Discriminant chronicles mining: Application to care pathways analytics
September 11, 2017 Β· Declared Dead Β· π Conference on Artificial Intelligence in Medicine in Europe
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Authors
Yann Dauxais, Thomas Guyet, David Gross-Amblard, AndrΓ© Happe
arXiv ID
1709.03309
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.DS
Citations
20
Venue
Conference on Artificial Intelligence in Medicine in Europe
Last Checked
4 months ago
Abstract
Pharmaco-epidemiology (PE) is the study of uses and effects of drugs in well defined populations. As medico-administrative databases cover a large part of the population, they have become very interesting to carry PE studies. Such databases provide longitudinal care pathways in real condition containing timestamped care events, especially drug deliveries. Temporal pattern mining becomes a strategic choice to gain valuable insights about drug uses. In this paper we propose DCM, a new discriminant temporal pattern mining algorithm. It extracts chronicle patterns that occur more in a studied population than in a control population. We present results on the identification of possible associations between hospitalizations for seizure and anti-epileptic drug switches in care pathway of epileptic patients.
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