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Using SNOMED CT for High Precision Entity Recognition in Swedish Clinical text
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2011 (English)Other (Other (popular science, discussion, etc.))
Abstract [en]

An evaluation was performed of retrieval of findings in Swedish clinical text through exact string matching against SNOMED CT. The aim was to create a system for retrieving clinical findings with high precision that for example can be used as training data for machine learning. The evaluation was performed on previously manually annotated findings, and the best approach showed a precision of 93 percent.

Place, publisher, year, pages
2011.
Keyword [en]
Clinical text, Swedish, Findings, SNOMED CT
Keyword [sv]
Klinisk text, Svenska, Medicinska fynd, SNOMED CT
National Category
Information Science
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-62359OAI: oai:DiVA.org:su-62359DiVA: diva2:441284
Available from: 2011-09-15 Created: 2011-09-15

Open Access in DiVA

fulltext(128 kB)96 downloads
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File name FULLTEXT01.pdfFile size 128 kBChecksum SHA-512
c6c6b0c9b90375176143e80e1e585003288d1d567eb3d2beea12b954e3587de88f1df052f8a5317ef02a864895a2b828a6e68abf7832941262f0714e683dc58b
Type fulltextMimetype application/pdf

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Department of Computer and Systems Sciences
Information Science

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
  • rtf