Using Machine Learning and Deep Learning Methods to Find Mentions of Adverse Drug Reactions in Social Media

Pilar López Úbeda, Manuel Carlos Díaz Galiano, Maite Martin, L. Alfonso Urena Lopez


Abstract
Over time the use of social networks is becoming very popular platforms for sharing health related information. Social Media Mining for Health Applications (SMM4H) provides tasks such as those described in this document to help manage information in the health domain. This document shows the first participation of the SINAI group. We study approaches based on machine learning and deep learning to extract adverse drug reaction mentions from Twitter. The results obtained in the tasks are encouraging, we are close to the average of all participants and even above in some cases.
Anthology ID:
W19-3216
Volume:
Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
102–106
Language:
URL:
https://www.aclweb.org/anthology/W19-3216
DOI:
10.18653/v1/W19-3216
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-3216.pdf