Minimum Message Length Segmentation
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
An Algorithm for Segmenting Categorical Time Series into Meaningful Episodes
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
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Australia has extensive administrative health data collected by Commonwealth and state agencies. Using a unique cleaned and linked administrative health dataset we address the problem of empirically defining episodes of care. An episode of care is a time interval containing medical services relating to a particular medical situation. In this paper the medical situation is a hospital admission. The medical services of interest are pathology tests, diagnostic imaging and non-invasive investigative procedures performed before or after the hospital admission, but 'associated' with the hospital admission. The task can be viewed as detecting a signal in a time series relating to a hospital admission, distinct from the background noise of on-going medical care. Our approach uses an ensemble (panel of experts) paradigm where we implement multiple agents (alternative predictive models) to separately estimate intervals and then choose a robust interval estimate using a voting scheme. The results have been used in a study for the Commonwealth Department of Health and Ageing.