Interactive Visualization of Machine Learning Model Results Predicting Infection Risk

Abstract
We present a novel visual-interactive interface to show results of a machine learning algorithm, which predicts the infection probability for patients in hospitals. The model result data is complex and needs to be presented in a clear and intuitive way to microbiology and infection control experts in hospitals. Our visual-interactive interface offers linked views which allow for detailed analysis of the model results. Feedback from microbiology and infection control experts showed that they were able to extract new insights regarding outbreaks and transmission pathways.
Description

CCS Concepts: Human-centered computing --> Visual analytics; Computing methodologies --> Artificial intelligence

        
@inproceedings{
10.2312:evp.20221113
, booktitle = {
EuroVis 2022 - Posters
}, editor = {
Krone, Michael
and
Lenti, Simone
and
Schmidt, Johanna
}, title = {{
Interactive Visualization of Machine Learning Model Results Predicting Infection Risk
}}, author = {
Schäfer, Steffen
and
Baumgartl, Tom
and
Wulff, Antje
and
Kuijper, Arjan
and
Marschollek, Michael
and
Scheithauer, Simone
and
von Landesberger, Tatiana
}, year = {
2022
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-03868-185-4
}, DOI = {
10.2312/evp.20221113
} }
Citation