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Combining Task Execution and Background Knowledge for the Verification of Medical Guidelines

Arjen Hommersom, Perry Groot, Peter Lucas, Michael Balser, Jonathan Schmitt

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.
published 2006 Proceedings of AI-2006, the 26th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence