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Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction
Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
2017 (engelsk)Inngår i: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 235, s. 241-245Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes. Here, we apply several spelling correction methods to Swedish medical text and evaluate their impact on SNOMED CT mapping; first in a controlled evaluation using medical literature text with induced errors, followed by a partial evaluation on clinical notes. It is shown that the best-performing method is context-sensitive, taking into account trigram frequencies and utilizing a corpus-based dictionary.

sted, utgiver, år, opplag, sider
2017. Vol. 235, s. 241-245
Emneord [en]
spelling correction, terminology mapping, clinical text
HSV kategori
Forskningsprogram
data- och systemvetenskap
Identifikatorer
URN: urn:nbn:se:su:diva-149424DOI: 10.3233/978-1-61499-753-5-241OAI: oai:DiVA.org:su-149424DiVA, id: diva2:1161592
Merknad

ISBN: 978-1-61499-752-8 (print), 978-1-61499-753-5 (online).

Tilgjengelig fra: 2017-11-30 Laget: 2017-11-30 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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Henriksson, AronDuneld, Martin
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RefereraExporteraLink to record
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  • ieee
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf