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Porting a Rule-based Assertion Classifier for Clinical Text from English to Swedish
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Karolinska University Hospital.
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2013 (English)In: Proceedings of the 4th International Louhi Workshop on Health Document Text Mining and Information Analysis - Louhi 2013 / [ed] Hanna Suominen, NICTA, Australia's ICT Research Centre of Excellence , 2013Conference paper, Published paper (Refereed)
Abstract [en]

An existing rule-based assertion classier is ported from En- glish to Swedish: pyConTextSwe. Evaluation on Swedish clinical texts shows that the English lexical resources are useful, but that there are assertion cues not obtainable in existing resources. Iterative error cor- rection of cue lexicons improves results for the ported classier. Overall nal results are 82% F-score on a development set and 74% on a test set.

Place, publisher, year, edition, pages
NICTA, Australia's ICT Research Centre of Excellence , 2013.
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-95949OAI: oai:DiVA.org:su-95949DiVA: diva2:662482
Conference
The 4th International Louhi Workshop on Health Document Text Mining and Information Analysis, Sydney, NSW, Australia, 11-12 February 2013
Available from: 2013-11-07 Created: 2013-11-07 Last updated: 2013-11-19Bibliographically approved

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http://nicta.com.au/__data/assets/pdf_file/0009/37656/louhi2013_submission_7.pdf

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