Knowledge-assisted visual analytics: data exploration and insight generation of health care data
Master Thesis
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Abstract |
The research area "Knowledge-Assisted Visual Analytics" (KAVA) deals with the integration of domain knowledge into Visual Analytics approaches which offers many advantages for research as well as for the analysis of data since analysts do not need to rely on their domain knowledge and can concentrate more on the analysis task itself. Especially in the health care sector, KAVA has great potential which is currently not fully exploited since there are only a few approaches that deal with KAVA in combination with health care data. To fill this gap, we propose a new KAVA approach dealing with a dataset that resulted from a clinical trial of a medication for treating the eye disease Uveitis to provide the possibility of exploring and analyzing the dataset. For designing and developing the approach a user-centered design process, involving a domain expert, in combination with problem-driven visualization research is applied. The final approach is validated using a qualitative task-oriented user study with five visualization experts. The results suggest that the approach is able to support the analysis as well as exploration of the dataset. |
Year of Publication |
2021
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Secondary Title |
Institute of Visual Computing and Human-Centered Technology
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Number of Pages |
94
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Publisher |
TU Wien
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Place Published |
Vienna
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DOI |
10.34726/hss.2021.80701
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