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Automatic Morphosyntactic Analaysis of Clinical Text
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (datorlingvistik)
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (datorlingvistik)
2014 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Electronical health records, also called clinical texts, have their own linguistic characteristics and have been shown to deviate from standard language. Therefore, computational linguistics tools trained on standard language presumably do not achieve the same accuracy when applied to clinical data. In this paper, we describe a pipeline of tools for the automatic processing of clinical texts in Swedish from tokenization through part-of-speech tagging and dependency parsing. The evaluation of the components of the pipeline shows that existing NLP tools can be used, but performance drops greatly when models trained on standard language are applied to clinical data. We also present a small, syntactically annotated data set of clinical text to serve as gold standard.

Place, publisher, year, edition, pages
2014.
Keyword [en]
clinical texts, morphosyntactic analysis
National Category
Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:uu:diva-239451OAI: oai:DiVA.org:uu-239451DiVA: diva2:774589
Conference
The Fifth Swedish Language Technology Conference, SLTC 2014,13-14 November 2014, Uppsala, Sweden
Available from: 2014-12-26 Created: 2014-12-26 Last updated: 2015-01-27Bibliographically approved

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fulltext(316 kB)108 downloads
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Type fulltextMimetype application/pdf

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Megyesi, Beata

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf