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Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review.

, , , , , , , , , and . BMC Medical Informatics Decis. Mak., 18 (1): 38:1-38:14 (2018)

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A survey of word embeddings for clinical text., , , , , and . J. Biomed. Informatics X, (2019)Can Character Embeddings Improve Cause-of-Death Classification for Verbal Autopsy Narratives?, , and . BioNLP@ACL, page 234-239. Association for Computational Linguistics, (2019)AutoScribe: Extracting Clinically Pertinent Information from Patient-Clinician Dialogues., , , , and . MedInfo, volume 264 of Studies in Health Technology and Informatics, page 1512-1513. IOS Press, (2019)Multi-task learning for interpretable cause of death classification using key phrase prediction., , and . BioNLP, page 12-17. Association for Computational Linguistics, (2018)Automating disease diagnosis and cause-of-death classification from medical narratives using event extraction and temporal ordering.. University of Toronto, Canada, (2021)Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review., , , , , , , , , and . BMC Medical Informatics Decis. Mak., 18 (1): 38:1-38:14 (2018)Toronto CL CLEF 2018 eHealth Task 1: Multi-lingual ICD-10 Coding using an Ensemble of Recurrent and Convolutional Neural Networks., , , , , , , and . CLEF (Working Notes), volume 2125 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)Automatically determining cause of death from verbal autopsy narratives., , , , and . BMC Medical Informatics Decis. Mak., 19 (1): 127:1-127:13 (2019)Using acoustics to improve pronunciation for synthesis of low resource languages., , and . INTERSPEECH, page 259-263. ISCA, (2015)Extracting relevant information from physician-patient dialogues for automated clinical note taking., , , , and . LOUHI@EMNLP, page 65-74. Association for Computational Linguistics, (2019)