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Comment
. 2013 May;20(3):591.
doi: 10.1136/amiajnl-2012-001603. Epub 2013 Jan 30.

Response to 'Use of an algorithm for identifying hidden drug-drug interactions in adverse event reports' by Gooden et al

Nicholas P Tatonetti, Joshua C Denny, Russ B Altman
Comment

Response to 'Use of an algorithm for identifying hidden drug-drug interactions in adverse event reports' by Gooden et al

Nicholas P Tatonetti et al. J Am Med Inform Assoc. 2013 May.
No abstract available

Keywords: Clinical Evaluation; Data Mining; Drug Interactions.

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Comment on

References

    1. Gooden KM, Pan X, Kawabata H, et al. Use of an algorithm for identifying hidden drug–drug interactions in adverse event reports. J Am Med Inform Assoc 2013;20:590. - PMC - PubMed
    1. Tatonetti NP, Fernald GH, Altman RB. A novel signal detection algorithm for identifying hidden drug–drug interactions in adverse event reports. J Am Med Inform Assoc 2012;19:79–85 - PMC - PubMed
    1. Tatonetti NP, Denny JC, Murphy SN, et al. Detecting drug interactions from adverse-event reports: interaction between paroxetine and pravastatin increases blood glucose levels. Clin Pharmacol Ther 2011;90:133–42 - PMC - PubMed
    1. Ritchie MD, Denny JC, Crawford DC, et al. Robust replication of genotype–phenotype associations across multiple diseases in an electronic medical record. Am J Hum Genet 2010;86:560–72 - PMC - PubMed
    1. Kho AN, Hayes MG, Rasmussen-Torvik L, et al. Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study. J Am Med Inform Assoc 2012;19:212–18 - PMC - PubMed

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