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Combining Biomarkers Linearly and Nonlinearly for Classification Using the Area Under the ROC Curve
In biomedical studies, it is often of interest to classify/predict a subject’s disease status based on a variety of biomarker measurements. A commonly used classification criterion is based on AUC - Area under the Receiver Operating Characteristic Curve. Many methods have been proposed to optimize a...
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| 出版年: | Stat Med |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2016
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4965290/ https://ncbi.nlm.nih.gov/pubmed/27058981 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.6956 |
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