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A novel framework for horizontal and vertical data integration in cancer studies with application to survival time prediction models
BACKGROUND: Recently high-throughput technologies have been massively used alongside clinical tests to study various types of cancer. Data generated in such large-scale studies are heterogeneous, of different types and formats. With lack of effective integration strategies novel models are necessary...
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| Publié dans: | Biol Direct |
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| Auteurs principaux: | , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
BioMed Central
2019
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6868770/ https://ncbi.nlm.nih.gov/pubmed/31752974 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13062-019-0249-6 |
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