Identifying potential adverse effects using the web: a new approach to medical hypothesis generation.
Identifying potential adverse effects using the web: a new approach to medical hypothesis generation.
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DOI：
10.1016/j.jbi.2011.07.005
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发表时间：
2011-12
影响因子：
4.5
通讯作者：
Holmes, John H.
中科院分区：
文献类型：
--
作者：
Benton, Adrian;Ungar, Lyle;Hill, Shawndra;Hennessy, Sean;Mao, Jun;Chung, Annie;Leonard, Charles E.;Holmes, John H.
医疗留言板是一种在线资源，具有特定条件的用户可以在其中交换信息，其中一些信息可能不会与医疗提供者共享。许多这些板包含大量的职位，并包含患者的意见和经验，这将是潜在的有用的临床医生和研究人员。我们提出了一种方法，能够收集医学留言板帖子的语料库，去识别语料库，并提取用户讨论的潜在药物不良反应的信息。使用乳腺癌留言板的帖子库，我们使用共现统计来识别药物事件对。然后，我们比较了他莫昔芬、阿那曲唑、阿司美坦和来曲唑包装标签上列出的药物事件对。在我们的系统识别的对中，75-80%记录在药物标签上。一些未记录的对可能代表以前未识别的药物不良反应。
Medical message boards are online resources where users with a particular condition exchange information, some of which they might not otherwise share with medical providers. Many of these boards contain a large number of posts and contain patient opinions and experiences that would be potentially useful to clinicians and researchers. We present an approach that is able to collect a corpus of medical message board posts, de-identify the corpus, and extract information on potential adverse drug effects discussed by users. Using a corpus of posts to breast cancer message boards, we identified drug event pairs using co-occurrence statistics. We then compared the identified drug event pairs with adverse effects listed on the package labels of tamoxifen, anastrozole, exemestane, and letrozole. Of the pairs identified by our system, 75–80% were documented on the drug labels. Some of the undocumented pairs may represent previously unidentified adverse drug effects.
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