Visual Analytics for Epidemiology
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Date
2019Author
Preim, Bernhard 
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We present visual analytics methods to analyze epidemiologic cohort studies. We consider the automatic identification of strong correlations and of subgroups that deviate from the global mean with respect to their risk for health disorders. Moreover, we tackle missing value problems and discuss appropriate imputation strategies and visual analytics support.
BibTeX
@inproceedings {10.2312:egm.20191034,
booktitle = {Eurographics 2019 - Dirk Bartz Prize},
editor = {Bruckner, Stefan and Oeltze-Jafra, Steffen},
title = {{Visual Analytics for Epidemiology}},
author = {Preim, Bernhard and Alemzadeh, Shiva and Ittermann, Till and Klemm, Paul and Niemann, Uli and Spiliopoulou, Myra},
year = {2019},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
DOI = {10.2312/egm.20191034}
}
booktitle = {Eurographics 2019 - Dirk Bartz Prize},
editor = {Bruckner, Stefan and Oeltze-Jafra, Steffen},
title = {{Visual Analytics for Epidemiology}},
author = {Preim, Bernhard and Alemzadeh, Shiva and Ittermann, Till and Klemm, Paul and Niemann, Uli and Spiliopoulou, Myra},
year = {2019},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
DOI = {10.2312/egm.20191034}
}