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2019 ACL ACL 2019

Towards Text Processing Pipelines to Identify Adverse Drug Events-related Tweets: University of Michigan @ SMM4H 2019 Task 1

Abstract

AbstractWe participated in Task 1 of the Social Media Mining for Health Applications (SMM4H) 2019 Shared Tasks on detecting mentions of adverse drug events (ADEs) in tweets. Our approach relied on a text processing pipeline for tweets, and training traditional machine learning and deep learning models. Our submitted runs performed above average for the task.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Healthcare & Medicine and Natural Language Processing

Authors

V.G.Vinod Vydiswaran, Grace Ganzel, Bryan Romas, Deahan Yu, Amy Austin, Neha Bhomia, Socheatha Chan, Stephanie Hall, Van Le, Aaron Miller, Olawunmi Oduyebo, Aulia Song, Radhika Sondhi, Danny Teng, Hao Tseng, Kim Vuong, Stephanie Zimmerman

Topics

Machine Learning > Application Areas > Risk Management Deep Learning > Architectures > Neural Networks Natural Language Processing > Understanding > Named Entity Recognition Machine Learning > Learning Types > Supervised Learning Healthcare & Medicine > Clinical > Medical NLP

Keywords

text classification named entity recognition deep learning text processing pipeline text processing adverse drug event tweet processing
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