Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering

An Hl7 Rim-Driven, Ontology-Based Approach to Healthcare Knowledge Base Development

Authors
Y.F. Zhang, P.F. Li, Y. Wang, J.S. Li
Corresponding Author
Y.F. Zhang
Available Online July 2015.
DOI
10.2991/aiie-15.2015.47How to use a DOI?
Keywords
HL7 RIM; ontology; knowledge base; clinical decision support
Abstract

The development of the core component of clinical decision support systems (CDSS), the knowledge base, has become a significant bottleneck in its successful application due to lack of effective knowledge representation models. To solve this problem, this paper presents a novel approach by developing a healthcare knowledge base using semantic technologies, of which the semantic healthcare knowledge ontology (SHKO) was constructed, based on HL7 reference information model (RIM), and the semantic healthcare expression repository (SHER) was built in Jena rule format and simple protocol and resource description framework query language (SPARQL). The proposed solution is validated in a case study of the management of patients with type 2 diabetes mellitus to demonstrate its technical feasibility.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-62520-70-7
ISSN
1951-6851
DOI
10.2991/aiie-15.2015.47How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Y.F. Zhang
AU  - P.F. Li
AU  - Y. Wang
AU  - J.S. Li
PY  - 2015/07
DA  - 2015/07
TI  - An Hl7 Rim-Driven, Ontology-Based Approach to Healthcare Knowledge Base Development
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 166
EP  - 169
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.47
DO  - 10.2991/aiie-15.2015.47
ID  - Zhang2015/07
ER  -