The Journal of Urology
Volume 182, Issue 2 , Pages 423-424 , August 2009

Prediction Models for Transitional Cell Carcinoma

References 

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  2. Schwarzer G, Schumacher M. Artificial neural networks for diagnosis and prognosis in prostate cancer. Semin Urol Oncol. 2002;20:89
  3. Schwarzer G, Vach W, Schumacher M. On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology. Stat Med. 2000;19:541
  4. Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361
  5. Kattan MW, Hess KR, Beck JR. Experiments to determine whether recursive partitioning (CART) or an artificial neural network overcomes theoretical limitations of Cox proportional hazards regression. Comput Biomed Res. 1998;31:363
  6. Schellhammer P, Cockett A, Boccon-Gibod L, et al. Assessment of endpoints for clinical trials for localized prostate cancer. Urology. 1997;49:27

PII: S0022-5347(09)01259-2

doi: 10.1016/j.juro.2009.05.072

The Journal of Urology
Volume 182, Issue 2 , Pages 423-424 , August 2009

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