LEDIEU, T.; BOUZILLE, G.; PLAISANT, C.; THIESSARD, Frantz; POLARD, E.; CUGGIA, M.

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AMIA ... Annual Symposium proceedings. AMIA Symposium. 2018, vol. 2018, p. 1368-1376

Résumé en anglais

Health 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.< Réduire

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https://oskar-bordeaux.fr/handle/20.500.12278/21251

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Bordeaux Population Health Research Center (BPH) - UMR 1219