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Identification of Adverse Drug Reaction Mentions in Tweets - SMM4H Shared Task 2019

机译:推文中的药物不良反应提及识别-SMM4H Shared Task 2019

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Analyzing social media posts can offer insights into a wide range of topics that are commonly discussed online, providing valuable information for studying various health-related phenomena reported online. The outcome of this work can offer insights into phar-macovigilance research to monitor the adverse effects of medications. This research specifically looks into mentions of adverse drug reactions (ADRs) in Twitter data through the Social Media Mining for Health Applications (SMM4H) Shared Task 2019. Adverse drug reactions are undesired harmful effects which can arise from medication or other methods of treatment. The goal of this research is to build accurate models using natural language processing techniques to detect reports of adverse drug reactions in Twitter data and extract these words or phrases.
机译:分析社交媒体帖子可以提供对在线上通常讨论的广泛主题的见解,为研究在线报道的各种与健康相关的现象提供有价值的信息。这项工作的结果可以提供对药物不良警戒研究的见解,以监测药物的不良反应。这项研究特别关注了通过健康应用社交媒体挖掘(SMM4H)共享任务2019在Twitter数据中提到的药物不良反应(ADR)。药物不良反应是药物或其他治疗方法所产生的不良影响。这项研究的目的是使用自然语言处理技术建立准确的模型,以检测Twitter数据中药物不良反应的报告并提取这些单词或短语。

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