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All Outputs (24)

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.