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