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Hypothesis generation by interactive visual exploration of heterogeneous medical data

Turkay, C., Lundervold, A., Lundervold, A. J. & Hauser, H. (2013). Hypothesis generation by interactive visual exploration of heterogeneous medical data. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Third International Workshop, HCI-KDD 2013, 1 July 2013 - 3 July 2013, Maribor, Slovenia.

Abstract

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.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: The final publication is available at link.springer.com
Publisher Keywords: interactive visual analysis, high dimensional medical data
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science
School of Science & Technology > Computer Science > giCentre
Related URLs:
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