Mining risk patterns in medical data

Paper

Li, Jiuyong, Fu, Ada Wai-Chee, He, Hongxing, Chen, Jie, Jin, Huidong, McAullay, Damien, Williams, Graham, Sparks, Ross and Kelman, Chris. 2005. "Mining risk patterns in medical data." Grossman, R., Bayardo, R., Bennett, K. and Vaidya, J. (ed.) 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2005). Chicago, United States 21 - 24 Aug 2005 United States. https://doi.org/10.1145/1081870.1081971
Paper/Presentation Title

Mining risk patterns in medical data

Presentation TypePaper
AuthorsLi, Jiuyong (Author), Fu, Ada Wai-Chee (Author), He, Hongxing (Author), Chen, Jie (Author), Jin, Huidong (Author), McAullay, Damien (Author), Williams, Graham (Author), Sparks, Ross (Author) and Kelman, Chris (Author)
EditorsGrossman, R., Bayardo, R., Bennett, K. and Vaidya, J.
Journal or Proceedings TitleProceedings of 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD 2005)
Number of Pages6
Year2005
Place of PublicationUnited States
ISBN159593135X
Digital Object Identifier (DOI)https://doi.org/10.1145/1081870.1081971
Web Address (URL) of Paperhttps://dl.acm.org/citation.cfm?doid=1081870.1081971
Conference/Event11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2005)
Event Details
11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2005)
Event Date
21 to end of 24 Aug 2005
Event Location
Chicago, United States
Abstract

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.

Keywordsrelative risk; rule; optimal risk pattern set; medical application
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
420399. Health services and systems not elsewhere classified
461399. Theory of computation not elsewhere classified
Public Notes

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Byline AffiliationsDepartment of Mathematics and Computing
Chinese University of Hong Kong, China
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
Institution of OriginUniversity of Southern Queensland
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