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Study shows that online data closely match formal, large-scale surveillance data and could help monitor the effects of local alcohol control policies

News: December 02, 2019

Read more here: https://www.eurekalert.org/pub_releases/2019-12/bch-anw120219.php and here: https://medicalxpress.com/news/2019-12-nimbler-track-alcohol-useby-twit…

Simplified Neural Unsupervised Domain Adaptation

Publication: Conference Paper

Miller, Timothy. 2019. “Simplified Neural Unsupervised Domain Adaptation”. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), 414–419. Minneapolis, Minnesota: Association for Computational Linguistics.

A BERT-based Universal Model for Both Within- and Cross-sentence Clinical Temporal Relation Extraction

Publication: Conference Paper

Lin, Chen, Timothy Miller, Dmitriy Dligach, Steven Bethard, and Guergana Savova. 2019. “A BERT-Based Universal Model for Both Within- and Cross-Sentence Clinical Temporal Relation Extraction”. In Proceedings of the 2nd Clinical Natural Language Processing Workshop, 65–71. Minneapolis, Minnesota, USA: Association for Computational Linguistics.

An increasingly complex view of intestinal motility

Publication: Journal Article

Rao, Meenakshi. 2020. “An Increasingly Complex View of Intestinal Motility”. Nat Rev Gastroenterol Hepatol 17 (2): 72-73.

A nimbler way to track alcohol use: mining Twitter and Google searches

News: December 02, 2019

Large, survey-based studies are a slow, expensive way to collect rigorous public health data. New research, focusing on alcohol use, shows that mining Twitter and online searches could enable public health professionals to get immediate, localized insights, spot emerging trends, and even measure the...

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Extracting Adverse Drug Event Information with Minimal Engineering

Publication: Conference Paper

Miller, Timothy, Alon Geva, and Dmitriy Dligach. 2019. “Extracting Adverse Drug Event Information With Minimal Engineering”. In Proceedings of the 2nd Clinical Natural Language Processing Workshop, 22–27. Minneapolis, Minnesota, USA: Association for Computational Linguistics.

Unsupervised Learning of PCFGs with Normalizing Flow

Publication: Conference Paper

Jin, Lifeng, Finale Doshi-Velez, Timothy Miller, Lane Schwartz, and William Schuler. 2019. “Unsupervised Learning of PCFGs With Normalizing Flow”. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2442–2452. Florence, Italy: Association for Computational Linguistics.

Two-stage Federated Phenotyping and Patient Representation Learning

Publication: Conference Paper

Liu, Dianbo, Dmitriy Dligach, and Timothy Miller. 2019. “Two-Stage Federated Phenotyping and Patient Representation Learning”. In Proceedings of the 18th BioNLP Workshop and Shared Task, 283–291. Florence, Italy: Association for Computational Linguistics.

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