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Increasing the efficiency of trial-patient matching: automated clinical trial eligibility Pre-screening for pediatric oncology patients.

, , , , , , , and . BMC Medical Informatics Decis. Mak., (2015)

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Linking Medications and Their Attributes in Clinical Notes and Clinical Trial Announcements for Information Extraction: A Sequence Labeling Approach., , , , , , and . HISB, page 84. IEEE Computer Society, (2012)Building an Automated Problem List Based on Natural Language Processing: Lessons Learned in the Early Phase of Development., , , , , , and . AMIA, AMIA, (2008)Mining FDA drug labels for medical conditions., , , , , , , , and . BMC Medical Informatics Decis. Mak., (2013)Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers., , , , , , , , , and 13 other author(s). Appl. Clin. Inform., 07 (03): 693-706 (2016)Building Gold Standard Corpora for Medical Natural Language Processing Tasks., , , , , , , , and . AMIA, AMIA, (2012)Detecting Epilepsy Diagnosis in Clinical Notes: A Comparison of Traditional Text Classification Methods., , , , , , , and . AMIA, AMIA, (2014)Using Natural Language Processing and the Electronic Health Record for Appendicitis Risk Stratification., , , , , , , and . HISB, page 32. IEEE Computer Society, (2012)Preliminary Experience with Amazon’s Mechanical Turk for Annotating Medical Named Entities, , , and . Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk, page 180–183. (2010)Increasing the efficiency of trial-patient matching: automated clinical trial eligibility Pre-screening for pediatric oncology patients., , , , , , , and . BMC Medical Informatics Decis. Mak., (2015)Cheap, Fast, and Good Enough for the Non-biomedical Domain but is It Usable for Clinical Natural Language Processing? Evaluating Crowdsourcing for Clinical Trial Announcement Named Entity Annotations., , , , , , and . HISB, page 106. IEEE Computer Society, (2012)