NDLI: Incoporating Data Mining Applications into Clinical Guildelines

Content Provider	IEEE Xplore Digital Library
Author	Kazemzadeh, R.S. Sartipi, K.
Copyright Year	2006
Description	Author affiliation: Dept. of Comput. & Software, McMaster Univ., Hamilton, Ont. (Kazemzadeh, R.S.; Sartipi, K.)
Abstract	Computer based clinical guidelines have been developed to help caregivers in practicing medicine. GLIF3 (Guideline Interchange Format 3) is one of several standards that specify the structure for defining guideline models. The decision making steps within the GLIF3 guidelines are limited to evaluation of basic logic expressions. On the other hand, data mining analyses aim at building descriptive or predictive mining models that contain valuable knowledge. However, this knowledge can not be represented using the current guideline specification standards. In this paper, we focus on encoding and sharing the results obtained from a data mining study in the context of clinical care and hence to make it available at the point of care. For this purpose, we investigate available standards to encode the mining results in an interoperable manner and then elaborate on how to incorporate them in the context of guideline-based clinical decision support systems, and in particular GLIF3 models. Finally, we demonstrate the proposed approach using a developed prototype tool for modeling and execution of knowledge-assisted guideline
Starting Page	321
Ending Page	328
File Size	331188
Page Count	8
File Format	PDF
ISBN	0769525171
ISSN	10637125
DOI	10.1109/CBMS.2006.99
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Guidelines Application software Decision making Logic Data analysis Buildings Predictive models Encoding Decision support systems GLIF. Data Mining Knowledge Management Healthcare Informatics Clinical Decision Support Clinical Guideline
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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