A retrospective evaluation of a data mining approach to aid finding new adverse drug reaction signals in the WHO international database.
about
Identifying plausible adverse drug reactions using knowledge extracted from the literatureComparison of two drug safety signals in a pharmacovigilance data mining framework.Data mining of the public version of the FDA Adverse Event Reporting SystemCommonality of drug-associated adverse events detected by 4 commonly used data mining algorithms.Association of statin use with sleep disturbances: data mining of a spontaneous reporting database and a prescription database.Pediatric drug safety signal detection: a new drug-event reference set for performance testing of data-mining methods and systems.Application of data mining techniques in pharmacovigilance.Early postmarketing drug safety surveillance: data mining points to consider.Application of an empiric Bayesian data mining algorithm to reports of pancreatitis associated with atypical antipsychotics.Potential utility of data-mining algorithms for early detection of potentially fatal/disabling adverse drug reactions: a retrospective evaluation.The role of data mining in pharmacovigilance.Data mining in spontaneous reports.Pharmacovigilance data mining with methods based on false discovery rates: a comparative simulation study.A computerized system for detecting signals due to drug-drug interactions in spontaneous reporting systems.Improving reporting of adverse drug reactions: Systematic review.Ability of nafamostat mesilate to prolong filter patency during continuous renal replacement therapy in patients at high risk of bleeding: a randomized controlled study.A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions.A brief primer on automated signal detection.A drug-adverse event extraction algorithm to support pharmacovigilance knowledge mining from PubMed citationsComparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records.Effect of consumer reporting on signal detection: using disproportionality analysis.Database size and power to detect safety signals in pharmacovigilance.The application of knowledge discovery in databases to post-marketing drug safety: example of the WHO database.Rhabdomyolysis a result of azithromycin and statins: an unrecognized interactionSignal Detection of Imipenem Compared to Other Drugs from Korea Adverse Event Reporting System DatabaseDefining a reference set to support methodological research in drug safety.Clustering WHO-ART terms using semantic distance and machine learning algorithms.Sequence Symmetry Analysis as a Signal Detection Tool for Potential Heart Failure Adverse Events in an Administrative Claims Database.Reducing the computational footprint for real-time BCPNN learning.Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload.Detecting drug-herbal interaction using a spontaneous reporting system database: an example with benzylpenicillin and qingkailing injection.Exploration of statistical shrinkage parameters of disproportionality methods in spontaneous reporting system of China.Comparison of statistical signal detection methods within and across spontaneous reporting databases.Identifying adverse events of vaccines using a Bayesian method of medically guided information sharing.A reference standard for evaluation of methods for drug safety signal detection using electronic healthcare record databases.Thrombotic events associated with C1 esterase inhibitor products in patients with hereditary angioedema: investigation from the United States Food and Drug Administration adverse event reporting system database.Reporting of adverse events following immunizations in Ghana - Using disproportionality analysis reporting ratios.Assessing performance of sequential analysis methods for active drug safety surveillance using observational data.Early detection of pharmacovigilance signals with automated methods based on false discovery rates: a comparative study.Clindamycin hydrochloride and clindamycin phosphate: two drugs or one? A retrospective analysis of a spontaneous reporting system.
P2860
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P2860
A retrospective evaluation of a data mining approach to aid finding new adverse drug reaction signals in the WHO international database.
description
2000 nî lūn-bûn
@nan
2000 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2000 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2000年の論文
@ja
2000年論文
@yue
2000年論文
@zh-hant
2000年論文
@zh-hk
2000年論文
@zh-mo
2000年論文
@zh-tw
2000年论文
@wuu
name
A retrospective evaluation of ...... he WHO international database.
@ast
A retrospective evaluation of ...... he WHO international database.
@en
type
label
A retrospective evaluation of ...... he WHO international database.
@ast
A retrospective evaluation of ...... he WHO international database.
@en
prefLabel
A retrospective evaluation of ...... he WHO international database.
@ast
A retrospective evaluation of ...... he WHO international database.
@en
P2093
P1433
P1476
A retrospective evaluation of ...... he WHO international database.
@en
P2093
P304
P356
10.2165/00002018-200023060-00004
P577
2000-12-01T00:00:00Z
P5875
P6179
1001132281