An Architecture for Semantic Navigation and Reasoning with Patient Data - Experiences of the Health-e-Child Project

  • Tamás Hauer
  • Dmitry Rogulin
  • Sonja Zillner
  • Andrew Branson
  • Jetendr Shamdasani
  • Alexey Tsymbal
  • Martin Huber
  • Tony Solomonides
  • Richard McClatchey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5318)


Medical ontologies have become the standard means of recording and accessing conceptualized biological and medical knowledge. The expressivity of these ontologies goes from simple concept lists through taxonomies to formal logical theories. In the context of patient information, their application is primarily annotation of medical (instance) data. To exploit higher expressivity, we propose an architecture which allows for reasoning on patient data using OWL DL ontologies. The implementation is carried out as part of the Health-e-Child platform prototype. We discuss the use case where ontologies establish a hierarchical classification of patients which in turn is used to aid the visualization of patient data. We briefly discuss the treemap-based patient viewer which has been evaluated in the Health-e-Child project.


Clinical Decision Support External Knowledge Regional Part Temporal Abstraction Platform Prototype 
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 2008

Authors and Affiliations

  • Tamás Hauer
    • 1
  • Dmitry Rogulin
    • 1
  • Sonja Zillner
    • 2
  • Andrew Branson
    • 1
  • Jetendr Shamdasani
    • 1
  • Alexey Tsymbal
    • 2
  • Martin Huber
    • 2
  • Tony Solomonides
    • 1
  • Richard McClatchey
    • 1
  1. 1.CCS Research Centre, CEMS FacultyUniversity of the West of England Coldharbour Lane, FrenchayBristolUK
  2. 2.Corporate Technology DivisionSiemens AGGermany

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