Detection of Infectious Outbreaks in Hospitals through Incremental Clustering
This paper highlights the shortcomings of current systems of nosocomial infection control and shows how techniques borrowed from statistics and Artificial Intelligence, in particular clustering, can be used effectively to enhance these systems beyond confirmation and into the more important realms of detection and prediction. A tool called HIC and examined in collaboration with the Cardiff Public Health Laboratory is presented. Preliminary experiments with the system demonstrate promise. In particular, the system was able to uncover a previously undiscovered cross-infection incident.
KeywordsNosocomial Infection Public Health Laboratory Incremental Cluster Expansion Rule Symbolic Comparison
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