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Extraction of potential adverse drug events from medical case reports
2012
Journal of Biomedical Semantics
The sheer amount of information about potential adverse drug events published in medical case reports pose major challenges for drug safety experts to perform timely monitoring. Efficient strategies for identification and extraction of information about potential adverse drug events from free-text resources are needed to support pharmacovigilance research and pharmaceutical decision making. Therefore, this work focusses on the adaptation of a machine learning-based system for the identification
doi:10.1186/2041-1480-3-15
pmid:23256479
pmcid:PMC3599676
fatcat:tlxygb4kfve4rclaf7eitp7j5y