Open AccessDiscriminant chronicles mining: Application to care pathways analytics
Author(s) -
Yann Dauxais,
Thomas Guyet,
David Gross-Amblard,
André Happe
Publication year - 2017
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1007/978-3-319-59758-4₂6
Subject(s) - computer science , analytics , linear discriminant analysis , data science , artificial intelligence , data mining
International audiencePharmaco-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