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Integration of gene interaction information into a reweighted random survival forest approach for accurate survival prediction and survival biomarker discovery
Accurately predicting patient risk and identifying survival biomarkers are two important tasks in survival analysis. For the emerging high-throughput gene expression data, random survival forest (RSF) is attracting more and more attention as it not only shows excellent performance on survival predic...
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| Format: | Online Artikel Text |
| Sprache: | English |
| Veröffentlicht: |
Nature Publishing Group UK
2018
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| Online Zugang: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123437/ https://www.ncbi.nlm.nih.gov/pubmed/30181543 http://dx.doi.org/10.1038/s41598-018-31497-0 |