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http://dx.doi.org/10.3745/KTSDE.2021.10.11.465

Detection of Adverse Drug Reactions Using Drug Reviews with BERT+ Algorithm  

Heo, Eun Yeong (한양대학교 컴퓨터소프트웨어학과)
Jeong, Hyeon-jeong (동덕여자대학교 정보통계학과)
Kim, Hyon Hee (동덕여자대학교 정보통계학과)
Publication Information
KIPS Transactions on Software and Data Engineering / v.10, no.11, 2021 , pp. 465-472 More about this Journal
Abstract
In this paper, we present an approach for detection of adverse drug reactions from drug reviews to compensate limitations of the spontaneous adverse drug reactions reporting system. Considering negative reviews usually contain adverse drug reactions, sentiment analysis on drug reviews was performed and extracted negative reviews. After then, MedDRA dictionary and named entity recognition were applied to the negative reviews to detect adverse drug reactions. For the experiment, drug reviews of Celecoxib, Naproxen, and Ibuprofen from 5 drug review sites, and analyzed. Our results showed that detection of adverse drug reactions is able to compensate to limitation of under-reporting in the spontaneous adverse drugs reactions reporting system.
Keywords
Detection of ADRs; Drug Reviews; Sentiment Analysis; Named Entity Recognition; ADRs Dictionary;
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