Role of text mining in early identification of potential drug safety issues.
作者： Mei Liu , Yong Hu , Buzhou Tang
DOI: 10.1007/978-1-4939-0709-0_13
关键词: Medical record 、 Clinical trial 、 Pharmacovigilance 、 Risk analysis (engineering) 、 Pharmacology 、 Social media 、 Drug development 、 Computer science 、 Adverse effect 、 Variety (cybernetics) 、 Therapeutic effect 、 Drug 、 Identification (information)
摘要: Drugs are an important part of today's medicine, designed to treat, control, and prevent diseases; however, besides their therapeutic effects, drugs may also cause adverse effects that range from cosmetic severe morbidity mortality. To identify these potential drug safety issues early, surveillance must be conducted for each throughout its life cycle, development different phases clinical trials, continued after market approval. A major aim pharmacovigilance is the drug-event associations novel in nature, severity, and/or frequency. Currently, state-of-the-art approach signal detection through automated procedures by analyzing vast quantities data knowledge. There exists a variety resources task, many them textual require text analytics natural language processing derive high-quality information. This chapter focuses on utilization mining techniques identifying sources such as biomedical literature, consumer posts social media, narrative electronic medical records.
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