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Haystacks and hypotheses.

, , and . ASIST, volume 40 of Proc. Assoc. Inf. Sci. Technol., page 59-64. Wiley, (2003)

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NRC-Canada at SMM4H Shared Task: Classifying Tweets Mentioning Adverse Drug Reactions and Medication Intake., , , and . CoRR, (2018)À la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge., , , and . JAMIA, 20 (5): 843-848 (2013)NRC-Canada at SMM4H Shared Task: Classifying Tweets Mentioning Adverse Drug Reactions and Medication Intake., , , and . SMM4H@AMIA, volume 1996 of CEUR Workshop Proceedings, page 1-11. CEUR-WS.org, (2017)Recognizing UMLS Semantic Types with Deep Learning., , , , , and . LOUHI@EMNLP, page 157-167. Association for Computational Linguistics, (2019)Finiding Gene Function using LitMiner., and . TREC, Special Publication 500-255, page 451-459. National Institute of Standards and Technology (NIST), (2003)Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010., , , , and . JAMIA, 18 (5): 557-562 (2011)Getting to the (c)ore of knowledge: mining biomedical literature., and . I. J. Medical Informatics, 67 (1-3): 7-18 (2002)ExaCT: automatic extraction of clinical trial characteristics from journal publications., , , , and . BMC Med. Inf. & Decision Making, (2010)Supporting the classification of pathology reports: comparing two information retrieval methods., , and . Computer Methods and Programs in Biomedicine, 62 (2): 109-113 (2000)Haystacks and hypotheses., , and . ASIST, volume 40 of Proc. Assoc. Inf. Sci. Technol., page 59-64. Wiley, (2003)