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Interpretable Probabilistic Latent Variable Models for Automatic Annotation of Clinical Text
We propose Latent Class Allocation (LCA) and Discriminative Labeled Latent Dirichlet Allocation (DL-LDA), two novel interpretable probabilistic latent variable models for automatic annotation of clinical text. Both models separate the terms that are highly characteristic of textual fragments annotat...
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| 出版年: | AMIA Annu Symp Proc |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
American Medical Informatics Association
2015
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4765604/ https://ncbi.nlm.nih.gov/pubmed/26958214 |
| タグ: |
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