Healtcare Trajectory Mining by Combining Multi-dimensional Component and Itemsets - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2013

Healtcare Trajectory Mining by Combining Multi-dimensional Component and Itemsets

Elias Egho
  • Function : Author
  • PersonId : 913967
Dino Ienco
Nicolas Jay
Amedeo Napoli
Pascal Poncelet
Catherine Quantin
Chedy Raïssi


Sequential pattern mining is an approach to extract corre- lations among temporal data. Many different methods were proposed to either enumerate sequences of set valued data (i.e., itemsets) or sequences containing multidimensional items. However, in many real-world scenar- ios, data sequences are described as events of both multi-dimensional and set valued informations. These rich heterogeneous descriptions can- not be exploited by traditional approaches. For example, in healthcare domain, hospitalizations are defined as sequences of multi-dimensional attributes (e.g. Hospital or Diagnosis) associated with sets of medical procedures (e.g. { Radiography, Appendectomy }). In this paper we pro- pose a new approach called MMISP (Mining Multi-dimensional-Itemset Sequential Patterns) to extract patterns from sequences including both multi-dimensional and set valued data. The novelties of the proposal lies in: (i) the way in which the data can be efficiently compressed; (ii) the ability to reuse a state-of-the-art sequential pattern mining algo- rithm and (iii) the extraction of new kind of patterns. We introduce as a case-study, experiments on real data aggregated from a regional health- care system and we point out the usefulness of the extracted patterns. Additional experiments on synthetic data highlights the efficiency and scalability of our approach.
Fichier principal
Vignette du fichier
NFMC2012.pdf (468.03 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

lirmm-00732661 , version 1 (16-09-2012)



Elias Egho, Dino Ienco, Nicolas Jay, Amedeo Napoli, Pascal Poncelet, et al.. Healtcare Trajectory Mining by Combining Multi-dimensional Component and Itemsets. NFMCP: New Frontiers in Mining Complex Patterns, Sep 2012, Bristol, United Kingdom. ⟨10.1007/978-3-642-37382-4_8⟩. ⟨lirmm-00732661⟩
745 View
798 Download



Gmail Mastodon Facebook X LinkedIn More