Abstract Background and objectives Pharmacovigilance (PhV) is an important clinical
activity with strong implications for population health and clinical research. The main goal of …

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 …

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 …

Background The detection of signals of adverse drug events (ADEs) has increased because
of the use of data mining algorithms in spontaneous reporting systems (SRSs). However …

Background Multi-item adverse drug event (ADE) associations are associations relating
multiple drugs to possibly multiple adverse events. The current standard in …

Since adverse drug reactions (ADRs) represent a significant health problem all over the
world, ADR detection has become an important research topic in drug safety surveillance …

The objective of this research is to assess the suitability of the Apriori association analysis
algorithm for the detection of adverse drug reactions (ADR) in health care data. The Apriori …

Early detection of unknown adverse drug reactions (ADRs) in postmarketing surveillance
saves lives and prevents harmful consequences. We propose a novel data mining approach …

With increasing trend of polypharmacy, drug‐drug interaction (DDI)‐induced adverse drug
events (ADEs) are considered as a major challenge for clinical practice. As premarketing …

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 …