Mining risk patterns in medical data
Paper
Paper/Presentation Title | Mining risk patterns in medical data |
---|---|
Presentation Type | Paper |
Authors | Li, 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) |
Editors | Grossman, R., Bayardo, R., Bennett, K. and Vaidya, J. |
Journal or Proceedings Title | Proceedings of 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD 2005) |
Number of Pages | 6 |
Year | 2005 |
Place of Publication | United States |
ISBN | 159593135X |
Digital Object Identifier (DOI) | https://doi.org/10.1145/1081870.1081971 |
Web Address (URL) of Paper | https://dl.acm.org/citation.cfm?doid=1081870.1081971 |
Conference/Event | 11th 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 |
Keywords | relative risk; rule; optimal risk pattern set; medical application |
ANZSRC Field of Research 2020 | 469999. 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 | Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. |
Byline Affiliations | Department of Mathematics and Computing |
Chinese University of Hong Kong, China | |
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0500/mining-risk-patterns-in-medical-data
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