NDLI: Artificial Intelligence Technique for Gene Expression Profiling of Urinary Bladder Cancer

Content Provider	IEEE Xplore Digital Library
Author	Abbod, M.F. Catto, J.W.F. Linkens, D.A. Wild, P.J. Herr, A. Wissmann, C. Pilarsky, C. Hartmann, A. Hamdy, F.C.
Copyright Year	2006
Description	Author affiliation: Sch. of Eng. & Design, Brunel Univ., Uxbridge (Abbod, M.F.)
Abstract	The purpose of this study is to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial intelligence (AI) techniques which provide better predictions than standard traditional statistical methods. The predictive accuracies of neuro-fuzzy modelling (NFM), artificial neural networks (ANN) and traditional logistic regression (LR) methods are compared for the behaviour of bladder cancer. Gene expression profiles of non-invasive and invasive bladder cancer were used to identify potential therapeutic or screening targets in bladder cancer, and to define genetic changes relevant for tumour progression of recurrent papillary bladder cancer (pTa). For all three methods, models were produced to predict the presence and timing of a tumour progression, stage and grade. AI methodology predicted progression with an accuracy ranging up to 100%. This was superior to logistic regression
Starting Page	646
Ending Page	651
File Size	6288531
Page Count	6
File Format	PDF
ISBN	142440195X
DOI	10.1109/IS.2006.348495
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-09-04
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial intelligence Gene expression Bladder Cancer Predictive models Artificial neural networks Logistics Tumors Standards development Statistical analysis logistic regression Bladder cancer gene expression neuro-fuzzy modelling
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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