Handbook of theoretical computer science (vol. B)
Equality and Domain Closure in First-Order Databases
Journal of the ACM (JACM)
Safe and sound: artificial intelligence in hazardous applications
Safe and sound: artificial intelligence in hazardous applications
From Informal Knowledge to Formal Logic: A Realistic Case Study in Medical Protocols
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Interpreting procedures from descriptive guidelines
Journal of Biomedical Informatics
Plan management in the medical domain
AI Communications
The mondex challenge: machine checked proofs for an electronic purse
FM'06 Proceedings of the 14th international conference on Formal Methods
Artificial Intelligence in Medicine
Actions with Failures in Interval Temporal Logic
Computational Logic in Multi-Agent Systems
Checking the quality of clinical guidelines using automated reasoning tools
Theory and Practice of Logic Programming
Formal methods: Practice and experience
ACM Computing Surveys (CSUR)
A Hybrid Approach to Clinical Guideline and to Basic Medical Knowledge Conformance
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Authoring and verification of clinical guidelines: A model driven approach
Journal of Biomedical Informatics
Extracting qualitative knowledge from medical guidelines for clinical decision-support systems
KR4HC'09 Proceedings of the 2009 AIME international conference on Knowledge Representation for Health-Care: data, Processes and Guidelines
Supporting adaptive clinical treatment processes through recommendations
Computer Methods and Programs in Biomedicine
Engineering Applications of Artificial Intelligence
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The application of a medical guideline to the treatment of a patient's disease can be seen as the execution of tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a "network of tasks,” that is, as a sequence of steps that have a specific function or goal. In this paper, a novel methodology for verifying the quality of such guidelines is introduced. To investigate the quality of such guidelines, we propose to include medical background knowledge to task networks and to formalize criteria for good medical practice that a guideline should comply with. This framework was successfully applied to a guideline dealing with the management of diabetes mellitus type 2 by using KIV.