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Clinical trials predicate subject eligibility on a diversity of criteria ranging from patient demographics to food allergies.
Measures of the amount of ecologic association between species
L. R. Dice · 1945
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A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries
W. Chapman, W. Bridewell, P. Hanbury, G. F. Cooper, and B. G. Buchanan · 2001
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Automated information extraction of key trial design elements from clinical trial publications
B. de Bruijn, S. Carini, S. Kiritchenko, J. Martin, and I. Sim · 2008
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Analysis of eligibility criteria complexity in clinical trials
J. Ross, S. Tu, S. Carini, and I. Sim · 2010
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Formal representation of eligibility criteria: a literature review
C. Weng, S. W. Tu, I. Sim, and R. Richesson · 2010
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A practical method for transforming free-text eligibility criteria into computable criteria
S. W. Tu, M. Peleg, S. Carini, M. Bobak, J. Ross, D. Rubin, and I. Sim · 2011
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EliXR: an approach to eligibility criteria extraction and representation
C. Weng, X. Wu, Z. Luo, M. R. Boland, D. Theodoratos, and S. B. Johnson · 2011
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Benchmarking ontologies: bigger or better?
L. Yao, A. Divoli, I. Mayzus, J. A. Evans, and A. Rzhetsky · 2011
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The ClinicalTrials.gov results database–update and key issues
D. A. Zarin, T. Tse, R. J. Williams, R. M. Califf, and N. C. Ide · 2011
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EliXR-TIME: A Temporal Knowledge Representation for Clinical Research Eligibility Criteria
M. R. Boland, S. W. Tu, S. Carini, I. Sim, and C. Weng · 2012
Cited alongside, same era.
A human-computer collaborative approach to identifying common data elements in clinical trial eligibility criteria
Z. Luo, R. Miotto, and C. Weng · 2013
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Unsuccessful trial accrual and human subjects protections: an empirical analysis of recently closed trials
B. Carlisle, J. Kimmelman, T. Ramsay, and N. MacKinnon · 2015
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EliIE: An open-source information extraction system for clinical trial eligibility criteria
T. Kang, S. Zhang, Y. Tang, G. Hruby, A. Rusanov, N. Elhadad, and C. Weng · 2017
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An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition
L. Luo, Z. Yang, P. Yang, Y. Zhang, L. Wang, H. Lin, and J. Wang · 2018
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Advances in pre-training distributed word representations
T. Mikolov, E. Grave, P. Bojanowski, C. Puhrsch, and A. Joulin · 2018
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Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition
Z. Zhai, D. Q. Nguyen, and K. Verspoor · 2018
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Information extraction applications for clinical trials: A survey
S. G. Alves, J. S. Costa, and J. Bernardino · 2019
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The Need for Clinical Trial Navigators
S. Gubar · 2019
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
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Automatic differentiation in pytorch
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, Z. DeVito, Z. Lin, A. Desmaison, L. Antiga, and A. Lerer · 2017
Cited alongside, same era.
The data gap in EHR for clinical research eligibility screening
A. Butler, W. Wei, C. Yuan, T. Kang, Y. Si, and C. Weng · 2018
Cited alongside, same era.
When will clinical trials finally reflect diversity?
T. Knepper and H. McLeod · 2018
Cited alongside, same era.
J. Lee, W. Yoon, S. Kim, D. Kim, S. Kim, C. H. So, and J. Kang · 2019
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Criteria2Query: a natural language interface to clinical databases for cohort definition
C. Yuan, P. B. Ryan, C. Ta, Y. Guo, Z. Li, J. Hardin, R. Makadia, P. Jin, N. Shang, T. Kang, and C. Weng · 2019
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