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Comparative study of intelligent models for the prediction of bladder cancer progression.

Abstract:

New techniques for the prediction of tumour behaviour are needed since statistical analysis has low accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide suitable methods. We have compared the predictive accuracies of neuro-fuzzy modelling (NFM), artificial neural networks (ANN) and traditional statistical methods for the prediction of bladder cancer. Experimental molecular biomarkers, including p53 expression and gene methylation, and conventional clinico...

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Publication status:
Published

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Institution:
University of Oxford
Department:
Oxford, MSD, Surgical Sciences, Biomedical Research Centre
Role:
Author
Journal:
Oncology reports
Volume:
15 Spec no.
Issue:
4
Pages:
1019-1022
Publication date:
2006-01-01
EISSN:
1791-2431
ISSN:
1021-335X
URN:
uuid:82a41aa3-127d-45b3-882e-c58bb4f97ca5
Source identifiers:
120646
Local pid:
pubs:120646

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