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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

Authors


Catto, JWF More by this author
Linkens, DA More by this author
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, Surgical Sciences, Biomedical Research Centre
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
URN:
uuid:63750c4d-6500-4e1c-8b51-23cf3b5ab6ad
Source identifiers:
120956
Local pid:
pubs:120956

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