Predicting hepatitis B virus–positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning

@article{Ye2003PredictingHB,
  title={Predicting hepatitis B virus–positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning},
  author={Qing-hai Ye and Lunxiu Qin and Marshonna Forgues and Ping He and Jin Woo Kim and Amy C. Peng and Richard B. Sim{\'o}n and Yan Li and Ana I Robles and Yidong Chen and Zeng-chen Ma and Zhi-quan Wu and Sheng-long Ye and Yin-kun Liu and Zhao-you Tang and Xin Wei Wang},
  journal={Nature Medicine},
  year={2003},
  volume={9},
  pages={416-423}
}
Hepatocellular carcinoma (HCC) is one of the most common and aggressive human malignancies. Its high mortality rate is mainly a result of intra-hepatic metastases. We analyzed the expression profiles of HCC samples without or with intra-hepatic metastases. Using a supervised machine-learning algorithm, we generated for the first time a molecular signature that can classify metastatic HCC patients and identified genes that were relevant to metastasis and patient survival. We found that the gene… CONTINUE READING
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