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Representing Clinical Knowledge in Oral Medicine Using Ontologies
University of Skövde, School of Humanities and Informatics. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).ORCID iD: 0000-0002-4828-3009
University of Skövde, The Informatics Research Centre. University of Skövde, School of Humanities and Informatics. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).ORCID iD: 0000-0001-8884-2154
2005 (English)In: Connecting Medical Informatics and Bio-Informatics: Proceedings of MIE2005 - The XIXth International Congress of the European Federation for Medical Informatics / [ed] Rolf Engelbrecht, Antoine Geissbuhler, Christian Lovis, George Mihalas, Amsterdam: IOS Press, 2005, 743-748 p.Conference paper, (Refereed)
Abstract [en]

Medical ontologies like GALEN, the FMA or SNOMED represent a kind of “100% certain” medical knowledge which is not inherent to all medical sub-domains. Clinical radiology uses computerized imaging techniques to make the human body visible and interprets the imaging findings in a clinical context delivering a textual report. For clinical radiology few standardized vocabularies are available. We examined the definitions given in the glossary of terms for thoracic radiology published by the Fleischner Society. We further classified these terms with regard to their definitions in terms of (a) describing visible structures on the image itself, (b) referring to ontological entities of the body (anatomical or pathological), and (c) terms imposing knowledge on structures visible on the image, epistemologically representing ontological entities of the body. Each ontological/epistemological definition was rated on a scale of vague/weak-sound/strong and put in context with the evaluation comments for the use of the terms given in the glossary itself. The result of this distinction shows that clinical radiology uses many terms referring to ontological entities valid for representation in a medical ontology. However, many epistemological terms exist in the terminology which impose epistemological knowledge on ontological entities. The analysis of the evaluation comments reveals that terms classified as sound (ontologically) and strong (epistemologically) are evaluated higher than terms bearing vague or weak definitions. On the basis of this, we argue that the distinction between ontological and epistemological definitions is necessary in order to construct epistemologically-sensitive application ontologies for medical sub-domains, like clinical radiology, where knowledge is fragmented in terms of description, inferred from a description, concluded on the basis of imaging, or other additional information with varying degrees of certainty.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2005. 743-748 p.
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, 1879-8365 ; 116
National Category
Computer Science
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-1703ISI: 000273025900121PubMedID: 16160347Scopus ID: 2-s2.0-84886916663ISBN: 978-1-58603-549-5 ISBN: 978-1-60750-135-0 OAI: oai:DiVA.org:his-1703DiVA: diva2:31979
Conference
MIE2005: The XIXth International Congress of the European Federation for Medical Informatics, 28-31 August 2005, Geneva, Switzerland
Available from: 2007-08-13 Created: 2007-08-13 Last updated: 2015-01-19Bibliographically approved

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PubMedScopushttp://ebooks.iospress.nl/volumearticle/10394

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CiteExportLink to record
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Citation style
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