@inproceedings { , title = {Discovering sequential patterns in a UK general practice database}, 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.}, conference = {2012 IEEE-EMBS International Conference on Biomedical and Health Informatics}, organization = {Hong Kong}, publicationstatus = {Accepted}, url = {https://nottingham-repository.worktribe.com/output/1009185}, author = {Reps, Jenna and Garibaldi, Jonathan M. and Aickelin, Uwe and Soria, Daniele and Gibson, Jack E. and Hubbard, Richard B.} }