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
Plan management in the medical domain
AI Communications
Formalising medical quality indicators to improve guidelines
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
Guideline-based careflow systems
Artificial Intelligence in Medicine
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The use of a medical guideline can be seen as the execution of computational 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', i.e., as a number of steps that have a specific function or goal. To investigate the quality of such guidelines we propose a formalization of criteria for good practice medicine a guideline should comply to. We use this theory in conjunction with medical background knowledge to verify the quality of a guideline dealing with diabetes mellitus type 2 using the interactive theorem prover KIV. Verification using task execution and background knowledge is a novel approach to quality checking of medical guidelines.