Mining multi-item drug adverse effect associations in spontaneous reporting systems
Background Multi-item adverse drug event (ADE) associations are associations relating
multiple drugs to possibly multiple adverse events. The current standard in …
multiple drugs to possibly multiple adverse events. The current standard in …
A new search method using association rule mining for drug-drug interaction based on spontaneous report system
Y Noguchi, A Ueno, M Otsubo, H Katsuno… - Frontiers in …, 2018 - frontiersin.org
Background: Adverse events (AEs) can be caused not only by one drug but also by the
interaction between two or more drugs. Therefore, clarifying whether an AE is due to a …
interaction between two or more drugs. Therefore, clarifying whether an AE is due to a …
[HTML][HTML] Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data
Abstract Background and objectives Pharmacovigilance (PhV) is an important clinical
activity with strong implications for population health and clinical research. The main goal of …
activity with strong implications for population health and clinical research. The main goal of …
[HTML][HTML] Statistical mining of potential drug interaction adverse effects in FDA's spontaneous reporting system
Many adverse drug effects (ADEs) can be attributed to drug interactions. Spontaneous
reporting systems (SRS) provide a rich opportunity to detect novel post-marketed drug …
reporting systems (SRS) provide a rich opportunity to detect novel post-marketed drug …
A comparison study of algorithms to detect drug–adverse event associations: frequentist, bayesian, and machine-learning approaches
Introduction It is important to monitor the safety profile of drugs, and mining for strong
associations between drugs and adverse events is an effective and inexpensive method of …
associations between drugs and adverse events is an effective and inexpensive method of …
Identification of adverse drug-drug interactions through causal association rule discovery from spontaneous adverse event reports
Objective Drug-drug interaction (DDI) is of serious concern, causing over 30% of all adverse
drug reactions and resulting in significant morbidity and mortality. Early discovery of adverse …
drug reactions and resulting in significant morbidity and mortality. Early discovery of adverse …
A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports
NP Tatonetti, GH Fernald… - Journal of the American …, 2012 - academic.oup.com
Abstract Objective Adverse drug events (ADEs) are common and account for 770 000
injuries and deaths each year and drug interactions account for as much as 30% of these …
injuries and deaths each year and drug interactions account for as much as 30% of these …
Novel data‐mining methodologies for adverse drug event discovery and analysis
An important goal of the health system is to identify new adverse drug events (ADEs) in the
postapproval period. Data‐mining methods that can transform data into meaningful …
postapproval period. Data‐mining methods that can transform data into meaningful …
Evaluation of statistical association measures for the automatic signal generation in pharmacovigilance
E Roux, F Thiessard, A Fourrier… - IEEE Transactions …, 2005 - ieeexplore.ieee.org
Pharmacovigilance aims at detecting the adverse effects of marketed drugs. It is generally
based on the spontaneous reporting of events thought to be the adverse effects of drugs …
based on the spontaneous reporting of events thought to be the adverse effects of drugs …
A potential causal association mining algorithm for screening adverse drug reactions in postmarketing surveillance
Early detection of unknown adverse drug reactions (ADRs) in postmarketing surveillance
saves lives and prevents harmful consequences. We propose a novel data mining approach …
saves lives and prevents harmful consequences. We propose a novel data mining approach …