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Similarity of Medical Cases in Health Care Using Cosine Similarity and Ontology
Mälardalen University, Department of Computer Science and Electronics.ORCID iD: 0000-0002-1212-7637
Mälardalen University, Department of Computer Science and Electronics.ORCID iD: 0000-0003-3802-4721
Mälardalen University, Department of Computer Science and Electronics.ORCID iD: 0000-0002-5562-1424
Mälardalen University, Department of Computer Science and Electronics.ORCID iD: 0000-0001-9857-4317
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2007 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The increasing use of digital patient records in hospital saves both time and reduces risks wrong treatments caused by lack of information. Digital patient records also enable efficient spread and transfer of experience gained from diagnosis and treatment of individual patient. This is today mostly manual (speaking with col-leagues) and rarely aided by computerized system. Most of the content in patient re-cords is semi-structured textual information. In this paper we propose a hybrid tex-tual case-based reasoning system promoting experience reuse based on structured or unstructured patient records, case-based reasoning and similarity measurement based on cosine similarity metric improved by a domain specific ontology and the nearest neighbor method. Not only new cases are learned, hospital staff can also add comments to existing cases and the approach enables prototypical cases.

Place, publisher, year, edition, pages
2007.
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-7034OAI: oai:DiVA.org:mdh-7034DiVA, id: diva2:237044
Conference
5th Workshop on CBR in the Health Sciences, Belfast, Northern Ireland
Available from: 2009-09-25 Created: 2009-09-25 Last updated: 2017-01-25Bibliographically approved

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Begum, ShahinaAhmed, Mobyen UddinFunk, PeterXiong, Ning

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Begum, ShahinaAhmed, Mobyen UddinFunk, PeterXiong, Ning
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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
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  • asciidoc
  • rtf