Personalized Information Services for Quality of Life: The Case of Airborne Pollen Induced Symptoms

  • Dimitris Voukantsis
  • Kostas Karatzas
  • Siegfried Jaeger
  • Uwe Berger
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 363)

Abstract

Allergies due to airborne pollen affect approximately 15-20% of European citizens; therefore, the provision of health related services concerning pollen-induced symptoms can improve the overall quality of life. In this paper, we demonstrate the development of personalized quality of life services by adopting a data-driven approach. The data we use consist of allergic symptoms reported by citizens as well as detailed pollen concentrations of the most allergenic taxa. We apply computational intelligence methods in order to develop models that associate pollen concentration levels with allergic symptoms on a personal level. The results for the case of Austria, show that this approach can result to accurate and reliable models; we report a correlation coefficient up to r=0.70 (average of 102 citizens). We conclude that some of these models could serve as the basis for personalized health services.

Keywords

Allergy Computational Intelligence Personalized Health Services 

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Copyright information

© International Federation for Information Processing 2011

Authors and Affiliations

  • Dimitris Voukantsis
    • 1
  • Kostas Karatzas
    • 1
  • Siegfried Jaeger
    • 2
  • Uwe Berger
    • 2
  1. 1.Informatics Systems & Applications Group, Dept. of Mechanical EngineeringAristotle UniversityThessalonikiGreece
  2. 2.Medizinische Universität WienUniversitätsklinik für Hals-, Nasen- und OhrenkrankheitenWienAustria

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