Varieties of knowledge elicitation techniques
International Journal of Human-Computer Studies
Ontological Engineering
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Jena: implementing the semantic web recommendations
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Journal of Biomedical Informatics
Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics)
Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics)
Editorial: Hybrid intelligent algorithms and applications
Information Sciences: an International Journal
Knowledge-based verification of clinical guidelines by detection of anomalies
Artificial Intelligence in Medicine
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Clinical practice guidelines are expected to promote more consistent, effective, and efficient medical practices, especially if implemented in clinical Decision Support Systems (DSSs). One prerequisite for the broad acceptance of clinical DSSs and their efficient application to medical settings is the guarantee of a high level of upgradability and maintainability. In this respect, this paper proposes KETO (Knowledge Editing TOol), a user-friendly tool to guide and assist the editing and formalization of condition-action clinical recommendations into a hybrid Knowledge Base (KB), made of if-then rules built on the top of ontological vocabularies, to be then used in a clinical DSS. The tool aims at: i) synergistically combining multiple knowledge representation techniques for building efficient DSSs able to deal with different clinical problems; ii) reducing the complexity of the formalization process, by enabling the creation and automatic encoding into machine executable languages of hybrid KBs that could be functional in the context of clinical DSSs.