Using OWL ontologies for adaptive patient information modelling and preoperative clinical decision support |
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Authors: | Matt-Mouley Bouamrane Alan Rector Martin Hurrell |
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Affiliation: | (1) Department of Practice and Policy, The School of Pharmacy, University of London, BMA House, Mezzanine Floor, Tavistock Square, London, WC1H 9JP, UK;(2) Center for Medication Safety and Service Quality, Hammersmith Hospitals NHS Trust and The School of Pharmacy, University of London, London, UK |
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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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