Visualization and Classification of Physiological Failure Modes in Ensemble Hemorrhage Simulation

被引:0
|
作者
Zhang, Song [1 ]
Pruett, William Andrew [2 ]
Hester, Robert [2 ]
机构
[1] Mississippi State Univ, Comp Sci & Engn, Mississippi State, MS 39762 USA
[2] Univ Mississippi, Med Ctr, Jackson, MS 39216 USA
来源
基金
美国国家科学基金会;
关键词
Physiology; ensemble; simulation; prediction; failure; visualization; EFFICIENT ALGORITHM;
D O I
10.1117/12.2080136
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
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页数:8
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