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SCAN: A Swedish Clinical Abbreviation Normalizer

Further Development and Adaptation to Radiology

  • Conference paper
Information Access Evaluation. Multilinguality, Multimodality, and Interaction (CLEF 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8685))

Abstract

Abbreviations pose a challenge for information extraction systems. In clinical text, abbreviations are abundant, as this type of documentation is written under time-pressure. We report work on characterizing abbreviations in Swedish clinical text and the development of SCAN: a Swedish Clinical Abbreviation Normalizer, which is built for the purpose of improving information access systems in the clinical domain. The clinical domain includes several subdomains with differing vocabularies depending on the nature of the specialist work, and adaption of NLP-tools may consequently be necessary. We extend and adapt SCAN, and evaluate on two different clinical subdomains: emergency department (ED) and radiology (X-ray). Overall final results are 85% (ED) and 83% (X-ray) F1-measure on the task of abbreviation identification. We also evaluate coverage of abbreviation expansion candidates in existing lexical resources, and create two new, freely available, lexicons with abbreviations and their possible expansions for the two clinical subdomains.

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Authors and Affiliations

  1. Dept. of Computer and Systems Sciences (DSV), Stockholm University, Forum 100, SE-164 40, Kista, Sweden

    Maria Kvist & Sumithra Velupillai

  2. Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Sweden

    Maria Kvist

Authors
  1. Maria Kvist
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  2. Sumithra Velupillai
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Editor information

Editors and Affiliations

  1. Google Inc., Brandschenkestraße 110, 8002, Zurich, Switzerland

    Evangelos Kanoulas

  2. Institute of Software Technology and Interactive Systems, Vienna University of Technology, Favoritenstrasse 9-11, 1040, Vienna, Austria

    Mihai Lupu

  3. Information School, University of Sheffield, Sheffield, UK

    Paul Clough

  4. Department of Computer Science and IT, RMIT University, 3000, Melbourne, VIC, Australia

    Mark Sanderson

  5. Department of Computing, Edge Hill University, L39 4QP, Ormskirk, Lancashire, UK

    Mark Hall

  6. Vienna University of Technology, Austria

    Allan Hanbury

  7. Information School, University of Sheffield, Regent Court, 211 Portobello, S1 4DP, Sheffield, UK

    Elaine Toms

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Kvist, M., Velupillai, S. (2014). SCAN: A Swedish Clinical Abbreviation Normalizer. In: Kanoulas, E., et al. Information Access Evaluation. Multilinguality, Multimodality, and Interaction. CLEF 2014. Lecture Notes in Computer Science, vol 8685. Springer, Cham. https://doi.org/10.1007/978-3-319-11382-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-11382-1_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11381-4

  • Online ISBN: 978-3-319-11382-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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