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Artificial intelligence for the prediction bladder cancer

Abstract:

New techniques for the prediction of tumour behaviour are needed as statistical analysis has a poor accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide these suitable methods. We have previously shown that the predictive accuracies of neuro-fuzzy modelling (NFM) and artificial neural networks (ANN), two methods of AI, are superior to traditional statistical methods for the behaviour of bladder cancer (Catto et al, 2003). In this paper, we explain the AI ...

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Publisher copy:
10.4015/S1016237204000098

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Role:
Author
Journal:
Biomedical Engineering - Applications, Basis and Communications
Volume:
16
Issue:
2
Pages:
49-58
Publication date:
2004-04-25
DOI:
EISSN:
1793-7132
ISSN:
1016-2372
Source identifiers:
120956
Language:
English
Keywords:
Pubs id:
pubs:120956
UUID:
uuid:63750c4d-6500-4e1c-8b51-23cf3b5ab6ad
Local pid:
pubs:120956
Deposit date:
2013-02-20

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