Identifying Adverse Drug Events in Observational Medical Data

Adverse drug events (ADEs) are a grave problem facing medical care. The Food
and Drug Administration places ADEs as the fourth-leading cause of mortality
in the U.S., where they harm more than two million people and cost $136
billion in additional care each year. Researchers have responded by
developing computational versions of epidemiological study designs and
analyses, but machine learning techniques have not yet been widely applied.


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