NDLI: Application of fuzzy ontological reasoning in an implementation of medical guidelines

Content Provider	IEEE Xplore Digital Library
Author	Szwed, P.
Copyright Year	2013
Description	Author affiliation: AGH Univ. of Sci. & Technol., Kraków, Poland (Szwed, P.)
Abstract	In this paper we address two problems. The first pertains to implementation of medical guidelines in an e-health system supporting self-management of chronic diseases. The system allows patients to enter observed symptoms and measured parameters, then makes assessment of disease state and informs about necessary actions. We propose to formalize guidelines as sets of fuzzy rules. Fuzziness is introduced to cope with uncertainty resulting from self-observations bias, low quality of sensors and limited patients skills. The second problem is more general. It concerns the reuse of knowledge gathered in ontologies and an application of Semantic Web technologies to perform fuzzy inference. We show that, despite the fact that commonly used ontology languages and supporting tools are not intended to handle vagueness and uncertainty, they can be successfully integrated to represent and execute a set of fuzzy rules. The proposed method consists in refactoring a domain ontology, then introducing additional relations expressing fuzzy properties, encoding Mamdani fuzzy rules in SWRL language and executing them with use of Pellet OWL reasoner. We describe a fuzzy reasoning engine applying this approach and discuss translation of fuzzy rules to SWRL constructs taking as example a complete set of rules formalizing a medical guideline for asthma control assessment.
Sponsorship	IEEE Ind. Electron. Soc.
Starting Page	342
Ending Page	349
File Size	143999
Page Count	8
File Format	PDF
ISBN	9781467356350
ISSN	21582246
e-ISBN	9781467356374
DOI	10.1109/HSI.2013.6577845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-06
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy sets OWL Ontologies e-health systems Cognition medical guidelines Fuzzy reasoning ontology fuzzy reasoning Guidelines Diseases
Content Type	Text
Resource Type	Article

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