AI Magazine
Introduction to special section on software testing
Communications of the ACM
A model for critiquing based on automated medical records
Computers and Biomedical Research
Proposals for a valid terminology in KBS validation
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Applying rule-based anomalies to KADS inference structures
Decision Support Systems - Eighth workshop on the validation and verification of knowledge-based systems
Validation, Verification, and Testing of Computer Software
ACM Computing Surveys (CSUR)
Representing Medical Protocols for Organizational Simulation: An Information-Processing Approach
Computational & Mathematical Organization Theory
Supporting Tools for Guideline Development and Dissemination
AIME '97 Proceedings of the 6th Conference on Artificial Intelligence in Medicine in Europe
AIME '97 Proceedings of the 6th Conference on Artificial Intelligence in Medicine in Europe
Artificial Intelligence in Medicine
Improving medical protocols by formal methods
Artificial Intelligence in Medicine
Authoring and verification of clinical guidelines: A model driven approach
Journal of Biomedical Informatics
Verification of temporal scheduling constraints in clinical practice guidelines
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
KETO: a knowledge editing tool for encoding condition --- action guidelines into clinical DSSs
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Using Recommendation to Support Adaptive Clinical Pathways
Journal of Medical Systems
A pattern-based knowledge editing system for building clinical Decision Support Systems
Knowledge-Based Systems
Journal of Biomedical Informatics
Methodological Review: Computer-interpretable clinical guidelines: A methodological review
Journal of Biomedical Informatics
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS'2011: 2nd International Fuzzy Systems Symposium
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As shown in numerous studies, a significant part of published clinical guidelines is tainted with different types of semantical errors that interfere with their practical application. The adaptation of generic guidelines, necessitated by circumstances such as resource limitations within the applying organization or unexpected events arising in the course of patient care, further promotes the introduction of defects. Still, most current approaches for the automation of clinical guidelines are lacking mechanisms, which check the overall correctness of their output. In the domain of software engineering in general and in the domain of knowledge-based systems (KBS) in particular, a common strategy to examine a system for potential defects consists in its verification. The focus of this work is to present an approach, which helps to ensure the semantical correctness of clinical guidelines in a three-step process. We use a particular guideline specification language called Asbru to demonstrate our verification mechanism. A scenario-based evaluation of our method is provided based on a guideline for the artificial ventilation of newborn infants. The described approach is kept sufficiently general in order to allow its application to several other guideline representation formats.