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

Bouamrane, M.M., Rector, A. and Hurrell, M. (2011) Using OWL ontologies for adaptive patient information modelling and preoperative clinical decision support. Knowledge and Information Systems, 29(2), pp. 405-418. (doi:10.1007/s10115-010-0351-7)

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Publisher's URL: http://dx.doi.org/10.1007/s10115-010-0351-7

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 systems 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 patient's reports consisting of a risk assessment and clinical recommendations such as relevant preoperative tests.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Bouamrane, Dr Matt-Mouley
Authors: Bouamrane, M.M., Rector, A., and Hurrell, M.
College/School:College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing > Centre for Population and Health Sciences
College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > General Practice and Primary Care
Journal Name:Knowledge and Information Systems
ISSN:0219-1377
Published Online:22 October 2010

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