Mining clinical big data for drug safety: Detecting inadequate treatment with a DNA sequence alignment algorithm
| dc.rights.license | open | en_US |
| dc.contributor.author | LEDIEU, T. | |
| dc.contributor.author | BOUZILLE, G. | |
| dc.contributor.author | PLAISANT, C. | |
| hal.structure.identifier | Bordeaux population health [BPH] | |
| dc.contributor.author | THIESSARD, Frantz | |
| dc.contributor.author | POLARD, E. | |
| dc.contributor.author | CUGGIA, M. | |
| dc.date.accessioned | 2020-11-30T09:46:09Z | |
| dc.date.available | 2020-11-30T09:46:09Z | |
| dc.date.issued | 2018 | |
| dc.identifier.issn | 1942-597X (Electronic) 1559-4076 (Linking) | en_US |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/21251 | |
| dc.description.abstractEn | 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. | |
| dc.language.iso | EN | en_US |
| dc.subject.en | ERIAS | |
| dc.title.en | Mining clinical big data for drug safety: Detecting inadequate treatment with a DNA sequence alignment algorithm | |
| dc.title.alternative | AMIA Annu Symp Proc | en_US |
| dc.type | Article de revue | en_US |
| dc.subject.hal | Sciences du Vivant [q-bio]/Santé publique et épidémiologie | en_US |
| dc.identifier.pubmed | 30815181 | en_US |
| bordeaux.journal | AMIA ... Annual Symposium proceedings. AMIA Symposium | en_US |
| bordeaux.page | 1368-1376 | en_US |
| bordeaux.volume | 2018 | en_US |
| bordeaux.hal.laboratories | Bordeaux Population Health Research Center (BPH) - UMR 1219 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.team | ERIAS | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.inpress | non | en_US |
| hal.export | false | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=AMIA%20...%20Annual%20Symposium%20proceedings.%20AMIA%20Symposium&rft.date=2018&rft.volume=2018&rft.spage=1368-1376&rft.epage=1368-1376&rft.eissn=1942-597X%20(Electronic)%201559-4076%20(Linking)&rft.issn=1942-597X%20(Electronic)%201559-4076%20(Linking)&rft.au=LEDIEU,%20T.&BOUZILLE,%20G.&PLAISANT,%20C.&THIESSARD,%20Frantz&POLARD,%20E.&rft.genre=article |
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