Bernard, J, Sessler, D, Kohlhammer, J et al. (1 more author) (2019) Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-operative Prostate Cancer. IEEE Transactions on Visualization and Computer Graphics, 25 (3). pp. 1615-1628. ISSN 1077-2626
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018, IEEE. This is an author produced version of a paper published in IEEE Transactions on Visualization and Computer Graphics. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher’s self-archiving policy. |
Keywords: | Information Visualization, Visual Analytics, Multivariate Data Visualization, Electronic Health Care Records, Medical Data Analysis, Prostate Cancer Disease, Design Study, User Study, Evaluation, Static Dashboard, Dashboard Network |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Mar 2018 17:11 |
Last Modified: | 20 Feb 2019 15:39 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/TVCG.2018.2803829 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:128739 |