The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression

Catto, J.W.F., Abbod, M.F., Wild, P.J. et al. (10 more authors) (2010) The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression. European Urology, 57 (3). pp. 398-406. ISSN 0302-2838

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Authors/Creators:
  • Catto, J.W.F.
  • Abbod, M.F.
  • Wild, P.J.
  • Linkens, D.A.
  • Pilarsky, C.
  • Rehman, I.
  • Rosario, D.J.
  • Denzinger, S.
  • Burger, M.
  • Stoehr, R.
  • Knuechel, R.
  • Hartmann, A.
  • Hamdy, F.C.
Copyright, Publisher and Additional Information: © 2010 Elsevier. This is an author produced version of a paper subsequently published in European Urology. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Artificial intelligence; Gene array; Bladder cancer; Prognosis
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine (Sheffield)
Depositing User: Miss Anthea Tucker
Date Deposited: 24 Feb 2010 17:27
Last Modified: 08 Jun 2014 23:26
Published Version: http://dx.doi.org/10.1016/j.eururo.2009.10.029
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.eururo.2009.10.029

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Filename: Catto_10439.pdf

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