Artificial neural networks for decision-making in urologic oncology.

@article{Anagnostou2003ArtificialNN,
  title={Artificial neural networks for decision-making in urologic oncology.},
  author={Theodore Anagnostou and Mesut Remzi and Michael Lykourinas and Bob Djavan},
  journal={European urology},
  year={2003},
  volume={43 6},
  pages={596-603}
}
The authors are presenting a thorough introduction in Artificial Neural Networks (ANNs) and their contribution to modern Urologic Oncology. The article covers a description of Artificial Neural Network methodology and points out the differences of Artificial Intelligence to traditional statistic models in terms of serving patients and clinicians, in a different way than current statistical analysis. Since Artificial Intelligence is not yet fully understood by many practicing clinicians, the… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 47 references

Artificial Neural Network model to predict biochemical failure after radical prostatectomy

  • C Porter, C O’Donnel, ED Crawford, EJ Gamito, A Errejon, E Genega
  • Mol Urol
  • 2001
1 Excerpt

Artificial Neural Networks to predict the outcome of repeat prostate biopsies

  • M Remzi, B Djavan, C Seitz, S Hruby, M. Marberger
  • J Urol 2001;165(Suppl 5):A357
  • 2001
1 Excerpt

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