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2018 | Supplement | Chapter

Integrating Association Rules Mined from Health-Care Data with Ontological Information for Automated Knowledge Generation

Authors : John Heritage, Sharon McDonald, Ken McGarry

Published in: Advances in Computational Intelligence Systems

Publisher: Springer International Publishing

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Abstract

Association rule mining can be combined with complex network theory to automatically create a knowledge base that reveals how certain drugs cause side-effects on patients when they interact with other drugs taken by the patient when they have two or more diseases. The drugs will interact with on-target and off-target proteins often in an unpredictable way. A computational approach is necessary to be able to unravel the complex relationships between disease comorbidities. We built statistical models from the publicly available FAERS dataset to reveal interesting and potentially harmful drug combinations based on side-effects and relationships between co-morbid diseases. This information is very useful to medical practitioners to tailor patient prescriptions for optimal therapy.

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Metadata
Title
Integrating Association Rules Mined from Health-Care Data with Ontological Information for Automated Knowledge Generation
Authors
John Heritage
Sharon McDonald
Ken McGarry
Copyright Year
2018
Book
Advances in Computational Intelligence Systems

Print ISBN: 978-3-319-66938-0

Electronic ISBN: 978-3-319-66939-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-66939-7_1

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