Visualization and classification of physiological failure modes in ensemble hemorrhage simulation

Song Zhang; William Andrew Pruett; Robert Hester

doi:10.1117/12.2080136

8 February 2015 Visualization and classification of physiological failure modes in ensemble hemorrhage simulation

Song Zhang, William Andrew Pruett, Robert Hester

Proceedings Volume 9397, Visualization and Data Analysis 2015; 93970O (2015) https://doi.org/10.1117/12.2080136
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

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.

Citation Download Citation

Song Zhang, William Andrew Pruett, and Robert Hester "Visualization and classification of physiological failure modes in ensemble hemorrhage simulation", Proc. SPIE 9397, Visualization and Data Analysis 2015, 93970O (8 February 2015); https://doi.org/10.1117/12.2080136

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