A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL

Na Hong, Guoqian D Jiang, Jyotishiman Pathak, Christopher G. Chute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning.

Original languageEnglish (US)
Title of host publicationStudies in Health Technology and Informatics
PublisherIOS Press
Pages1093
Number of pages1
Volume216
ISBN (Print)9781614995630
DOIs
StatePublished - 2015
Event15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil
Duration: Aug 19 2015Aug 23 2015

Publication series

NameStudies in Health Technology and Informatics
Volume216
ISSN (Print)09269630
ISSN (Electronic)18798365

Other

Other15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
CountryBrazil
CitySao Paulo
Period8/19/158/23/15

Keywords

  • Diagnostic Criteria
  • Formalization
  • OWL
  • Rules
  • SWRL

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Hong, N., Jiang, G. D., Pathak, J., & Chute, C. G. (2015). A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL. In Studies in Health Technology and Informatics (Vol. 216, pp. 1093). (Studies in Health Technology and Informatics; Vol. 216). IOS Press. https://doi.org/10.3233/978-1-61499-564-7-1093