AIMC Topic: Adverse Drug Reaction Reporting Systems
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Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.
Clinical pharmacology and therapeutics
Feb 28, 2020
Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this s...
A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis.
International journal of medical informatics
Oct 5, 2019
CONTEXT: Adverse events in healthcare are often collated in incident reports which contain unstructured free text. Learning from these events may improve patient safety. Natural language processing (NLP) uses computational techniques to interrogate f...
Comparison of text processing methods in social media-based signal detection.
Pharmacoepidemiology and drug safety
Aug 7, 2019
PURPOSE: Adverse event (AE) identification in social media (SM) can be performed using various types of natural language processing (NLP) and machine learning (ML). These methods can be categorized by complexity and precision level. Co-occurrence-bas...
Data Collection
Pharmacovigilance
Datasets as Topic
Feasibility Studies
Drug-Related Side Effects and Adverse Reactions
False Positive Reactions
Adverse Drug Reaction Reporting Systems
False Negative Reactions
Retrospective Studies
Social Media
Natural Language Processing
Sensitivity and Specificity
Semi-Supervised Learning Algorithm for Identifying High-Priority Drug-Drug Interactions Through Adverse Event Reports.
IEEE journal of biomedical and health informatics
Aug 2, 2019
Identifying drug-drug interactions (DDIs) is a critical enabler for reducing adverse drug events and improving patient safety. Generating proper DDI alerts during prescribing workflow has the potential to prevent DDI-related adverse events. However, ...
Artificial Intelligence for Drug Toxicity and Safety.
Trends in pharmacological sciences
Aug 2, 2019
Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, however, can result in damaging side effects and must be closely monitored. Pharmacovigilance is the field of science that monitors, detects, and preve...
Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer.
International journal of medical informatics
May 25, 2019
BACKGROUND: Hospital discharge summaries offer a potentially rich resource to enhance pharmacovigilance efforts to evaluate drug safety in real-world clinical practice. However, it is infeasible for experts to read through all discharge summaries to ...
Smoothing dense spaces for improved relation extraction between drugs and adverse reactions.
International journal of medical informatics
May 13, 2019
BACKGROUND AND OBJECTIVE: This work aims at extracting Adverse Drug Reactions (ADRs), i.e. a harm directly caused by a drug at normal doses, from Electronic Health Records (EHRs). The lack of readily available EHRs because of confidentiality issues a...
Detecting Potential Adverse Drug Reactions Using a Deep Neural Network Model.
Journal of medical Internet research
Feb 6, 2019
BACKGROUND: Adverse drug reactions (ADRs) are common and are the underlying cause of over a million serious injuries and deaths each year. The most familiar method to detect ADRs is relying on spontaneous reports. Unfortunately, the low reporting rat...
Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing.
Clinical pharmacology and therapeutics
Dec 11, 2018
Automation of pharmaceutical safety case processing represents a significant opportunity to affect the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of using artificial intellig...
Identifying health information technology related safety event reports from patient safety event report databases.
Journal of biomedical informatics
Sep 10, 2018
OBJECTIVE: The objective of this paper was to identify health information technology (HIT) related events from patient safety event (PSE) report free-text descriptions. A difference-based scoring approach was used to prioritize and select model featu...
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