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Mining Risk Patterns in Medical Data by Jiuyong Li; Ada Wai-chee Fu; Hongxing He; Jie Chen; Huidong Jin; Damien McAullay; Graham Williams; Ross Sparks; Chris Kelman is a scholarly article available to read on EtoBox.

What is Mining Risk Patterns in Medical Data about?

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.

Author

Jiuyong Li; Ada Wai-chee Fu; Hongxing He; Jie Chen; Huidong Jin; Damien McAullay; Graham Williams; Ross Sparks; Chris Kelman

Publisher

ACM

Published

2005

Language

EN