Study of the Drug-related Adverse Events with the Help of Electronic Health Records and Natural Language Processing

S Allabun, BO Soufiene - International Journal of Advanced …, 2023 - search.proquest.com
Surveillance of pharmacovigilance, also known as drug safety surveillance, involves the
monitoring and evaluation of drug-related adverse events or side effects to ensure the safe …

Using machine learning for pharmacovigilance: a systematic review

P Pilipiec, M Liwicki, A Bota - Pharmaceutics, 2022 - mdpi.com
Pharmacovigilance is a science that involves the ongoing monitoring of adverse drug
reactions to existing medicines. Traditional approaches in this field can be expensive and …

Improving drug safety with adverse event detection using natural language processing

T Botsis, K Kreimeyer - Expert Opinion on Drug Safety, 2023 - Taylor & Francis
Introduction Pharmacovigilance (PV) involves monitoring and aggregating adverse event
information from a variety of data sources, including health records, biomedical literature …

[HTML][HTML] Pharmacovigilance through the development of text mining and natural language processing techniques

I Segura-Bedmar, P Martínez - Journal of biomedical informatics, 2015 - Elsevier
As defined by the World Health Organization (WHO), pharmacovigilance encompasses a
range of activities whose common aim is to detect and prevent any possible drug-related …

NLPADADE: Leveraging Natural Language Processing for Automated Detection of Adverse Drug Effects

AB Bomgni, CEM Ngale, S Aryal… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
Pharmacovigilance is a systematic and scientifically rigorous discipline that assumes
responsibility for the safety of pharmaceuticals, with its primary objective being the mitigation …

Natural language processing for EHR-based pharmacovigilance: a structured review

Y Luo, WK Thompson, TM Herr, Z Zeng, MA Berendsen… - Drug safety, 2017 - Springer
The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug
events (ADEs) with pharmaceutical products. This article is a comprehensive structured …

[HTML][HTML] Extracting adverse drug events from clinical notes

D Mahendran, BT McInnes - AMIA Summits on Translational …, 2021 - ncbi.nlm.nih.gov
Adverse drug events (ADEs) are unexpected incidents caused by the administration of a
drug or medication. To identify and extract these events, we require information about not …

A study of deep learning approaches for medication and adverse drug event extraction from clinical text

Q Wei, Z Ji, Z Li, J Du, J Wang, J Xu… - Journal of the …, 2020 - academic.oup.com
Objective This article presents our approaches to extraction of medications and associated
adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 …

A Modified Skip‐Gram Algorithm for Extracting Drug‐Drug Interactions from AERS Reports

L Wang, W Pan, QH Wang, H Bai, W Liu… - … Methods in Medicine, 2020 - Wiley Online Library
Drug‐drug interactions (DDIs) are one of the indispensable factors leading to adverse event
reactions. Considering the unique structure of AERS (Food and Drug Administration …

IBM Research System at MADE 2018: detecting adverse drug events from electronic health records

B Dandala, V Joopudi… - … Workshop on Medication …, 2018 - proceedings.mlr.press
Abstract Adverse Drug Events (ADEs) are common and occur in approximately 2-5% of
hospitalized adult patients. Each ADE is estimated to increase healthcare cost by more than …