Name
Abstract | ||
|---|---|---|
The aim of research is to develop artificial neural network based system for childhood obesity prediction based on various types of medical and sociological data. If obesity could be predicted it could be prevented in most cases and degenerative and chronic diseases caused by it avoided. A new generation of artificial neural network is used to handle this difficult problem successfully. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1109/ANNES.1995.499512 | ANNES |
Keywords | Field | DocType |
chronic disease,childhood obesity prediction,sociological data,difficult problem,various type,artificial neural networks,childhood obesity predicition,new generation,artificial neural network,computer science,system testing,backpropagation,pediatrics,application software | Radial basis function neural,System testing,Computer science,Childhood obesity,Artificial intelligence,Application software,Backpropagation,Chronic disease,Artificial neural network,Machine learning | Conference |
ISBN | Citations | PageRank |
0-8186-7174-2 | 1 | 0.48 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bojan Novak | 1 | 5 | 2.45 |
| Martin Bigec | 2 | 1 | 0.48 |