document: Mining risk patterns in medical data In this paper , we discuss a problem of finding risk patterns in medical data . We define risk patterns by a statistical metric , relative risk , which has been widely used in epidemiological research . We characterise the problem of mining risk patterns as an optimal rule discovery problem . We study an anti-monotone property for mining optimal risk pattern sets and present an algorithm to make use of the property in risk pattern discovery . The method has been applied to a real world data set to find patterns associated with an allergic event for ACE inhibitors . The algorithm has generated some useful results for medical researchers .
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