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.

A hybrid approach to the verification of computer interpretable guidelines

ANSELMA, LUCA;
2015

Abstract

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.
Foundations of Biomedical Knowledge Representation
Springer Verlag
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9521
287
315
978-3-319-28006-6
978-3-319-28007-3
978-3-319-28006-6
978-3-319-28007-3
http://springerlink.com/content/0302-9743/copyright/2005/
Clinical guidelines, artificial intelligence
Anselma, Luca; Bottrighi, Alessio; Giordano, Laura; Hommersom, Arjen; Molino, Gianpaolo; Montani, Stefania; Terenziani, Paolo; Torchio, Mauro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1621043
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