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Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration
Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerfu...
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| 出版年: | Biometrics |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2015
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4713389/ https://ncbi.nlm.nih.gov/pubmed/26177419 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/biom.12343 |
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