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Novel Data-Mining Methodologies for Adverse Drug Event Discovery and Analysis

期刊

CLINICAL PHARMACOLOGY & THERAPEUTICS
卷 91, 期 6, 页码 1010-1021

出版社

WILEY
DOI: 10.1038/clpt.2012.50

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资金

  1. National Library of Medicine [1R01LM010016, 3R01LM010016-01S1, 3R01LM010016-02S1, 5T15-LM007079-19(HS)]
  2. National Center for Biomedical Ontology [U54-HG004028]
  3. i2b2 National Center for Biomedical Computing [2U54LM008748]

向作者/读者索取更多资源

An important goal of the health system is to identify new adverse drug events (ADEs) in the postapproval period. Data-mining methods that can transform data into meaningful knowledge to inform patient safety have proven essential for this purpose. New opportunities have emerged to harness data sources that have not been used within the traditional framework. This article provides an overview of recent methodological innovations and data sources used to support ADE discovery and analysis.

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