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 …
Prospective data mining of six products in the US FDA Adverse Event Reporting System: disposition of events identified and impact on product safety profiles
S Bailey, A Singh, R Azadian, P Huber, M Blum - Drug safety, 2010 - Springer
Background: The use of data mining has increased among regulators and pharmaceutical
companies. The incremental value of data mining as an adjunct to traditional …
companies. The incremental value of data mining as an adjunct to traditional …
Comparison of data mining methods for the signal detection of adverse drug events with a hierarchical structure in postmarketing surveillance
There are several different proposed data mining methods for the postmarketing
surveillance of drug safety. Adverse events are often classified into a hierarchical structure …
surveillance of drug safety. Adverse events are often classified into a hierarchical structure …
[引用][C] Signal detection in pharmacovigilance: empirical evaluation of data mining tools
KA Chan, M Hauben - Pharmacoepidemiology and Drug …, 2005 - Wiley Online Library
How to quickly identify safety signals from postmarketing data is a constant challenge for
regulators and manufacturers of drugs, vaccines, and devices. As regulatory agencies and …
regulators and manufacturers of drugs, vaccines, and devices. As regulatory agencies and …
[HTML][HTML] Big data and pharmacovigilance: data mining for adverse drug events and interactions
CL Ventola - Pharmacy and therapeutics, 2018 - ncbi.nlm.nih.gov
Adverse drug events (ADEs), including drug interactions, have a tremendous impact on
patient health and generate substantial health care costs. A “big data” approach to …
patient health and generate substantial health care costs. A “big data” approach to …
Data mining spontaneous adverse drug event reports for safety signals in Singapore–a comparison of three different disproportionality measures
PS Ang, Z Chen, CL Chan, BC Tai - Expert opinion on drug safety, 2016 - Taylor & Francis
Objectives: Quantitative data mining methods can be used to identify potential signals of
unexpected relationships between drug and adverse event (AE). This study aims to compare …
unexpected relationships between drug and adverse event (AE). This study aims to compare …
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 …
[HTML][HTML] Commonality of drug-associated adverse events detected by 4 commonly used data mining algorithms
T Sakaeda, K Kadoyama, K Minami… - International journal of …, 2014 - ncbi.nlm.nih.gov
Objectives: Data mining algorithms have been developed for the quantitative detection of
drug-associated adverse events (signals) from a large database on spontaneously reported …
drug-associated adverse events (signals) from a large database on spontaneously reported …
A reference standard for evaluation of methods for drug safety signal detection using electronic healthcare record databases
Background The growing interest in using electronic healthcare record (EHR) databases for
drug safety surveillance has spurred development of new methodologies for signal …
drug safety surveillance has spurred development of new methodologies for signal …
Time‐to‐signal comparison for drug safety data‐mining algorithms vs. traditional signaling criteria
AM Hochberg, M Hauben - Clinical Pharmacology & …, 2009 - Wiley Online Library
Data mining may improve identification of signals, but its incremental utility is in question.
The objective of this study was to compare associations highlighted by data mining vs. those …
The objective of this study was to compare associations highlighted by data mining vs. those …