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Identifying Medication Abuse and Adverse Effects from Tweets:University of Michigan at #SMM4H 2020

机译:鉴定推文中的药物滥用和不利影响:密歇根大学#SMM4H 2020

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The team from the University of Michigan participated in three tasks in the Social Media Mining for Health Applications (#SMM4H) 2020 shared tasks - on detecting mentions of adverse effects (Task 2), extracting and normalizing them (Task 3), and detecting mentions of medication abuse (Task 4). Our approaches relied on a combination of traditional machine learning and deep learning models. On Tasks 2 and 4, our submitted runs performed at or above the task average.
机译:来自密歇根大学的团队参加了社交媒体挖掘的三个任务,用于健康应用(#SMM4H)2020共享任务 - 检测不利影响的提及(任务2),提取和归一化它们(任务3),并检测提及 药物滥用(任务4)。 我们的方法依赖于传统机器学习和深度学习模型的组合。 在任务2和4上,我们提交的运行在任务平均值或之上执行。

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