Visual Assistance in Clinical Decision Support
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Clinical decision-making for complex diseases such as cancer aims at finding the right diagnosis, optimal treatment or best aftercare for a specific patient. The decision-making process is very challenging due to the distributed storage of patient information entities in multiple hospital information systems, the required inclusion of multiple clinical disciplines with their different views of disease and therapy, and the multitude of available medical examinations, therapy options and aftercare strategies. Clinical Decision Support Systems (CDSS) address these difficulties by presenting all relevant information entities in a concise manner and providing a recommendation based on interdisciplinary disease- and patient-specific models of diagnosis and treatment. This work summarizes our research on visual assistance for therapy decision-making. We aim at supporting the preparation and implementation of expert meetings discussing cancer cases (tumor boards) and the aftercare consultation. In very recent work, we started to address the generation of models underlying a CDSS. The developed solutions combine state-of-the-art interactive visualizations with methods from statistics, machine learning and information organization.
Description
@inproceedings{10.2312:evm.20211075,
booktitle = {EuroVis 2021 - Dirk Bartz Prize},
editor = {Oeltze-Jafra, Steffen and Raidou, Renata Georgia},
title = {{Visual Assistance in Clinical Decision Support}},
author = {Müller, Juliane and Cypko, Mario and Oeser, Alexander and Stoehr, Matthäus and Zebralla, Veit and Schreiber, Stefanie and Wiegand, Susanne and Dietz, Andreas and Oeltze-Jafra, Steffen},
year = {2021},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-147-2},
DOI = {10.2312/evm.20211075}
}