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A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis
Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such infor...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638936/ https://www.ncbi.nlm.nih.gov/pubmed/29026100 http://dx.doi.org/10.1038/s41598-017-13133-5 |