A Comparison Study of Algorithms to Detect Drug–Adverse Event Associations: Frequentist, Bayesian, and Machine-Learning Approaches

An MCEM Framework for Drug Safety Signal Detection and Combination from Heterogeneous Real World Evidence

(2018) Cao Xiao et al.   Scientific Reports

VigiBase, the WHO Global ICSR Database System: Basic Facts

(2017) Marie Lindquist   DRUG INFORMATION JOURNAL

Detecting gene-gene interactions using a permutation-based random forest method

(2016) Jing Li et al.   BioData Mining

Performance of Pharmacovigilance Signal-Detection Algorithms for the FDA Adverse Event Reporting System

(2013) R Harpaz et al.   CLINICAL PHARMACOLOGY & THERAPEUTICS

Defining a Reference Set to Support Methodological Research in Drug Safety

(2013) Patrick B. Ryan et al.   DRUG SAFETY

Speeding up incremental wrapper feature subset selection with Naive Bayes classifier

(2013) Pablo Bermejo et al.   KNOWLEDGE-BASED SYSTEMS

Random forests for genomic data analysis

(2012) Xi Chen et al.   GENOMICS

Antipsychotics, Glycemic Disorders, and Life-Threatening Diabetic Events: A Bayesian Data-Mining Analysis of the FDA Adverse Event Reporting System (1968-2004)

(2008) William DuMouchel et al.   Annals of Clinical Psychiatry