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EACL - Expansion of Abbreviations in CLinical text
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Computational linguistics)
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Computational linguistics)ORCID iD: 0000-0002-4838-6518
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2014 (English)In: Workshop on Predicting and Improving Text Readability for Target Reader Populations, PITR 2014, 2014Conference paper, Published paper (Refereed)
Abstract [en]

In the medical domain, especially in clinical texts, non-standard abbreviations are prevalent, which impairs readability for patients. To ease the understanding of the physicians’ notes, abbreviations need to be identified and expanded to their original forms. We present a distributional semantic approach to find candidates of the original form of the abbreviation, and combine this with Levenshtein distance to choose the correct candidate among the semantically related words. We apply the method to radiology reports and medical journal texts, and compare the results to general Swedish. The results show that the correct expansion of the abbreviation can be found in 40% of the cases, an improvement by 24 percentage points compared to the baseline (0.16), and an increase by 22 percentage points compared to using word space models alone (0.18).

Place, publisher, year, edition, pages
2014.
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:uu:diva-264782OAI: oai:DiVA.org:uu-264782DiVA: diva2:861523
Conference
European Association for Computational Linguistics, EACL 2014
Available from: 2015-10-17 Created: 2015-10-17 Last updated: 2017-01-25

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Megyesi, Beata

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