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Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces
The pathological description of the stage of a tumor is an important clinical designation and is considered, like many other forms of biomedical data, an ordinal outcome. Currently, statistical methods for predicting an ordinal outcome using clinical, demographic, and high-dimensional correlated fea...
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| Gepubliceerd in: | Cancer Inform |
|---|---|
| Hoofdauteurs: | , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Libertas Academica
2015
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4447150/ https://ncbi.nlm.nih.gov/pubmed/26052223 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4137/CIN.S17277 |
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