Discriminant chronicles mining: Application to care pathways analytics

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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Communication dans un congrès
Artificial Intelligence in Medicine, Jun 2017, Vienna, Austria. 2017, 16th Conference on Artificial Intelligence in Medicine. <http://aime17.aimedicine.info/>. <10.1007/978-3-319-59758-4₂6>
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https://hal.archives-ouvertes.fr/hal-01568929
Contributeur : Yann Dauxais <>
Soumis le : lundi 11 septembre 2017 - 09:55:46
Dernière modification le : mardi 19 septembre 2017 - 08:37:51

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Yann Dauxais, Thomas Guyet, David Gross-Amblard, André Happe. Discriminant chronicles mining: Application to care pathways analytics. Artificial Intelligence in Medicine, Jun 2017, Vienna, Austria. 2017, 16th Conference on Artificial Intelligence in Medicine. <http://aime17.aimedicine.info/>. <10.1007/978-3-319-59758-4₂6>. <hal-01568929>

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