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Using OWL ontologies for adaptive patient information modelling and preoperative clinical decision support

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Abstract

We here present our research and experience regarding the design and implementation of a knowledge-based preoperative assessment decision support system. We discuss generic design considerations as well as the practical system implementation. 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. We discuss how the system enables to tailor patient information collection according to personalized medical context. The use of ontologies at the core of the system’s architecture permits to efficiently manage a vast repository of preoperative assessment domain knowledge, including classification of surgical procedures, classification of morbidities and guidelines for routine preoperative tests. Logical inference on the domain knowledge according to individual patient’s medical context enables personalized patients’ reports consisting of a risk assessment and clinical recommendations such as relevant preoperative tests.

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Authors and Affiliations

  1. Faculty of Medicine, University of Glasgow, Glasgow, Scotland, UK

    Matt-Mouley Bouamrane

  2. School of Computer Science, Manchester University, Manchester, UK

    Alan Rector

  3. CIS Informatics, Glasgow, Scotland, UK

    Martin Hurrell

Authors
  1. Matt-Mouley Bouamrane
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  2. Alan Rector
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  3. Martin Hurrell
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Correspondence to Matt-Mouley Bouamrane.

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Bouamrane, MM., Rector, A. & Hurrell, M. Using OWL ontologies for adaptive patient information modelling and preoperative clinical decision support. Knowl Inf Syst 29, 405–418 (2011). https://doi.org/10.1007/s10115-010-0351-7

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  • DOI: https://doi.org/10.1007/s10115-010-0351-7

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