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2017 28th International Workshop on Database and Expert Systems Applications (DEXA)最新文献

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Adverse Drug Extraction in Twitter Data Using Convolutional Neural Network 利用卷积神经网络提取Twitter数据中的不良药物
L. Akhtyamova, M. Alexandrov, J. Cardiff
The study of health-related topics on social media has become a useful tool for the early detection of the different adverse medical conditions. In particular, it concerns cases related to the treatment of mental diseases, as the effects of medications here often prove to be unpredictable. In our research, we use convolutional neural networks (CNN) with word2vec embedding to classify user comments on Twitter. The aim of the classification is to reveal adverse drug reactions of users. The results obtained are highly promising, showing the overall usefulness of neural network algorithms in this kind of tasks.
社交媒体上健康相关话题的研究已经成为早期发现不同不良医疗状况的有用工具。特别是,它涉及与精神疾病治疗有关的案件,因为在这里,药物的效果往往是不可预测的。在我们的研究中,我们使用卷积神经网络(CNN)与word2vec嵌入来对Twitter上的用户评论进行分类。分类的目的是揭示使用者的药物不良反应。结果显示神经网络算法在这类任务中的总体有效性。
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引用次数: 18
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2017 28th International Workshop on Database and Expert Systems Applications (DEXA)
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