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Conference Papers Year : 2016

Discovering ADE associations from EHRs using pattern structures and ontologies

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Abstract

Patient Electronic Health Records (EHRs) constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequently associated ADEs in subgroups of patients. Because ADEs have complex manifestations, we use formal concept analysis and its pattern structures, a mathematical framework that allows generalization, while taking into account domain knowledge formalized in medical ontologies. Results obtained with three different settings show that this approach is flexible and allows extraction of association rules at various levels of generalization.
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Dates and versions

hal-01369448 , version 1 (21-09-2016)

Identifiers

  • HAL Id : hal-01369448 , version 1

Cite

Gabin Personeni, Marie-Dominique Devignes, Michel Dumontier, Malika Smaïl-Tabbone, Adrien Coulet. Discovering ADE associations from EHRs using pattern structures and ontologies. Phenotype Day, Bio-Ontologies SIG, ISMB, Jul 2016, Orlando, United States. ⟨hal-01369448⟩
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