74 citations · 118 across the 15 of their papers we have counts for
6 papers · 1 filter
Attributes for Causal Inference in Longitudinal Observational Databases
Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin +3
The pharmaceutical industry is plagued by the problem of side effects that can occur anytime a prescribed medication is ingested. There has been a recent interest in using the vast…
Tuning a Multiple Classifier System for Side Effect Discovery using Genetic Algorithms
Jenna M. Reps, Uwe Aickelin, Jonathan M. Garibaldi
In previous work, a novel supervised framework implementing a binary classifier was presented that obtained excellent results for side effect discovery. Interestingly, unique side…
Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs
Jenna M. Reps, Jonathan M. Garibaldi, Uwe Aickelin +3
Background: Children are frequently prescribed medication off-label, meaning there has not been sufficient testing of the medication to determine its safety or effectiveness. The m…
A Novel Semi-Supervised Algorithm for Rare Prescription Side Effect Discovery
Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin +3
Drugs are frequently prescribed to patients with the aim of improving each patient's medical state, but an unfortunate consequence of most prescription drugs is the occurrence of u…
Comparing Stochastic Differential Equations and Agent-Based Modelling and Simulation for Early-stage Cancer
Grazziela P Figueredo, Peer-Olaf Siebers, Markus R Owen +2
There is great potential to be explored regarding the use of agent-based modelling and simulation as an alternative paradigm to investigate early-stage cancer interactions with the…
Comparison of algorithms that detect drug side effects using electronic healthcare databases
Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin +3
The electronic healthcare databases are starting to become more readily available and are thought to have excellent potential for generating adverse drug reaction signals. The Heal…