Early Detection of Pharmacovigilance Signals with Automated Methods Based on False Discovery Rates-Reference-Cited by-同舟云学术

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Early Detection of Pharmacovigilance Signals with Automated Methods Based on False Discovery Rates

Published:2012-06 Issue:6 Volume:35 Page:495-506
ISSN:0114-5916
Container-title:Drug Safety
language:en
Short-container-title:Drug Safety

Author:

Ahmed Ismaïl,Thiessard Frantz,Miremont-Salamé Ghada,Haramburu Françoise,Kreft-Jais Carmen,Bégaud Bernard,Tubert-Bitter Pascale

Publisher

Springer Science and Business Media LLC

Subject

Pharmacology (medical),Pharmacology,Toxicology

Reference24 articles.

1. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions

2. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports

3. A Bayesian neural network method for adverse drug reaction signal generation

4. Extending the methods used to screen the WHO drug safety database towards analysis of complex associations and improved accuracy for rare events

5. Use of Screening Algorithms and Computer Systems to Efficiently Signal Higher-Than-Expected Combinations of Drugs and Events in the US FDA??s Spontaneous Reports Database

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1. Simultaneous Confidence Intervals for Signal Detection and Ascertaining Precision of Adverse Event Rates in Clinical Trials;Statistics in Biopharmaceutical Research;2024-08-05

2. Adverse drug reaction signal detection methods in spontaneous reporting system: A systematic review;Pharmacoepidemiology and Drug Safety;2024-02-28

3. Is There a Risk for Semaglutide Misuse? Focus on the Food and Drug Administration’s FDA Adverse Events Reporting System (FAERS) Pharmacovigilance Dataset;Pharmaceuticals;2023-07-11

4. Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study;Drug Safety;2023-07-08

5. Artificial Intelligence in Pharmacovigilance and COVID-19;Current Drug Safety;2023-02

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