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- W2563583309 abstract "In clinical documents, medical terms are often expressed in multi-word phrases. Traditional topic modelling approaches relying on the bag-of-words assumption are not effective in extracting topic themes from clinical documents. This paper proposes to first extract medical phrases using an off-the-shelf tool for medical concept mention extraction, and then train a topic model which takes a hierarchy of Pitman-Yor processes as prior for modelling the generation of phrases of arbitrary length. Experimental results on patients' discharge summaries show that the proposed approach outperforms the state-of-the-art topical phrase extraction model on both perplexity and topic coherence measure and finds more interpretable topics." @default.
- W2563583309 created "2017-01-06" @default.
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- W2563583309 date "2016-03-05" @default.
- W2563583309 modified "2023-10-04" @default.
- W2563583309 title "Extracting Topical Phrases from Clinical Documents" @default.
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- W2563583309 doi "https://doi.org/10.1609/aaai.v30i1.10365" @default.
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