Adverse Drug Extraction in Twitter Data Using Convolutional Neural Network
Liliya Akhtyamova, Mikhail Alexandrov, John Cardiff · 2017
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.