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Reps, Jenna, Garibaldi, Jonathan M., Aickelin, Uwe, Soria, Daniele, Gibson, Jack E. and Hubbard, Richard B. (2012) Discovering sequential patterns in a UK general practice database. In: 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics, 5-7 Jan 2012, Hong Kong. (In Press)

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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.

Item Type:	Conference or Workshop Item (Paper)
RIS ID:	https://nottingham-repository.worktribe.com/output/1009185
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.
Schools/Departments:	University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User:	Aickelin, Professor Uwe
Date Deposited:	18 Jul 2013 15:03
Last Modified:	04 May 2020 20:22
URI:	https://eprints.nottingham.ac.uk/id/eprint/2063

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