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Mining clinical big data for drug safety: Detecting inadequate treatment with a DNA sequence alignment algorithm

dc.rights.licenseopenen_US
dc.contributor.authorLEDIEU, T.
dc.contributor.authorBOUZILLE, G.
dc.contributor.authorPLAISANT, C.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorTHIESSARD, Frantz
dc.contributor.authorPOLARD, E.
dc.contributor.authorCUGGIA, M.
dc.date.accessioned2020-11-30T09:46:09Z
dc.date.available2020-11-30T09:46:09Z
dc.date.issued2018
dc.identifier.issn1942-597X (Electronic) 1559-4076 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/21251
dc.description.abstractEnHealth data mining can bring valuable information for drug safety activities. We developed a visual analytics tool to find specific clinical event sequences within the data contained in a clinical data warehouse. To this aim, we adapted the Smith-Waterman DNA sequence alignment algorithm to retrieve clinical event sequences with a temporal pattern from the electronic health records included in a clinical data warehouse. A web interface facilitates interactive query specification and result visualization. We describe the adaptation of the Smith-Waterman algorithm, and the implemented user interface. The evaluation with pharmacovigilance use cases involved the detection of inadequate treatment decisions in patient sequences. The precision and recall results (F-measure = 0.87) suggest that our adaptation of the Smith-Waterman-based algorithm is well-suited for this type of pharmacovigilance activities. The user interface allowed the rapid identification of cases of inadequate treatment.
dc.language.isoENen_US
dc.subject.enERIAS
dc.title.enMining clinical big data for drug safety: Detecting inadequate treatment with a DNA sequence alignment algorithm
dc.title.alternativeAMIA Annu Symp Procen_US
dc.typeArticle de revueen_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed30815181en_US
bordeaux.journalAMIA ... Annual Symposium proceedings. AMIA Symposiumen_US
bordeaux.page1368-1376en_US
bordeaux.volume2018en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - U1219en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamERIASen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.exportfalse
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