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Comprehensible Predictive Modeling Using Regularized Logistic Regression and Comorbidity Based Features
Different studies have demonstrated the importance of comorbidities to better understand the origin and evolution of medical complications. This study focuses on improvement of the predictive model interpretability based on simple logical features representing comorbidities. We use group lasso based...
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| Опубликовано в: : | PLoS One |
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| Главные авторы: | , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Public Library of Science
2015
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4672891/ https://ncbi.nlm.nih.gov/pubmed/26645087 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0144439 |
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