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Medical knowledge extraction. Applications of data analysis methods
Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
1992 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

In this thesis we explore and discuss some important methods for knowledge extraction from meclical data. This is done in relation to, and for the purpose of design and development of decision support systems, which could be population specific.

To test data and extract knowledge, we use univariate and multivariate statistical methods, the rough sets theory and probabilistic artificial intelligence approaches. These methods are used to estimate characteristics of patient groups, disease profiles and other features relevant for medical problems. In particular, we apply them to clifferentiate among patient groups, develop patient models and derive decision rules. Our experience refers to two medical domains (patients with diagnosed and non-diagnosed, but suspected liver disease and patients with duodenal ulcer surgery).

Extracted knowledge can be used both in clinical practice and health care programs, as well as in computer based decision support systems to adjust them to various clinical environments.

sted, utgiver, år, opplag, sider
Linköping: Linköpings universitet , 1992. , s. 22 + 4 papers
Serie
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 311
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-29511Lokal ID: LiU-Tek-Lic 1992:03ISBN: 91-7870-871-0 (tryckt)OAI: oai:DiVA.org:liu-29511DiVA, id: diva2:250326
Presentation
1992-02-14, Föreläsningssalen, IMT, plan 11, Lab II-byggnaden, Campus US, Linköpings universitet, Linköping, 14:00 (engelsk)
Tilgjengelig fra: 2009-10-09 Laget: 2009-10-09 Sist oppdatert: 2013-12-05bibliografisk kontrollert

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RefereraExporteraLink to record
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Referensformat
  • apa
  • harvard1
  • ieee
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  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf