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2020 – today
- 2023
[c21]Simon Suster, Timothy Baldwin, Karin Verspoor
:
Promoting Fairness in Classification of Quality of Medical Evidence. BioNLP@ACL 2023: 413-426- [c20]Gleb Kuzmin, Artem Vazhentsev, Artem Shelmanov, Xudong Han, Simon Suster, Maxim Panov, Alexander Panchenko, Timothy Baldwin:
Uncertainty Estimation for Debiased Models: Does Fairness Hurt Reliability? IJCNLP (1) 2023: 744-770 - 2021
- [c19]Pieter Fivez, Simon Suster, Walter Daelemans:
Integrating Higher-Level Semantics into Robust Biomedical Name Representations. LOUHI@EACL 2021: 49-58 - [c18]Pieter Fivez, Simon Suster, Walter Daelemans:
Scalable Few-Shot Learning of Robust Biomedical Name Representations. BioNLP@NAACL-HLT 2021: 23-29 - [c17]Madhumita Sushil, Simon Suster, Walter Daelemans:
Are we there yet? Exploring clinical domain knowledge of BERT models. BioNLP@NAACL-HLT 2021: 41-53 - [c16]Madhumita Sushil, Simon Suster, Walter Daelemans:
Contextual explanation rules for neural clinical classifiers. BioNLP@NAACL-HLT 2021: 202-212 - [c15]Pieter Fivez, Simon Suster, Walter Daelemans:
Conceptual Grounding Constraints for Truly Robust Biomedical Name Representations. EACL 2021: 2440-2450 - [c14]Karin Verspoor, Simon Suster, Yulia Otmakhova, Shevon Mendis, Zenan Zhai, Biaoyan Fang, Jey Han Lau, Timothy Baldwin, Antonio Jimeno-Yepes, David Martínez:
Brief Description of COVID-SEE: The Scientific Evidence Explorer for COVID-19 Related Research. ECIR (2) 2021: 559-564 - [c13]Simon Suster, Pieter Fivez, Pietro Totis, Angelika Kimmig, Jesse Davis, Luc De Raedt, Walter Daelemans:
Mapping probability word problems to executable representations. EMNLP (1) 2021: 3627-3640 - [c12]Simon Suster, Karin Verspoor, Timothy Baldwin, Jey Han Lau, Antonio Jimeno-Yepes, David Martinez Iraola, Yulia Otmakhova:
Impact of detecting clinical trial elements in exploration of COVID-19 literature. ICHI 2021: 495-496 - [i14]Simon Suster, Karin Verspoor, Timothy Baldwin, Jey Han Lau, Antonio Jimeno-Yepes, David Martínez, Yulia Otmakhova:
Impact of detecting clinical trial elements in exploration of COVID-19 literature. CoRR abs/2105.12261 (2021) - 2020
- [c11]Yulia Otmakhova, Karin Verspoor, Timothy Baldwin, Simon Suster:
Improved Topic Representations of Medical Documents to Assist COVID-19 Literature Exploration. NLP4COVID@EMNLP 2020 - [i13]Madhumita Sushil, Simon Suster, Walter Daelemans:
Distilling neural networks into skipgram-level decision lists. CoRR abs/2005.07111 (2020) - [i12]Karin Verspoor, Simon Suster, Yulia Otmakhova, Shevon Mendis, Zenan Zhai, Biaoyan Fang, Jey Han Lau, Timothy Baldwin, Antonio Jimeno-Yepes, David Martínez:
COVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research. CoRR abs/2008.07880 (2020)
2010 – 2019
- 2019
- [j2]Stéphan Tulkens, Simon Suster, Walter Daelemans:
Unsupervised concept extraction from clinical text through semantic composition. J. Biomed. Informatics 91 (2019) - [i11]Simon Suster, Madhumita Sushil, Walter Daelemans:
Why can't memory networks read effectively? CoRR abs/1910.07350 (2019) - 2018
- [j1]Madhumita Sushil, Simon Suster, Kim Luyckx, Walter Daelemans:
Patient representation learning and interpretable evaluation using clinical notes. J. Biomed. Informatics 84: 103-113 (2018) - [c10]Simon Suster, Madhumita Sushil, Walter Daelemans:
Revisiting neural relation classification in clinical notes with external information. Louhi@EMNLP 2018: 22-28 - [c9]Madhumita Sushil, Simon Suster, Walter Daelemans:
Rule induction for global explanation of trained models. BlackboxNLP@EMNLP 2018: 82-97 - [c8]Simon Suster, Walter Daelemans:
CliCR: a Dataset of Clinical Case Reports for Machine Reading Comprehension. NAACL-HLT 2018: 1551-1563 - [i10]Simon Suster, Walter Daelemans:
CliCR: A Dataset of Clinical Case Reports for Machine Reading Comprehension. CoRR abs/1803.09720 (2018) - [i9]Madhumita Sushil, Simon Suster, Kim Luyckx, Walter Daelemans:
Patient representation learning and interpretable evaluation using clinical notes. CoRR abs/1807.01395 (2018) - [i8]Madhumita Sushil, Simon Suster, Walter Daelemans:
Rule induction for global explanation of trained models. CoRR abs/1808.09744 (2018) - 2017
- [c7]Simon Suster, Walter Daelemans:
Clinical Machine Comprehension Using Case Reports. AMIA 2017 - [c6]Pieter Fivez, Simon Suster, Walter Daelemans:
Unsupervised Context-Sensitive Spelling Correction of Clinical Free-Text with Word and Character N-Gram Embeddings. BioNLP 2017: 143-148 - [c5]Simon Suster, Stéphan Tulkens, Walter Daelemans:
A Short Review of Ethical Challenges in Clinical Natural Language Processing. EthNLP@EACL 2017: 80-87 - [i7]Simon Suster, Stéphan Tulkens, Walter Daelemans:
A Short Review of Ethical Challenges in Clinical Natural Language Processing. CoRR abs/1703.10090 (2017) - [i6]Pieter Fivez, Simon Suster, Walter Daelemans:
Unsupervised Context-Sensitive Spelling Correction of English and Dutch Clinical Free-Text with Word and Character N-Gram Embeddings. CoRR abs/1710.07045 (2017) - [i5]Madhumita Sushil, Simon Suster, Kim Luyckx, Walter Daelemans:
Unsupervised patient representations from clinical notes with interpretable classification decisions. CoRR abs/1711.05198 (2017) - 2016
- [c4]Stéphan Tulkens, Simon Suster, Walter Daelemans:
Using Distributed Representations to Disambiguate Biomedical and Clinical Concepts. BioNLP@ACL 2016: 77-82 - [c3]Simon Suster, Ivan Titov, Gertjan van Noord:
Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders. HLT-NAACL 2016: 1346-1356 - [i4]Simon Suster, Ivan Titov, Gertjan van Noord:
Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders. CoRR abs/1603.09128 (2016) - [i3]Stéphan Tulkens, Simon Suster, Walter Daelemans:
Using Distributed Representations to Disambiguate Biomedical and Clinical Concepts. CoRR abs/1608.05605 (2016) - 2015
- [c2]Manuela Hürlimann, Benno Weck, Esther van den Berg, Simon Suster, Malvina Nissim:
GLAD: Groningen Lightweight Authorship Detection. CLEF (Working Notes) 2015 - [i2]Simon Suster:
An investigation into language complexity of World-of-Warcraft game-external texts. CoRR abs/1502.02655 (2015) - [i1]Simon Suster, Gertjan van Noord, Ivan Titov:
Word Representations, Tree Models and Syntactic Functions. CoRR abs/1508.07709 (2015) - 2014
- [c1]Simon Suster, Gertjan van Noord:
From neighborhood to parenthood: the advantages of dependency representation over bigrams in Brown clustering. COLING 2014: 1382-1391
Coauthor Index
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