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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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書誌詳細
出版年:AMIA Annu Symp Proc
主要な著者: Kotov, Alexander, Hasan, Mehedi, Carcone, April, Dong, Ming, Naar-King, Sylvie, BroganHartlieb, Kathryn
フォーマット: Artigo
言語:Inglês
出版事項: American Medical Informatics Association 2015
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オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC4765604/
https://ncbi.nlm.nih.gov/pubmed/26958214
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