Artificial Intelligence in Medicine
Volume 28, Issue 1 , Pages 1-25 , May 2003

A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer

  • P.J.G. Lisboa

      Affiliations

    • School of Computing and Mathematical Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK
    • Corresponding Author InformationCorresponding author. Tel.: +55-51-33165571; fax: +55-51-33168010.
    • ,
  • H. Wong

      Affiliations

    • School of Computing and Mathematical Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK
    • ,
  • P. Harris

      Affiliations

    • School of Computing and Mathematical Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK
    • ,
  • R. Swindell

      Affiliations

    • Medical Statistics Department, Christie Hospital, Wilmslow Road, Withington, Manchester M20 4BX, UK

Received 29 July 2002 ,Revised 15 November 2002 ,Accepted 10 December 2002.

References 

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  3. Lisboa PJG. A review of evidence of health benefit from artificial neural networks in medical intervention. Neural Networks. 2002;15(1):9–37
  4. Biganzoli E, Boracchi P, Mariani L, Marubini E. Feed forward neural networks for the analysis of censored survival data: a partial logistic regression approach. Stat. Med. 1998;17:1169–1186
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  7. Ravdin PM, Clark FM, Hilsenbeck SG, Owens MA, Vendely P, Pandian MR, et al.  A demonstration that breast cancer recurrence can be predicted by neural network analysis. Breast Cancer Res. Treatment. 1992;21:47–53
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  10. Bishop CM. Neural network for pattern recognition. Oxford: Clarendon Press; 1995.
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  12. Lisboa PJG, Etchells TA, Pountney DC. Minimal MLPs do not model the XOR logic. Neurocomputing. 2002;48:1033–1037
  13. Lisboa PJG, Vellido A, Wong H. Bias reduction in skewed binary classification with Bayesian neural networks. Neural Networks. 2000;13:407–410
  14. Mantel N. Evaluation of survival data and two new rank order statistics arising in its consideration. Cancer Chemother. Rep. 1966;50:163–170
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PII: S0933-3657(03)00033-2

doi: 10.1016/S0933-3657(03)00033-2

Artificial Intelligence in Medicine
Volume 28, Issue 1 , Pages 1-25 , May 2003

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