Fuzzy Logic in Clinical Practice Decision Support Systems

Authors:
Gleb Beliakov
Affiliations:
-
Venue:
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 5 - Volume 5
Year:
2000

Citing 0
Cited 7

Development of intelligent planning system (INPLANS): an analysis of student's performance using fuzzy systems

AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Modeling and automation of diagnosis and treatment of diabetes

SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
An adaptive neuro-fuzzy approach to risk factor analysis of Salmonella Typhimurium infection

Applied Soft Computing
Hybrid approach for context-aware service discovery in healthcare domain

Journal of Computer and System Sciences
Fuzzy logic for decision support in chronic care

Artificial Intelligence in Medicine
Interval type-2 fuzzy logic for encoding clinical practice guidelines

Knowledge-Based Systems
Structural verification through similarity measures for fuzzy rule bases representing clinical guidelines

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS'2011: 2nd International Fuzzy Systems Symposium

Quantified Score

Hi-index	0.00

Visualization

Abstract

Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners.