Steven Bethard, Ph.D.

2013-2016 Computer and Information Science University of Alabama, Birmingham, Birmingham, AL, United States 
 2016- School of Information University of Arizona, Tucson, AZ 
Natural Language Processing, Computational Linguistics, Machine Learning
"Steven Bethard"


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James H. Martin grad student 2007 CU Boulder
 (Finding event, temporal and causal structure in text: A machine learning approach.)
Tamara R. Sumner post-doc 2008-2008 CU Boulder (EduTree)
Dan Jurafsky post-doc 2009-2010 Stanford
Marie-Francine Moens post-doc 2010-2011 KU Leuven
Martha Palmer post-doc 2011-2013 CU Boulder (LinguisTree)


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Upendra Sapkota grad student 2014-2015 UAB
John David Osborne grad student 2014-2016 UAB
Quynh Thi Ngoc grad student 2012-2017 KU Leuven
Farig Sadeque grad student 2014-2019 University of Arizona
Vikas Yadav grad student 2016-2020 University of Arizona
Dongfang Xu grad student 2016-2021 University of Arizona
Zeyu Zhang grad student 2019-2023 University of Arizona
BETA: Related publications


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Laparra E, Bethard S, Miller TA. (2020) Rethinking domain adaptation for machine learning over clinical language. Jamia Open. 3: 146-150
Xu D, Gopale M, Zhang J, et al. (2020) Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)-based ranking for concept normalization. Journal of the American Medical Informatics Association : Jamia
Lin C, Bethard S, Dligach D, et al. (2020) Does BERT need domain adaptation for clinical negation detection? Journal of the American Medical Informatics Association : Jamia
González-López S, López-López A, Bethard S, et al. (2019) A Model for Identifying Steps in Undergraduate Thesis Methodology Research in Computing Science. 148: 17-24
Laparra E, Xu D, Bethard S. (2018) From Characters to Time Intervals: New Paradigms for Evaluation and Neural Parsing of Time Normalizations. Transactions of the Association For Computational Linguistics. 6: 343-356
Xu D, Yadav V, Bethard S. (2018) UArizona at the MADE1.0 NLP Challenge. Proceedings of Machine Learning Research. 90: 57-65
Osborne JD, Neu MB, Danila MI, et al. (2018) CUILESS2016: a clinical corpus applying compositional normalization of text mentions. Journal of Biomedical Semantics. 9: 2
Sadeque F, Xu D, Bethard S. (2017) UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection. Ceur Workshop Proceedings. 1866
Miller T, Dligach D, Bethard S, et al. (2017) Towards Generalizable Entity-Centric Clinical Coreference Resolution. Journal of Biomedical Informatics
Osborne JD, Wyatt M, Westfall AO, et al. (2016) Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning. Journal of the American Medical Informatics Association : Jamia
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