Pharmacovigilance with Transformers: A Framework to Detect Adverse Drug Reactions Using BERT Fine‐Tuned with FARM

S Hussain, H Afzal, R Saeed, N Iltaf… - … Methods in Medicine, 2021 - Wiley Online Library
Adverse drug reactions (ADRs) are the undesirable effects associated with the use of a drug
due to some pharmacological action of the drug. During the last few years, social media has …

Explainable detection of adverse drug reaction with imbalanced data distribution

J Wang, LC Yu, X Zhang - PLoS computational biology, 2022 - journals.plos.org
Analysis of health-related texts can be used to detect adverse drug reactions (ADR). The
greatest challenge for ADR detection lies in imbalanced data distributions where words …

Drug adverse event detection using text-based convolutional neural networks (TextCNN) technique

A Rawat, MA Wani, M ElAffendi, AS Imran, Z Kastrati… - Electronics, 2022 - mdpi.com
With the rapid advancement in healthcare, there has been exponential growth in the
healthcare records stored in large databases to help researchers, clinicians, and medical …

[PDF][PDF] Adverse drug reactions extraction from social media: a systematic review

A Dey, J Shrivastava, C Kumar… - … International Journal of …, 2022 - academia.edu
The objective of this study is to observe the importance of social media in automatic
extraction of Adverse Drug Reactions (ADRs) from different medical forum, social media like …

Accuracy analysis of the end-to-end extraction of related named entities from Russian drug review texts by modern approaches validated on English Biomedical …

A Sboev, R Rybka, A Selivanov, I Moloshnikov… - Mathematics, 2023 - mdpi.com
An extraction of significant information from Internet sources is an important task of
pharmacovigilance due to the need for post-clinical drugs monitoring. This research …

Interactive attention network for adverse drug reaction classification

I Alimova, V Solovyev - Artificial Intelligence and Natural Language: 7th …, 2018 - Springer
Detection of new adverse drug reactions is intended to both improve the quality of
medications and drug reprofiling. Social media and electronic clinical reports are becoming …

Classical-quantum hybrid transfer learning for adverse drug reaction detection from social media posts

A Dey, JN Shrivastava, C Kumar - Journal of Computational Social …, 2024 - Springer
Abstract Adverse Drug Reactions (ADRs) is a threat to human beings, sometimes it causes
death. Thus, the detection of ADRs is crucial. This paper introduces a classical-quantum …

Multiple features-based adverse drug reaction detection from social media using deep convolutional neural networks (DCNN)

S Spandana, RV Prakash - Multimedia Tools and Applications, 2024 - Springer
Adverse drug responses (ADRs) are unfavourable side effects of using a medication that
result from the medication's pharmacological activity. Social media has gained popularity …

Detecting adverse drug reactions from biomedical texts with neural networks

I Alimova, E Tutubalina - Proceedings of the 57th Annual Meeting …, 2019 - aclanthology.org
Detection of adverse drug reactions in postapproval periods is a crucial challenge for
pharmacology. Social media and electronic clinical reports are becoming increasingly …

A LSTM-based method with attention mechanism for adverse drug reaction sentences detection

E El-allaly, M Sarrouti, N En-Nahnahi… - … Intelligent Systems for …, 2020 - Springer
Adverse drug reactions (ADRs) are among the top causes of morbidity, mortality and
substantial healthcare costs and thus should be detected early to reduce consequences on …