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首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >A temporal interestingness measure for drug interaction signal detection in post-marketing surveillance
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A temporal interestingness measure for drug interaction signal detection in post-marketing surveillance

机译：上市后监视中药物相互作用信号检测的时间兴趣度度量

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摘要

Drug-drug interactions (DDIs) can result in serious consequences, including death. Existing methods for identifying potential DDIs in post-marketing surveillance primarily rely on the FDA's (Food and Drug Administration) spontaneous reporting system. However, this system suffers from severe underreporting, which makes it difficult to timely collect enough valid cases for statistical analysis. In this paper, we study how to signal potential DDIs using patient electronic health data. Specifically, we focus on discovery of potential DDIs by analyzing the temporal relationships between the concurrent use of two drugs of interest and the occurrences of various symptoms using novel temporal association mining techniques we developed. A new interestingness measure called functional temporal interest was proposed to assess the degrees of temporal association between two drugs of interest and each symptom. The measure was employed to screen potential DDIs from 21,405 electronic patient cases retrieved from the Veterans Affairs Medical Center in Detroit, Michigan. The preliminary results indicate the usefulness of our method in finding potential DDIs for further analysis (e.g., epidemiology study) and investigation (e.g., case review) by drug safety professionals.
机译：药物相互作用（DDI）可能导致严重后果，包括死亡。在上市后监视中识别潜在DDI的现有方法主要依赖于FDA（食品和药物管理局）的自发报告系统。但是，此系统的报告严重不足，因此难以及时收集足够的有效案例进行统计分析。在本文中，我们研究了如何使用患者电子健康数据来发信号通知潜在的DDI。具体来说，我们通过使用我们开发的新型时间关联挖掘技术来分析两种感兴趣药物的同时使用与各种症状的发生之间的时间关系，从而专注于潜在DDI的发现。提出了一种新的趣味性测度，称为功能性时空兴趣，以评估两种所关注药物和每种症状之间的时间关联程度。该措施用于从密歇根州底特律的退伍军人事务医疗中心取回的21,405例电子病历中筛选潜在的DDI。初步结果表明，我们的方法在寻找潜在的DDI以便进行进一步的分析（例如流行病学研究）和药物安全专业人员的调查（例如案例审查）方面非常有用。

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