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Interactive Visual Analysis of Heterogeneous Cohort Study Data
PrePrint
ISSN: 0272-1716
Paolo Angelelli, University of Bergen, Bergen
Steffen Oeltze, University of Magdeburg, Magdeburg
Cagatay Turkay, University of Bergen, Bergen
Judit Haasz, University of Bergen, Bergen
Erlend Hodneland, University of Bergen, Bergen
Arvid Lundervold, University of Bergen, Bergen
Astri Lundervold, University of Bergen, Bergen
Bernhard Preim, University of Magdeburg, Magdeburg
Helwig Hauser, University of Bergen, Bergen
Cohort studies are used in medicine to enable the study of medical hypotheses in large samples. Often, a large amount of heterogeneous data is acquired from many subjects. The analysis is usually hypothesis-driven, i.e., a specific subset of such data is studied to confirm or reject specific hypotheses. In this paper, we demonstrate how we enable the interactive visual exploration and analysis of such data, helping with the generation of new hypotheses and contributing to the process of validating them. We propose a data-cube based model which allows to handle partially overlapping data subsets during the interactive visualization. This model enables the seamless integration of the heterogeneous data, as well as the linking of spatial and non-spatial views on these data. We implemented this model in an application prototype, and used it to analyze data acquired in the context of a cohort study on cognitive aging. In this paper we present a case-study analysis of selected aspects of brain connectivity by using a prototype implementation of the presented model, to demonstrate its potential and flexibility.
Citation:
Paolo Angelelli, Steffen Oeltze, Cagatay Turkay, Judit Haasz, Erlend Hodneland, Arvid Lundervold, Astri Lundervold, Bernhard Preim, Helwig Hauser, "Interactive Visual Analysis of Heterogeneous Cohort Study Data," IEEE Computer Graphics and Applications, 18 April 2014. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/MCG.2014.40>
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