AIMC Topic: Adverse Drug Reaction Reporting Systems

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Identifying New Candidate Predictors of Mortality in Japanese Patients with Severe Drug Eruptions.

Drug safety Nov 1, 2025
UNLABELLED: BACKGROUND AND OBJECTIVES: SCORe of Toxic Epidermal Necrolysis (SCORTEN) and ABCD-10 have been developed as scoring systems for predicting mortality associated with Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN). These...
Japan Adverse Drug Reaction Reporting Systems Drug Eruptions Stevens-Johnson Syndrome Middle Aged Severity of Illness Index East Asian People Adult Male Machine Learning Algorithms Databases, Factual Female Aged Aged, 80 and over Humans
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A review on adverse drug reaction related to medication in health sector: an account of what we have discovered and implemented-pharmacovigilance.

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...
Humans Risk Factors Prevalence Health Care Sector Adverse Drug Reaction Reporting Systems Drug-Related Side Effects and Adverse Reactions Pharmacovigilance
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Enhancing Vaccine Safety Surveillance: Extracting Vaccine Mentions from Emergency Department Triage Notes Using Fine-Tuned Large Language Models.

Studies in health technology and informatics Aug 7, 2025
This study evaluates fine-tuned Llama 3.2 models for extracting vaccine-related information from emergency department triage notes to support near real-time vaccine safety surveillance. Prompt engineering was used to initially create a labeled datase...
Natural Language Processing Emergency Service, Hospital Vaccines Electronic Health Records Triage Large Language Models Data Mining Adverse Drug Reaction Reporting Systems Product Surveillance, Postmarketing Humans
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Optimizing Entity Recognition in Psychiatric Treatment Data with Large Language Models.

Studies in health technology and informatics Aug 7, 2025
Extracting nuanced adverse drug reactions (ADRs) from patient self-reported messages using is pivotal but challenging, particularly given HIPAA constraints. We investigate locally deployable small LLMs-Mistral-7B, Llama-3-8B, and Gemma-7B-for ADR ext...
Humans Mental Disorders Large Language Models Drug-Related Side Effects and Adverse Reactions Electronic Health Records Data Mining Natural Language Processing Adverse Drug Reaction Reporting Systems
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Development of an Automated Classification System for Medication-Related Incident Factors: A Practical Approach to Enhancing Patient Safety Management.

Studies in health technology and informatics Aug 7, 2025
Analyzing medication-related incident reports is crucial for patient safety; however, systematically extracting the underlying factors contributing to incident occurrence remains challenging. We developed a multi-label classifier that automatically i...
Humans Medication Errors Adverse Drug Reaction Reporting Systems Patient Safety Natural Language Processing Risk Management
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Natural Language Processing-Based Approach to Detect Common Adverse Events of Anticancer Agents from Unstructured Clinical Notes: A Time-to-Event Analysis.

Studies in health technology and informatics Aug 7, 2025
This study assessed the effectiveness of natural language processing (NLP) in detecting adverse events (AEs) from anticancer agents by analyzing data from over 39,000 cancer patients. A specialized machine learning model identified known AEs from ant...
Humans Machine Learning Electronic Health Records Drug-Related Side Effects and Adverse Reactions Neoplasms Data Mining Antineoplastic Agents Adverse Drug Reaction Reporting Systems Natural Language Processing
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Detecting Adverse Drug Events in Clinical Notes Using Large Language Models.

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...
Humans Electronic Health Records Pharmacovigilance Natural Language Processing Adverse Drug Reaction Reporting Systems Drug-Related Side Effects and Adverse Reactions Large Language Models Data Mining
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Leveraging Large Language Models for Synthetic Data Generation to Enhance Adverse Drug Event Detection in Tweets.

Studies in health technology and informatics May 15, 2025
Adverse drug event (ADE) detection in social media texts poses significant challenges due to the informal nature of the text and the limited availability of annotations. The scarcity of ADE named entity recognition (NER) datasets for social media hin...
Adverse Drug Reaction Reporting Systems Large Language Models Natural Language Processing Drug-Related Side Effects and Adverse Reactions Data Mining Humans Social Media
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Leveraging Generative AI for Drug Safety and Pharmacovigilance.

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...
Adverse Drug Reaction Reporting Systems Humans Drug-Related Side Effects and Adverse Reactions Artificial Intelligence Machine Learning Pharmacovigilance
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Machine Learning upon RDF Knowledge Graphs for Drug Safety: A Case Study on Reactome Data.

Studies in health technology and informatics Aug 22, 2024
Artificial Intelligence (AI), particularly Machine Learning (ML), has gained attention for its potential in various domains. However, approaches integrating symbolic AI with ML on Knowledge Graphs have not gained significant focus yet. We argue that ...
Semantics Adverse Drug Reaction Reporting Systems Databases, Factual Signal Transduction Drug-Related Side Effects and Adverse Reactions Humans Machine Learning
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