Name
Title | ||
|---|---|---|
Recognition of Coronary Heart Disease Patients by RBF Neural Network Basing on Contents of Microelements in Human Blood |
Abstract | ||
|---|---|---|
Radial-Basis-Function (RBF) artificial neural network was developed to recognize the coronary heart disease patients basing on the contents of microelements in human blood. Leave-one out method was used to train the model. After training, the RBF model was used to recognize the coronary heart disease patients. Results showed that the RBF model recognized the three samples correctly, and the accuracy of RBF model was higher than the BP model. It showed that the RBF model could recognize the patients more accurately and it has important theoretical meaning and application value. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ISCID.2009.248 | ISCID (2) |
Keywords | Field | DocType |
application value,coronary heart disease patients,rbf model,bp model,coronary heart disease patient,important theoretical meaning,human blood,rbf neural network basing,artificial neural network,heart,radial basis function,cardiology,backpropagation,artificial neural networks,mathematical model,predictive models | Pattern recognition,Computer science,Artificial intelligence,Artificial neural network,Backpropagation,Heart disease | Conference |
Citations | PageRank | References |
1 | 0.35 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei You | 1 | 11 | 4.20 |
| Y.-Y. Wang | 2 | 539 | 75.11 |
| Baoan Wo | 3 | 1 | 0.35 |
| Shuiqing Lv | 4 | 1 | 0.35 |
| Aili Zhan | 5 | 1 | 0.35 |
| Wenjing Sun | 6 | 1 | 0.35 |