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Disease Diagnosis Using Query-Based Neural Networks.
- Source :
- Advances in Neural Networks - ISNN 2005; 2005, p767-773, 7p
- Publication Year :
- 2005
-
Abstract
- The ability of high tolerance for learning-by-example makes neural networks flexible and powerful in resolving various application problems. However, while being applied in real world, the time required to induce models from large data sets should be considered. In this paper, we apply QSS (Query-based learning with Selective-attention and Self-regulation) to back-propagation neural networks for resolving the data classification problem in biomedical applications. Results show that the proposed method can significantly reduce the training set cardinality. Additionally, the quality of training results can be ensured. It provides a powerful tool to help physicians analyze, model and make sense of complex clinical data for disease diagnosis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783540259145
- Database :
- Complementary Index
- Journal :
- Advances in Neural Networks - ISNN 2005
- Publication Type :
- Book
- Accession number :
- 32883948
- Full Text :
- https://doi.org/10.1007/11427469_122