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Tytuł:
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A Comparative Study of the Arden Syntax and GDL Clinical Knowledge Representation Languages.
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Autorzy:
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de Bruin JS; Institute eHealth, FH Joanneum University of Applied Sciences GmbH, Graz, Austria.
Chen R; Cambio Healthcare Systems, Stockholm, Sweden.; Health Informatics Centre, LIME, Karolinska Institute, Solna, Sweden.
Rappelsberger A; Section for Artificial Intelligence and Decision Support, Medical University of Vienna, Vienna, Austria.
Adlassnig KP; Section for Artificial Intelligence and Decision Support, Medical University of Vienna, Vienna, Austria.; Medexter Healthcare GmbH, Vienna, Austria.
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Źródło:
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Studies in health technology and informatics [Stud Health Technol Inform] 2020 Jun 26; Vol. 272, pp. 187-190.
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Typ publikacji:
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Comparative Study; Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: Amsterdam ; Washington, DC : IOS Press, 1991-
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MeSH Terms:
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Decision Support Systems, Clinical*
Programming Languages*
Artificial Intelligence ; Language
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Contributed Indexing:
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Keywords: Arden Syntax; Clinical; Decision Support Systems; Guideline Definition Language
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Entry Date(s):
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Date Created: 20200702 Date Completed: 20200714 Latest Revision: 20200714
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Update Code:
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20240105
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DOI:
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10.3233/SHTI200525
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PMID:
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32604632
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The expressiveness of a medical knowledge representation language has significant impact on the effectiveness of a knowledge-based clinical decision support system. We assess the expressiveness of two such languages, Arden Syntax and the Guideline Definition Language. Using data extracted from both languages' specifications, we quantify expressiveness by means of language syntax and the number of supported operators. Preliminary results show that Arden Syntax is a more dynamic standard, having better readability and a higher number and more diverse operators than GDL. In contrast, GDL is a more rigid language that utilizes an underlying data model specification in the openEHR framework.
