Application of neural networks and sensitivity analysis to improved prediction of trauma survival
โ Scribed by Andrew Hunter; Lee Kennedy; Jenny Henry; Ian Ferguson
- Book ID
- 114175814
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 90 KB
- Volume
- 62
- Category
- Article
- ISSN
- 0169-2607
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Tool wear sensing plays an important role in the optimisation of tool exchange and tip geometry compensation during automated machining in flexible manufacturing systems. The focus of this work is to develop a reliable method to predict flank wear during a turning process. A neural network scheme i
Results breast carcinoma data set, using only the TNM variables, the artificial neural network's predictions of 10-year survival were significantly more accurate 4 Division of Cancer Treatment, National Cancer than those of the TNM staging system (TNM, 0.692; ANN, 0.730; P รต 0.01). For
This paper investigates the use of neural networks for the identification of linear time invariant dynamical systems. Two classes of networks, namely the multilayer feedforward network and the recurrent network with linear neurons, are studied. A notation based on Kronecker product and vector-valued
This paper considers the application of artificial neural networks to determine the relationships between the bond rating of the financial variables of the major companies of the U.S.A. Owing to the high correlation between some of the financial variables, the inputs to the neural network are in pri