | 4 | 2 | 0.47 |