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Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-Operative Prostate Cancer

Bernard, Jürgen and Sessler, David and Kohlhammer, Jörn and Ruddle, Roy A. (2019):
Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-Operative Prostate Cancer.
In: IEEE Transactions on Visualization and Computer Graphics, IEEE, pp. 1615-1628, 25, (3), ISSN 1077-2626,
DOI: 10.1109/TVCG.2018.2803829,
[Online-Edition: https://doi.org/10.1109/TVCG.2018.2803829],
[Article]

Abstract

In this design study, we present a visualization technique that segments patients' histories instead of treating them as raw event sequences, aggregates the segments using criteria such as the whole history or treatment combinations, and then visualizes the aggregated segments as static dashboards that are arranged in a dashboard network to show longitudinal changes. The static dashboards were developed in nine iterations, to show 15 important attributes from the patients' histories. The final design was evaluated with five non-experts, five visualization experts and four medical experts, who successfully used it to gain an overview of a 2,000 patient dataset, and to make observations about longitudinal changes and differences between two cohorts. The research represents a step-change in the detail of large-scale data that may be successfully visualized using dashboards, and provides guidance about how the approach may be generalized.

Item Type: Article
Erschienen: 2019
Creators: Bernard, Jürgen and Sessler, David and Kohlhammer, Jörn and Ruddle, Roy A.
Title: Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-Operative Prostate Cancer
Language: English
Abstract:

In this design study, we present a visualization technique that segments patients' histories instead of treating them as raw event sequences, aggregates the segments using criteria such as the whole history or treatment combinations, and then visualizes the aggregated segments as static dashboards that are arranged in a dashboard network to show longitudinal changes. The static dashboards were developed in nine iterations, to show 15 important attributes from the patients' histories. The final design was evaluated with five non-experts, five visualization experts and four medical experts, who successfully used it to gain an overview of a 2,000 patient dataset, and to make observations about longitudinal changes and differences between two cohorts. The research represents a step-change in the detail of large-scale data that may be successfully visualized using dashboards, and provides guidance about how the approach may be generalized.

Journal or Publication Title: IEEE Transactions on Visualization and Computer Graphics
Volume: 25
Number: 3
Publisher: IEEE
Uncontrolled Keywords: Information visualization, Visual analytics, Multivariate data, Data visualization, User study, Evaluation
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 10 Jul 2019 11:23
DOI: 10.1109/TVCG.2018.2803829
Official URL: https://doi.org/10.1109/TVCG.2018.2803829
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