TITLE

Detecting adverse drug events through data mining

AUTHOR(S)
GLASGOW, JUSTIN M.; KABOLI, PETER J.
PUB. DATE
February 2010
SOURCE
American Journal of Health-System Pharmacy;2/15/2010, Vol. 67 Issue 4, p317
SOURCE TYPE
Academic Journal
DOC. TYPE
Opinion
ABSTRACT
The article presents author's view on the detection of adverse drug events (ADE) through data mining. He discusses the questions raised by the review of medical records and gathering information on ADEs from other information sources. He also discusses the role of automated systems to detect ADEs. He explains that data mining is a way to uncover hidden patterns that lead to knowledge for strategic decision making. He explains several data mining tools including neural networks and decision trees.
ACCESSION #
47924167

 

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