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Dynamic prediction of time to a clinical event with sparse and irregularly measured longitudinal biomarkers
In clinical research and practice, landmark models are commonly used to predict the risk of an adverse future event, using patients’ longitudinal biomarker data as predictors. However, these data are often observable only at intermittent visits, making their measurement times irregularly spaced and...
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| 出版年: | Biom J |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7502505/ https://ncbi.nlm.nih.gov/pubmed/32196728 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/bimj.201900112 |
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