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

  • Matt-Mouley Bouamrane
  • Alan Rector
  • Martin Hurrell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6497)


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.


Decision Support System Clinical Decision Support System Risk Grade Automate Inference Computerize Clinical Decision Support System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Matt-Mouley Bouamrane
    • 1
  • Alan Rector
    • 2
  • Martin Hurrell
    • 3
  1. 1.College of Medical, Veterinary and Life Sciences, Centre for Population and Health SciencesUniversity of GlasgowScotland, U.K.
  2. 2.School of Computer ScienceManchester UniversityU.K.
  3. 3.CIS InformaticsGlasgowScotland, U.K.

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