DSA ADS Course - 2021
Algorithm, Adverse Event Reporting System, FAERS, Data Mining, Signal Detection, Bayes Geometric Mean, FDA AERS Database, Disproportionality Analysis, Pharmacovigilance
A Comparative Study of Data Mining Algorithms used for Signal Detection in FDA AERS Database
DSA ADS Course - 2021
Algorithm, Adverse Event Reporting System, FAERS, Data Mining, Signal Detection, Bayes Geometric Mean
Commonality of Drug-associated Adverse Events Detected by 4 Commonly Used Data Mining Algorithms
Objectives: Data mining algorithms have been developed for the quantitative detection of drug-associated adverse events (signals) from a large database on spontaneously reported adverse events. In the present study, the commonality of signals detected by 4 commonly used data mining algorithms was examined.
DSA External Course - 2021
Abstract:
Machine Learning and Data Mining (MLDM) algorithms are becoming increasingly important in analyzing large volume of data generated by simulations, experiments and mobile devices. With increasing data volume, distributed memory systems (such as tightly connected supercomputers or cloud computing systems) are becoming important in designing in-memory and massively parallel MLDM algorithms. Yet, the majority of open source MLDM software is limited to sequential execution with a few supporting multi-core/many-core execution.