Bernard, Jürgen ; Sessler, David ; Kohlhammer, Jörn ; 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, 25 (3)
doi: 10.1109/TVCG.2018.2803829
Artikel, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Bernard, Jürgen ; Sessler, David ; Kohlhammer, Jörn ; Ruddle, Roy A. |
| Art des Eintrags: | Bibliographie |
| Titel: | Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-Operative Prostate Cancer |
| Sprache: | Englisch |
| Publikationsjahr: | 2019 |
| Verlag: | IEEE |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Transactions on Visualization and Computer Graphics |
| Jahrgang/Volume einer Zeitschrift: | 25 |
| (Heft-)Nummer: | 3 |
| DOI: | 10.1109/TVCG.2018.2803829 |
| URL / URN: | https://doi.org/10.1109/TVCG.2018.2803829 |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | Information visualization, Visual analytics, Multivariate data, Data visualization, User study, Evaluation |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 10 Jul 2019 11:23 |
| Letzte Änderung: | 10 Jul 2019 11:23 |
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