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arXiv · 1307.1411

Discovering Sequential Patterns in a UK General Practice Database

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

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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard. 2013-07-04. Discovering Sequential Patterns in a UK General Practice Database. https://arxiv.org/abs/1307.1411

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