End-to-end relation extraction using lstms on sequences and tree structures M Miwa, M Bansal ACL2016, 2016 | 1480 | 2016 |
Using text mining for study identification in systematic reviews: a systematic review of current approaches A O’Mara-Eves, J Thomas, J McNaught, M Miwa, S Ananiadou Systematic reviews 4, 1-22, 2015 | 660 | 2015 |
Modeling joint entity and relation extraction with table representation M Miwa, Y Sasaki Proceedings of the 2014 conference on empirical methods in natural language …, 2014 | 400 | 2014 |
A neural layered model for nested named entity recognition M Ju, M Miwa, S Ananiadou Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 311 | 2018 |
Inter-sentence relation extraction with document-level graph convolutional neural network SK Sahu, F Christopoulou, M Miwa, S Ananiadou arXiv preprint arXiv:1906.04684, 2019 | 243 | 2019 |
Connecting the dots: Document-level neural relation extraction with edge-oriented graphs F Christopoulou, M Miwa, S Ananiadou arXiv preprint arXiv:1909.00228, 2019 | 241 | 2019 |
Event extraction with complex event classification using rich features M Miwa, R Sætre, JD Kim, J Tsujii Journal of bioinformatics and computational biology 8 (01), 131-146, 2010 | 227 | 2010 |
Reducing systematic review workload through certainty-based screening M Miwa, J Thomas, A O’Mara-Eves, S Ananiadou Journal of biomedical informatics 51, 242-253, 2014 | 210 | 2014 |
Deep exhaustive model for nested named entity recognition MG Sohrab, M Miwa Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 207 | 2018 |
Protein–protein interaction extraction by leveraging multiple kernels and parsers M Miwa, R Sætre, Y Miyao, J Tsujii International journal of medical informatics 78 (12), e39-e46, 2009 | 203 | 2009 |
Event extraction across multiple levels of biological organization S Pyysalo, T Ohta, M Miwa, HC Cho, J Tsujii, S Ananiadou Bioinformatics 28 (18), i575-i581, 2012 | 170 | 2012 |
Discovering and visualizing indirect associations between biomedical concepts Y Tsuruoka, M Miwa, K Hamamoto, J Tsujii, S Ananiadou Bioinformatics 27 (13), i111-i119, 2011 | 154 | 2011 |
Simple customization of recursive neural networks for semantic relation classification K Hashimoto, M Miwa, Y Tsuruoka, T Chikayama Proceedings of the 2013 conference on empirical methods in natural language …, 2013 | 144 | 2013 |
Topic detection using paragraph vectors to support active learning in systematic reviews K Hashimoto, G Kontonatsios, M Miwa, S Ananiadou Journal of biomedical informatics 62, 59-65, 2016 | 134 | 2016 |
A rich feature vector for protein-protein interaction extraction from multiple corpora M Miwa, R Sætre, Y Miyao, J Tsujii Proceedings of the 2009 conference on empirical methods in natural language …, 2009 | 134 | 2009 |
Word embedding-based antonym detection using thesauri and distributional information M Ono, M Miwa, Y Sasaki Proceedings of the 2015 Conference of the North American Chapter of the …, 2015 | 131 | 2015 |
Boosting automatic event extraction from the literature using domain adaptation and coreference resolution M Miwa, P Thompson, S Ananiadou Bioinformatics 28 (13), 1759-1765, 2012 | 128 | 2012 |
A walk-based model on entity graphs for relation extraction F Christopoulou, M Miwa, S Ananiadou arXiv preprint arXiv:1902.07023, 2019 | 116 | 2019 |
Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods F Christopoulou, TT Tran, SK Sahu, M Miwa, S Ananiadou Journal of the American Medical Informatics Association 27 (1), 39-46, 2020 | 101 | 2020 |
Entity-focused sentence simplification for relation extraction M Miwa, R Sætre, Y Miyao, J Tsujii Proceedings of the 23rd International Conference on Computational …, 2010 | 85 | 2010 |