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Text and Data Mining Techniques in Adverse Drug Reaction Detection

机译:药物不良反应检测中的文本和数据挖掘技术

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摘要

We review data mining and related computer science techniques that have been studied in the area of drug safety to identify signals of adverse drug reactions from different data sources, such as spontaneous reporting databases, electronic health records, and medical literature. Development of such techniques has become more crucial for public heath, especially with the growth of data repositories that include either reports of adverse drug reactions, which require fast processing for discovering signals of adverse reactions, or data sources that may contain such signals but require data or text mining techniques to discover them. In order to highlight the importance of contributions made by computer scientists in this area so far, we categorize and review the existing approaches, and most importantly, we identify areas where more research should be undertaken.
机译:我们回顾了在药物安全领域研究过的数据挖掘和相关计算机科学技术,以识别来自不同数据源(例如自发报告数据库,电子健康记录和医学文献)的药物不良反应信号。此类技术的开发对于公共卫生变得越来越重要,特别是随着数据库的增长,其中包括不良药物反应的报告(需要快速处理以发现不良反应的信号)或可能包含此类信号但需要数据的数据源或文本挖掘技术来发现它们。为了强调到目前为止计算机科学家在该领域做出的贡献的重要性,我们对现有方法进行了分类和审查,最重要的是,我们确定了需要进行更多研究的领域。

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