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


KIPS Transactions on Software and Data Engineering, Vol. 10, No. 11, pp. 465-472, Nov. 2021
https://doi.org/10.3745/KTSDE.2021.10.11.465,   PDF Download:
Keywords: Detection of ADRs, Drug Reviews, sentiment analysis, named entity recognition, ADRs Dictionary
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.


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Cite this article
[IEEE Style]
E. Y. Heo, H. Jeong, H. H. Kim, "Detection of Adverse Drug Reactions Using Drug Reviews with BERT+ Algorithm," KIPS Transactions on Software and Data Engineering, vol. 10, no. 11, pp. 465-472, 2021. DOI: https://doi.org/10.3745/KTSDE.2021.10.11.465.

[ACM Style]
Eun Yeong Heo, Hyeon-jeong Jeong, and Hyon Hee Kim. 2021. Detection of Adverse Drug Reactions Using Drug Reviews with BERT+ Algorithm. KIPS Transactions on Software and Data Engineering, 10, 11, (2021), 465-472. DOI: https://doi.org/10.3745/KTSDE.2021.10.11.465.