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One of the most considerable functions in a hospital's infection control program is the surveillance of antibiotic resistance. Several traditional methods used to measure it do not provide adequate and promising results for further analysis. Data mining techniques, such as the association rules, have been used in the past and successfully led to discovering interesting patterns in public health data. In this work, we present the architecture of a novel framework which integrates data fromdoi:10.1109/cbms.2007.8 dblp:conf/cbms/GiannopoulouKPPVV07 fatcat:jrlfysd3o5btrca75fesskvu5y