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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6214199/ https://www.ncbi.nlm.nih.gov/pubmed/30393771 http://dx.doi.org/10.1186/s41512-018-0043-4 |