Experience of Using OWL Ontologies for Automated Inference of Routine Pre-operative Screening Tests

Abstract

We describe our experience of designing and implementing a knowledge-based pre-operative assessment decision support system. We developed the system using semantic web technology, including modular ontologies developed in the OWL Web Ontology Language, the OWL Java Application Programming Interface and an automated logic reasoner. Using ontologies at the core of the system’s architecture permits to efficiently manage a vast repository of pre-operative assessment domain knowledge, including classification of surgical procedures, classification of morbidities, and guidelines for routine pre-operative screening tests. Logical inference on the domain knowledge, according to individual patient’s medical context (medical history combined with planned surgical procedure) enables to generate personalised patients’ reports, consisting of a risk assessment and clinical recommendations, including relevant pre-operative screening tests.

DOI: 10.1007/978-3-642-17749-1_4

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Cite this paper

@inproceedings{Bouamrane2010ExperienceOU, title={Experience of Using OWL Ontologies for Automated Inference of Routine Pre-operative Screening Tests}, author={Matt-Mouley Bouamrane and Alan L. Rector and Martin Hurrell}, booktitle={International Semantic Web Conference}, year={2010} }