Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma.

@article{Wei2004PredictionOC,
  title={Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma.},
  author={Jun S Wei and Braden T. Greer and Frank Westermann and Seth Steinberg and Chang-Gue Son and Qing-Rong Chen and Craig C. Whiteford and Sven Bilke and Alexei L. Krasnoselsky and Nicola Cenacchi and Daniel R. Catchpoole and Frank Berthold and Manfred Schwab and Javed Khan},
  journal={Cancer research},
  year={2004},
  volume={64 19},
  pages={6883-91}
}
Currently, patients with neuroblastoma are classified into risk groups (e.g., according to the Children's Oncology Group risk-stratification) to guide physicians in the choice of the most appropriate therapy. Despite this careful stratification, the survival rate for patients with high-risk neuroblastoma remains <30%, and it is not possible to predict which of these high-risk patients will survive or succumb to the disease. Therefore, we have performed gene expression profiling using cDNA… CONTINUE READING

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