Ontology-based modeling of breast cancer follow-up clinical practice guideline for providing clinical decision support

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

17 Citations (Scopus)

Abstract

Breast cancer is the most common cancer among women in Canada. There are identified incentives to the transfer of breast cancer follow-up care to family physicians after primary treatment has been completed by oncologists at the tertiary care centers. This paper presents a semantic web approach to develop a clinical decision support system to support family physicians to provide breast cancer follow-up care. Our approach involved the computerization and execution of a breast cancer follow-up Clinical Practice Guideline. The computerization of the clinical practice guideline led to the development of a breast cancer ontology. We present our breast cancer ontology which models the knowledge inherent within the breast cancer follow-up clinical practice guideline-the breast cancer ontology serves as the knowledge source to determine patient-specific recommendations. In this paper, we discuss the ontology engineering process that highlights the specification of our breast cancer ontology in terms of clinical concepts and the relationships between the concepts expressed as OWL classes and properties, using the Proté gé ontology development tool.

Original languageEnglish
Title of host publicationProceedings - Twentieth IEEE International Symposium on Computer-Based Medical Systems, CBMS'07
Pages542-547
Number of pages6
DOIs
Publication statusPublished - 2007
Event20th IEEE International Symposium on Computer-Based Medical Systems, CBMS'07 - Maribor, Slovenia
Duration: Jun 20 2007Jun 22 2007

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
ISSN (Print)1063-7125

Conference

Conference20th IEEE International Symposium on Computer-Based Medical Systems, CBMS'07
Country/TerritorySlovenia
CityMaribor
Period6/20/076/22/07

ASJC Scopus Subject Areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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