Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Algorithm and Care Pathway: Clinical Guidelines and Healthcare Processes
AIME '97 Proceedings of the 6th Conference on Artificial Intelligence in Medicine in Europe
Fuzzy Logic in Clinical Practice Decision Support Systems
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 5 - Volume 5
Appropriate choice of aggregation operators in fuzzy decision support systems
IEEE Transactions on Fuzzy Systems
Interval type-2 fuzzy logic for encoding clinical practice guidelines
Knowledge-Based Systems
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Computerized clinical guidelines can provide significant benefits in terms of health outcomes and costs, however, their effective computer implementation presents significant problems. Vagueness and ambiguity inherent in natural language (textual) clinical guidelines makes them problematic for formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. In care plan on-line (CPOL), an intranet-based chronic disease care planning system for general practitioners (GPs) in use in South Australia, we formally treat fuzziness in interpretation of quantitative data, formulation of recommendations and unequal importance of clinical indicators. We use expert judgment on cases, as well as direct estimates by experts, to optimize aggregation operators and treat heterogeneous combinations of conjunction and disjunction that are present in the natural language decision rules formulated by specialist teams.