Using Formal Concept Analysis for mining and interpreting patient flows within a healthcare network

Nicolas Jay (1) , François Kohler (2) , Amedeo Napoli (1)

1 ORPAILLEUR - Knowledge representation, reasonning
2 SPI-EAO - Santé Publique, Information médicale et Enseignement multimédia Assisté par Ordinateur

This paper presents an original experiment based on frequent itemset search and lattice based classification. This work focuses on the ability of iceberg-lattices to discover and represent flows of patient within a healthcare network. We give examples of analysis of real medical data showing how Formal Concept Analysis techniques can be helpful in the interpretation step of the knowledge discovery in databases process. This combined approach has been successfully used to assist public health managers in designing healthcare networks and planning medical resources.

Mots clés: Formal Concept Analysis; frequent itemsets; network

Domaines: Intelligence artificielle [cs.AI]; Santé publique et épidémiologie

Nicolas Jay, François Kohler, Amedeo Napoli. Using Formal Concept Analysis for mining and interpreting patient flows within a healthcare network. Fourth International Conference on Concept Lattices and Their Applications - CLA 2006, Oct 2006, Hammamet, Tunisia. ⟨10.1007/978-3-540-78921-5_19⟩. ⟨inria-00109863⟩