A Hybrid Approach to the Verification of Computer Interpretable Guidelines

L. Anselma*, A. Bottrighi, L. Giordano, A.J. Hommersom, G. Molino, S. Montani, P. Terenziani, M. Torchio

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review


Computer Interpretable Guidelines (CIGs) are assuming a major role in the medical area, in order to enhance the quality of medical assistance by providing physicians with evidence-based recommendations. However, the complexity of CIGs (which may contain hundreds of related clinical activities) demands for a verification process, aimed at assuring that a CIG satisfies several different types of properties (e.g., verification of the CIG correctness with respect to several criteria). Verification is a demanding task, which may be enhanced through the adoption of advanced Artificial Intelligence techniques. In this paper, we propose a general and hybrid approach to address such a task, suggesting that, given the heterogeneous character of the knowledge in CIGs, different forms of verification should be supported, through the adoption of proper (and different) methodologies.
Original languageEnglish
Title of host publicationFoundations of Biomedical Knowledge Representation
Subtitle of host publicationMethods and Applications
EditorsArjen Hommersom, Peter Lucas
Place of PublicationCham
PublisherSpringer International Publishing
Number of pages29
ISBN (Electronic)9783319280073
ISBN (Print)9783319280066
Publication statusPublished - 2015

Publication series

SeriesLecture Notes in Computer Science
SeriesLecture Notes in Artificial Intelligence (subseries)


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