Cognitive fuzzy modeling for enhanced risk assessment in a health care institution

dc.contributor.author	Smith E.	en
dc.contributor.author	Eloff J.	en
dc.date.accessioned	2012-11-01T16:31:39Z
dc.date.available	2012-11-01T16:31:39Z
dc.date.issued	2000	en
dc.identifier.citation	IEEE Intelligent Systems and Their Applications	en
dc.identifier.citation	15	en
dc.identifier.citation	2	en
dc.identifier.issn	8859000	en
dc.identifier.uri	http://hdl.handle.net/10500/7515
dc.description.abstract	A cognitive fuzzy-modeling approach is proposed for risk assessment in health care institutions, building on fuzzy logic's great potential in dealing with vague information and human common sense and intuition. This cognitive fuzzy approach is unique because it uses both the fuzzy cognitive map (FCM) and the fuzzy-rule-based techniques to calculate the IT risk value linked to a phase in a specific patient route. The advantage of using these techniques together is that it takes into account intuitive human observation, which forms the basis of any risk assessment, and also accounts for the vagueness regarding patient information and risks when calculating a phase's risk level in a typical patient route.	en
dc.language.iso	en	en
dc.publisher	IEEE, Piscataway, NJ, United States	en
dc.subject	Cognitive systems; Health care; Information technology; Mathematical models; Risk assessment; Cognitive fuzzy maps (CFM); Fuzzy sets	en
dc.title	Cognitive fuzzy modeling for enhanced risk assessment in a health care institution	en
dc.type	Article	en