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Authors: Shenhui Jiang 1 ; Shiaofen Fang 1 ; Sam Bloomquist 1 ; Jeremy Keiper 1 ; Mathew Palakal 1 ; Yuni Xia 1 and Shaun Grannis 2

Affiliations: 1 Indiana University Purdue University Indianapolis, United States ; 2 Indiana University School of Medicine, United States

Keyword(s): Healthcare Data, Spatiotemporal Visualization, Geospatial Information Visualization, Data and Text Mining, Web-based Visualization Systems.

Related Ontology Subjects/Areas/Topics: Biomedical Visualization and Applications ; Computer Vision, Visualization and Computer Graphics ; General Data Visualization ; Large Data Visualization ; Spatial Data Visualization ; Time-Dependent Visualization

Abstract: Healthcare data visualization is challenging due to the needs for integrating geospatial information, temporal information, text information, and heterogenious health attributes within a common visual context. We recently developed a web-based healthcare data visualization system, Health-Terrain, based on a Notifiable Condition Detector (NCD) use case. In this paper, we will describe this system, with emphasis on the visualization techniques developed specifically for healthcare data. Two new visualization techniques will be described: (1) A spatial texture based visualization approach for multi-dimensional attributes and time-series data; (2) A spiral theme plot technique for visualizing time-variant patient data.

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Paper citation in several formats:
Jiang, S.; Fang, S.; Bloomquist, S.; Keiper, J.; Palakal, M.; Xia, Y. and Grannis, S. (2016). Healthcare Data Visualization: Geospatial and Temporal Integration. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - IVAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 212-219. DOI: 10.5220/0005714002120219

@conference{ivapp16,
author={Shenhui Jiang. and Shiaofen Fang. and Sam Bloomquist. and Jeremy Keiper. and Mathew Palakal. and Yuni Xia. and Shaun Grannis.},
title={Healthcare Data Visualization: Geospatial and Temporal Integration},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - IVAPP},
year={2016},
pages={212-219},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005714002120219},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - IVAPP
TI - Healthcare Data Visualization: Geospatial and Temporal Integration
SN - 978-989-758-175-5
IS - 2184-4321
AU - Jiang, S.
AU - Fang, S.
AU - Bloomquist, S.
AU - Keiper, J.
AU - Palakal, M.
AU - Xia, Y.
AU - Grannis, S.
PY - 2016
SP - 212
EP - 219
DO - 10.5220/0005714002120219
PB - SciTePress

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