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Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data
BACKGROUND: Understanding the complex biological mechanisms of cancer patient survival using genomic and clinical data is vital, not only to develop new treatments for patients, but also to improve survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause...
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| I publikationen: | BMC Med Genomics |
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| Huvudupphovsmän: | , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
BioMed Central
2019
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6927105/ https://ncbi.nlm.nih.gov/pubmed/31865908 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12920-019-0624-2 |
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