Mining consequence events in temporal health data
It is useful, sometimes crucial in medicine domain, to discover a temporal association or causal relationship among events. Such a mining problem is often challenging because 'consequence events' may not reliably occur after each trigger event of interest. This makes it difficult to apply existing temporal data mining techniques directly to real world problems. In this paper, we formalise the problem of mining consequence events of newly-introduced interventions. We combine the...[Show more]
|Collections||ANU Research Publications|
|Source:||Intelligent Data Analysis|
|01_Chen_Mining_consequence_events_in_2010.pdf||1.33 MB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.