Department of Pharmaceutical and Drug Discovery, Faculty of Science, King Mongkut’s University of Technology Thonburi, Thailand
Research Article
Extraction of Drug-Drug Interactions Using Convolutional Neural Networks
Author(s): Puneet Souda*
Drug-drug interaction (DDI) extraction has long been a popular relation extraction
task in natural language processing (NLP). Modern support vector machines
(SVM) with a high number of manually set features are the foundation of most
DDI extraction methods. Convolutional neural networks (CNN), a reliable machine
learning technique that nearly never requires manually generated features, have
recently shown significant promise for a variety of NLP tasks. CNN should be used
for DDI extraction, which has never been looked at. A CNN-based technique for
DDI extraction was put forth. CNN is a good option for DDI extraction, as shown by
experiments done on the 2013 DDI Extraction challenge corpus. The CNN-based
DDI extraction approach outperforms the currently highest performing method by
69.75%, achieving a score of 69.75%.
Keywords
Drug-drug i.. View More»
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