Discovering associations between adverse drug events using pattern structures and ontologies.

Journal: Journal of biomedical semantics
Published Date: Aug 22, 2017

Abstract

BACKGROUND: Patient data, such as electronic health records or adverse event reporting systems, constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequently associated ADEs in subgroups of patients.

Authors

  • Gabin Personeni
    LORIA (CNRS, Inria NGE, Université de Lorraine), Campus Scientifique, Vandœuvre-lès-Nancy, F-54506, France. gabin.personeni@loria.fr.
  • Emmanuel Bresso
    LORIA (CNRS, Inria NGE, Université de Lorraine), Campus Scientifique, Vandœuvre-lès-Nancy, F-54506, France.
  • Marie-Dominique Devignes
    LORIA (CNRS, Inria NGE, Université de Lorraine), Campus Scientifique, Vandœuvre-lès-Nancy, F-54506, France.
  • Michel Dumontier
    Stanford University, Stanford, CA USA.
  • Malika Smaïl-Tabbone
    LORIA (CNRS, Inria NGE, Université de Lorraine), Campus Scientifique, Vandœuvre-lès-Nancy, F-54506, France.
  • Adrien Coulet
    LORIA (CNRS, Inria Nancy-Grand Est, University of Lorraine), Campus Scientifique, Nancy, France. adrien.coulet@loria.fr.

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