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Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia

Ng, Kee Siong; Shan, Y.; Murray, D.W.; Sutinen, A.; Scharwz, B.; Jeacocke, D.; Farrugia, J.


This paper describes our experience with applying data mining techniques to the problem of fraud detection in spatio-temporal health data in Medicare Australia. A modular framework that brings together disparate data mining techniques is adopted. Several generally applicable techniques for extracting features from spatial and temporal data are also discussed. The system was evaluated with input from domain experts and was found to achieve high hit rates. We also discuss some lessons drawn from...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Conference paper
Source: IEEE International Conference on Data Mining (ICDM 2010) proceedings


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