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Natural Language Processing (1206) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (256) Machine Learning (2981) Generative Language Models Including ChatGPT (1370)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67513, first published .
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Predicting Drug–Side Effect Relationships From Parametric Knowledge Embedded in Biomedical BERT Models: Methodological Study With a Natural Language Processing Approach

Predicting Drug–Side Effect Relationships From Parametric Knowledge Embedded in Biomedical BERT Models: Methodological Study With a Natural Language Processing Approach

Authors of this article:

Woohyuk Jeon1 Author Orcid Image ;   Minjae Park1 Author Orcid Image ;   Doyeon An1 Author Orcid Image ;   Wonshik Nam1 Author Orcid Image ;   Ju-Young Shin2 Author Orcid Image ;   Seunghee Lee3 Author Orcid Image ;   Suehyun Lee1 Author Orcid Image
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  2. Park J, Kim M, Lee S. AI Pharmacovigilance Workflow for Detecting Neurological Adverse Events from Reports, Notes, and Literature. Pharmacophore 2025;16(3):42 View

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  1. Shovon R, Sabbir M, Chowdhury T, Alam M, Hasan M, Urmi S, Arif M. 2025 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE). Hybrid Transformer-Based Approaches for Pharmacovigilance: Detecting Adverse Drug Reaction from Patient-Generated Drug Reviews View