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Social media offer insights of patients' medical problems such as drug side effects and treatment failures. Patient reports of adverse drug events from social media have great potential to improve current practice of pharmacovigilance. However, extracting patient adverse drug event reports from social media continues to be an important challenge for health informatics research. In this study, we develop a research framework with advanced natural language processing techniques for integrated anddoi:10.1016/j.jbi.2015.10.011 pmid:26518315 fatcat:53nu3jrxfbdmxe2yqpaaqyrija