This study aimed to detect and contrast the adverse drug event (ADE) signals associated with sodium zirconate cyclosilicate (SZC) and Patiromer by leveraging the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS), thereby in...
Naunyn-Schmiedeberg's archives of pharmacology
Nov 1, 2025
Despite the extensive research on medication-related adverse events (MRAEs) in healthcare, the assessment of the present scenario is made more difficult by the high degree of variability in study results. This study's primary goal was to create a cur...
Studies in health technology and informatics
May 15, 2025
Monitoring adverse drug events (ADEs) is critical for pharmacovigilance and patient safety. However, identifying ADEs remains challenging, as suspected or confirmed side effects are often documented solely in the unstructured text of electronic healt...
Current reviews in clinical and experimental pharmacology
Jan 1, 2025
Predictions are made by artificial intelligence, especially through machine learning, which uses algorithms and past knowledge. Notably, there has been an increase in interest in using artificial intelligence, particularly generative AI, in the pharm...
Studies in health technology and informatics
Aug 22, 2024
Causal Deep/Machine Learning (CDL/CML) is an emerging Artificial Intelligence (AI) paradigm. The combination of causal inference and AI could mine explainable causal relationships between data features, providing useful insights for various applicati...
This new editorial discusses the promise and challenges of successful integration of natural language processing methods into electronic health records for timely, robust, and fair oncology pharmacovigilance.
Pharmacovigilance (PV) deals with the detection, collection, assessment, understanding, and prevention of adverse effects associated with drugs. The objective of PV is to ensure the safety of the medicines and patients by monitoring and reporting all...
Studies in health technology and informatics
Jun 29, 2022
Many decision support methods and systems in pharmacovigilance are built without explicitly addressing specific challenges that jeopardize their eventual success. We describe two sets of challenges and appropriate strategies to address them. The firs...
Studies in health technology and informatics
May 25, 2022
Methods of natural language processing associated with machine learning or deep learning can support detection of adverse drug reactions in abstracts of case reports available on Pubmed. In 2012, Gurulingappa et al. proposed a training set for the re...
Journal of the American Medical Informatics Association : JAMIA
Sep 18, 2021
OBJECTIVE: Research on pharmacovigilance from social media data has focused on mining adverse drug events (ADEs) using annotated datasets, with publications generally focusing on 1 of 3 tasks: ADE classification, named entity recognition for identify...
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