Ontology-Driven Adaptive Medical Information Collection System

  • Matt-Mouley Bouamrane
  • Alan Rector
  • Martin Hurrell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4994)


Computer-based surveys and questionnaires have become ubiquitous. Yet in many cases, Information Collection Systems (ICS) offer limited support in terms of tailoring structure and content of surveys in response to user interaction. Previous techniques for content adaptation such as conditional branching do not scale well and are also hard to maintain as structural dependencies in a survey often need to be hard-coded in the system. We here propose a generic model for context-sensitive self adaptation of ICS, based on a questionnaire ontology. We illustrate the model with a description of our own medical ICS implementation and discuss the potential benefits of such system, especially in the context of tailored healthcare.


Adaptive Property Medical Questionnaire Question Class Patient Medical History Answer Class 
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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  1. 1.
    Couper, M.P.: Usability evaluation of computer-assisted survey instruments. Social Science Computer Review 18(4), 384–396 (2000)Google Scholar
  2. 2.
    Norman, K.L., Friedman, Z., Norman, K., Stevenson, R.: Navigational issues in the design of online self-administered questionnaires. Behaviour & Information Technology 20(1), 37–45 (2001)CrossRefGoogle Scholar
  3. 3.
    Bachman, J.W.: The patient-computer interview: a neglected tool that can aid the clinician. Mayo Clinic Proceedings 78, 67–78 (2003)CrossRefGoogle Scholar
  4. 4.
    Jameson, A.: Adaptive interfaces and agents, 305–330 (2003)Google Scholar
  5. 5.
    van Ginneken, A.M., de Wilde, M., Blok, C.: Generic computer-based questionnaires: an extension to opensde. In: Proceedings of 11th World Congress on Medical Informatics, MEDINFO, pp. 688–692 (2004)Google Scholar
  6. 6.
    Vahabzadeh, M., Epstein, D., Mezghanni, M., Lin, J.L., Preston, K.: An electronic diary software for ecological momentary assessment (EMA) in clinical trials. In: Proceedings of 17th IEEE Symposium on Computer-Based Medical Systems, CBMS 2004, Bethesda, US, pp. 167–172. IEEE Computer Society, Los Alamitos (2004)CrossRefGoogle Scholar
  7. 7.
    Gómez-Pérez, A., Fernández-López, M., Corcho, O.: Ontological Engineering. Advanced Information and Knowledge Processing series. Springer, Heidelberg (2003)Google Scholar
  8. 8.
    Yu, A.: Methods in biomedical ontology. Journal of Biomedical Informatics 39(3), 252–266 (2006)CrossRefGoogle Scholar
  9. 9.
    Horrocks, I., Patel-Schneider, P., van Harmelen, F.: From SHIQ and RDF to OWL: The making of a web ontology language. Journal of Web Semantics 1(1), 7–26 (2003)Google Scholar
  10. 10.
    Knublauch, H., Fergerson, R.W., Noy, N.F., Musen, M.A.: The Protégé OWL Plugin: An Open Development Environment for Semantic Web Applications. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 229–243. Springer, Heidelberg (2004)Google Scholar
  11. 11.
    Horridge, M., Bechhofer, S., Noppens, O.: Igniting the owl 1.1 touch paper: The owl api. In: Proceedings of the third International Workshop of OWL Experiences and Directions, OWLED 2007, Innsbruck, Austria (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Matt-Mouley Bouamrane
    • 1
    • 2
  • Alan Rector
    • 1
  • Martin Hurrell
    • 2
  1. 1.School of Computer ScienceManchester UniversityUK
  2. 2.CIS InformaticsGlasgowUK

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