Extraction of potential adverse drug events from medical case reports.
Extraction of potential adverse drug events from medical case reports.
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DOI：
10.1186/2041-1480-3-15
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发表时间：
2012-12-20
影响因子：
1.9
通讯作者：
Toldo L
中科院分区：
文献类型：
--
作者：
Gurulingappa H;Mateen-Rajput A;Toldo L
医学病例报告中发布的关于潜在药物不良事件的大量信息对药物安全专家进行及时监测构成了重大挑战。需要从自由文本资源中识别和提取潜在药物不良事件信息的有效策略，以支持药物警戒研究和药物决策。因此，这项工作的重点是调整基于机器学习的系统，以从MEDLINE病例报告中识别和提取潜在的药物不良事件关系。它依赖于使用本体驱动方法手动注释的高质量语料库。系统的定性评价显示出稳健的结果。一项从MEDLINE中提取大规模关系的实验提供了未在药物专论中报告的潜在药物不良事件。总体而言，这种方法为药物安全专业人员提供了一个可扩展的自动协助平台，以自动收集作为自由文本数据传输的潜在药物不良事件。
The sheer amount of information about potential adverse drug events published in medical case reports pose major challenges for drug safety experts to perform timely monitoring. Efficient strategies for identification and extraction of information about potential adverse drug events from free‐text resources are needed to support pharmacovigilance research and pharmaceutical decision making. Therefore, this work focusses on the adaptation of a machine learning‐based system for the identification and extraction of potential adverse drug event relations from MEDLINE case reports. It relies on a high quality corpus that was manually annotated using an ontology‐driven methodology. Qualitative evaluation of the system showed robust results. An experiment with large scale relation extraction from MEDLINE delivered under‐identified potential adverse drug events not reported in drug monographs. Overall, this approach provides a scalable auto‐assistance platform for drug safety professionals to automatically collect potential adverse drug events communicated as free‐text data.
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DOI：
10.1197/jamia.m3028
发表时间：
2009-05-01
影响因子：
6.4
作者：
Wang, Xiaoyan;Hripcsak, George;Friedman, Carol
通讯作者：
Friedman, Carol
影响因子：
4.5
作者：
Benton, Adrian;Ungar, Lyle;Hill, Shawndra;Hennessy, Sean;Mao, Jun;Chung, Annie;Leonard, Charles E.;Holmes, John H.
通讯作者：
Holmes, John H.
影响因子：
7.7
作者：
Henegar, Corneliu;Bousquet, Cedric;Jaulent, Marie-Christine
通讯作者：
Jaulent, Marie-Christine
影响因子：
9.9
作者：
Kuhn M;Campillos M;Letunic I;Jensen LJ;Bork P
通讯作者：
Bork P
影响因子：
4.5
作者：
van Mulligen, Erik M.;Fourrier-Reglat, Annie;Furlong, Laura I.
通讯作者：
Furlong, Laura I.