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Discovering sequential patterns in a UK general practice database

Reps, Jenna; Garibaldi, Jonathan M.; Aickelin, Uwe; Soria, Daniele; Gibson, Jack E.; Hubbard, Richard B.

Authors

Jenna Reps

Jonathan M. Garibaldi

Uwe Aickelin

Daniele Soria

Jack E. Gibson

Richard B. Hubbard



Abstract

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, allowing the implementation of preventative actions.
In this paper sequential rule mining is applied to a General
Practice database to find rules involving a patients age, gender and medical history. By incorporating these rules into current health-care a patient can be highlighted as susceptible to a future illness based on past or current illnesses, gender and year of birth. This knowledge has the ability to greatly improve health-care and reduce health-care costs.

Citation

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

Conference Name 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics
End Date Jan 7, 2012
Deposit Date Jul 18, 2013
Peer Reviewed Peer Reviewed
Public URL http://eprints.nottingham.ac.uk/id/eprint/2063
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
Additional Information Copyright 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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