Adverse Drug Reaction Posts Detection with a Bi-LSTM based approach-Reference-Cited by-同舟云学术

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Adverse Drug Reaction Posts Detection with a Bi-LSTM based approach

Published:2023-02 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Big Data and Smart Computing (BigComp)
language:
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Author:

Lee Chung-Chun¹,Lee Seunghee²,Song Mi Hwa³,Lee Suehyun¹,Kim Jong-Yeop²

Affiliation:

1. College of Medicine Konyang University,Department of Biomedical Informatics,Daejeon,Republic of Korea

2. Konyang Univ. Medical Center,Healthcare Data Science Center,Daejeon,Republic of Korea

3. Semyung University,Division of Information and Communication Sciences,Jecheon,Republic of Korea

Funder

Ministry of Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10066534/10066540/10066546.pdf?arnumber=10066546

Reference5 articles.

1. Impact of SMOTE on imbalanced text features for toxic comments classification using RVVC model;rupapara;IEEE Access,2021

2. Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts

3. South Korean geriatrics on Beers Criteria medications at risk of adverse drug events

4. Clinical and economic burden of adverse drug reactions;sultana;Journal of Pharmacy and Pharmacology,2013

5. Factors associated with preventable adverse drug reactions

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