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Proceedings Paper

Visualization and classification of physiological failure modes in ensemble hemorrhage simulation
Author(s): Song Zhang; William Andrew Pruett; Robert Hester
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Paper Abstract

In an emergency situation such as hemorrhage, doctors need to predict which patients need immediate treatment and care. This task is difficult because of the diverse response to hemorrhage in human population. Ensemble physiological simulations provide a means to sample a diverse range of subjects and may have a better chance of containing the correct solution. However, to reveal the patterns and trends from the ensemble simulation is a challenging task. We have developed a visualization framework for ensemble physiological simulations. The visualization helps users identify trends among ensemble members, classify ensemble member into subpopulations for analysis, and provide prediction to future events by matching a new patient’s data to existing ensembles. We demonstrated the effectiveness of the visualization on simulated physiological data. The lessons learned here can be applied to clinically-collected physiological data in the future.

Paper Details

Date Published: 8 February 2015
PDF: 8 pages
Proc. SPIE 9397, Visualization and Data Analysis 2015, 93970O (8 February 2015); doi: 10.1117/12.2080136
Show Author Affiliations
Song Zhang, Mississippi State Univ. (United States)
William Andrew Pruett, The Univ. of Mississippi Medical Ctr. (United States)
Robert Hester, The Univ. of Mississippi Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 9397:
Visualization and Data Analysis 2015
David L. Kao; Ming C. Hao; Mark A. Livingston; Thomas Wischgoll, Editor(s)

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