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Identifying Important Risk Factors for Survival in Systolic Heart Failure Patients Using Random Survival Forests
BACKGROUND: Heart failure survival models are typically constructed using Cox-proportional hazards regression. Regression modeling suffers from a number of limitations, including bias introduced by commonly used variable selection methods. We illustrate the value of an intuitive, robust approach to...
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| Главные авторы: | , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2010
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3991475/ https://ncbi.nlm.nih.gov/pubmed/21098782 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1161/CIRCOUTCOMES.110.939371 |
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