All Outputs (9)

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining (2015)
Journal Article
Reps, J. M., Aickelin, U., & Hubbard, R. B. (2016). Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining. Computers in Biology and Medicine, 69, https://doi.org/10.1016/j.compbiomed.2015.11.014

Purpose: To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. Methods: We co... Read More about Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations (2015)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Gibson, J. E., & Hubbard, R. B. (2015). A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations. Journal of Biomedical Informatics, 56, https://doi.org/10.1016/j.jbi.2015.06.011

Big longitudinal observational medical data potentially hold a wealth of information and have been recognised as potential sources for gaining new drug safety knowledge. Unfortunately there are many complexities and underlying issues when analysing l... Read More about A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations.

Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs (2014)
Journal Article
Reps, J., M. Garibaldi, J., Aickelin, U., Soria, D., E. Gibson, J., & B. Hubbard, R. (2014). Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs. Drug Safety, 37(3), 163-170. https://doi.org/10.1007/s40264-014-0137-z

Background: Children are frequently prescribed medication `o-label', meaning there has not been sucient testing of the medication to determine its safety or eectiveness. The main reason this safety knowledge is lacking is due to ethical restrictions... Read More about Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs.

Comparison of algorithms that detect drug side effects using electronic healthcare databases (2013)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. (2013). Comparison of algorithms that detect drug side effects using electronic healthcare databases. Soft Computing, 17(12), https://doi.org/10.1007/s00500-013-1097-4

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 Health Improvement Network (THIN) database is an electronic healthcare dat... Read More about Comparison of algorithms that detect drug side effects using electronic healthcare databases.

A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery (2013)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. (2014). A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE Journal of Biomedical and Health Informatics, 18(2), 537-547. https://doi.org/10.1109/JBHI.2013.2281505

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 undesirable side effects. Side effects that occur in more than one in a... Read More about A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery.

Attributes for causal inference in electronic healthcare databases (2013)
Conference Proceeding
Reps, J., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. (2013). Attributes for causal inference in electronic healthcare databases.

Side effects of prescription drugs present a serious issue. Existing algorithms that detect side effects generally require further analysis to confirm causality. In this paper we investigate attributes based on the Bradford-Hill causality criteria... Read More about Attributes for causal inference in electronic healthcare databases.

Comparing data-mining algorithms developed for longitudinal observational databases
Conference Proceeding
Reps, J., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. Comparing data-mining algorithms developed for longitudinal observational databases.

Longitudinal observational databases have become a recent interest in the post marketing drug surveillance community due to their ability of presenting a new perspective for detecting negative side effects. Algorithms mining longitudinal observation... Read More about Comparing data-mining algorithms developed for longitudinal observational databases.

Discovering sequential patterns in a UK general practice database
Conference Proceeding
Reps, J., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. Discovering sequential patterns in a UK general practice database.

The wealth of computerised medical information becoming readily available presents the opportunity to examine patterns of illnesses, therapies and responses. These patterns may be able to predict illnesses that a patient is likely to develop, allowi... Read More about Discovering sequential patterns in a UK general practice database.

Investigating the detection of adverse drug events in a UK general practice electronic health-care database
Conference Proceeding
Reps, J., Feyereisl, J., Garibaldi, J. M., Aickelin, U., Gibson, J. E., & Hubbard, R. B. Investigating the detection of adverse drug events in a UK general practice electronic health-care database.

Data-mining techniques have frequently been developed for Spontaneous reporting databases. These techniques aim to find adverse drug events accurately and efficiently. Spontaneous reporting databases are prone to missing information,under reporting... Read More about Investigating the detection of adverse drug events in a UK general practice electronic health-care database.