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Combined performance of screening and variable selection methods in ultra-high dimensional data in predicting time-to-event outcomes
BACKGROUND: Building prognostic models of clinical outcomes is an increasingly important research task and will remain a vital area in genomic medicine. Prognostic models of clinical outcomes are usually built and validated utilizing variable selection methods and machine learning tools. The challen...
Tallennettuna:
| Julkaisussa: | Diagn Progn Res |
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| Päätekijät: | , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
BioMed Central
2018
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6214199/ https://ncbi.nlm.nih.gov/pubmed/30393771 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s41512-018-0043-4 |
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