 Connection
Steven Bethard to Humans
This is a "connection" page, showing publications Steven Bethard has written about Humans.
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Connection Strength |
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0.050 |
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Xu D, Gopale M, Zhang J, Brown K, Begoli E, Bethard S. Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)-based ranking for concept normalization. J Am Med Inform Assoc. 2020 10 01; 27(10):1510-1519.
Score: 0.020
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Bethard S, Lu Z, Martin JH, Hunter L. Semantic role labeling for protein transport predicates. BMC Bioinformatics. 2008 Jun 11; 9:277.
Score: 0.009
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Lin C, Bethard S, Dligach D, Sadeque F, Savova G, Miller TA. Does BERT need domain adaptation for clinical negation detection? J Am Med Inform Assoc. 2020 04 01; 27(4):584-591.
Score: 0.005
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Miller T, Dligach D, Bethard S, Lin C, Savova G. Towards generalizable entity-centric clinical coreference resolution. J Biomed Inform. 2017 05; 69:251-258.
Score: 0.004
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Osborne JD, Wyatt M, Westfall AO, Willig J, Bethard S, Gordon G. Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning. J Am Med Inform Assoc. 2016 11; 23(6):1077-1084.
Score: 0.004
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Pathak J, Bailey KR, Beebe CE, Bethard S, Carrell DC, Chen PJ, Dligach D, Endle CM, Hart LA, Haug PJ, Huff SM, Kaggal VC, Li D, Liu H, Marchant K, Masanz J, Miller T, Oniki TA, Palmer M, Peterson KJ, Rea S, Savova GK, Stancl CR, Sohn S, Solbrig HR, Suesse DB, Tao C, Taylor DP, Westberg L, Wu S, Zhuo N, Chute CG. Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium. J Am Med Inform Assoc. 2013 Dec; 20(e2):e341-8.
Score: 0.003
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Dligach D, Bethard S, Becker L, Miller T, Savova GK. Discovering body site and severity modifiers in clinical texts. J Am Med Inform Assoc. 2014 May-Jun; 21(3):448-54.
Score: 0.003
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Savova G, Bethard S, Styler W, Martin J, Palmer M, Masanz J, Ward W. Towards temporal relation discovery from the clinical narrative. AMIA Annu Symp Proc. 2009 Nov 14; 2009:568-72.
Score: 0.002
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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