Hypothesis Generation by Interactive Visual Exploration of Heterogeneous Medical Data

  • Cagatay Turkay
  • Arvid Lundervold
  • Astri Johansen Lundervold
  • Helwig Hauser
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7947)


High dimensional, heterogeneous datasets are challenging for domain experts to analyze. A very large number of dimensions often pose problems when visual and computational analysis tools are considered. Analysts tend to limit their attention to subsets of the data and lose potential insight in relation to the rest of the data. Generating new hypotheses is becoming problematic due to these limitations. In this paper, we discuss how interactive analysis methods can help analysts to cope with these challenges and aid them in building new hypotheses. Here, we report on the details of an analysis of data recorded in a comprehensive study of cognitive aging. We performed the analysis as a team of visualization researchers and domain experts. We discuss a number of lessons learned related to the usefulness of interactive methods in generating hypotheses.


interactive visual analysis high dimensional medical data 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Cagatay Turkay
    • 1
  • Arvid Lundervold
    • 2
  • Astri Johansen Lundervold
    • 3
  • Helwig Hauser
    • 1
  1. 1.Department of InformaticsUniversity of BergenNorway
  2. 2.Department of BiomedicineUniversity of BergenNorway
  3. 3.Department of Biological and Medical PsychologyUniversity of BergenNorway

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