A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring
A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring
复制标题
分层切换线性动力系统应用于新生儿病情监测中败血症的检测
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Y. Freer
中科院分区：
文献类型：
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作者：
Ioan Stanculescu;Christopher K. I. Williams;Y. Freer
在本文中，我们开发了一个分层切换线性动力学系统（HSLDS）的检测新生儿败血症在重症监护病房。Quinn等人（2009）的因子转换LDS（FSLDS）能够根据许多离散因子描述观察到的生命体征数据，这些离散因子具有生理或人为来源。在本文中，我们证明，通过添加一个更高级别的离散变量与语义脓毒症/非脓毒症，我们可以检测到的生理因素的变化，信号脓毒症的存在。我们证明，我们的模型用于检测脓毒症的性能与Stanculescu等人（2013）的自回归HMM没有统计学差异，尽管他们的模型被赋予生理因素的“地面实况”注释，而我们的HSLDS必须从原始生命体征数据中推断它们。
In this paper we develop a Hierarchical Switching Linear Dynamical System (HSLDS) for the detection of sepsis in neonates in an intensive care unit. The Factorial Switching LDS (FSLDS) of Quinn et al. (2009) is able to describe the observed vital signs data in terms of a number of discrete factors, which have either physiological or artifactual origin. In this paper we demonstrate that by adding a higher-level discrete variable with semantics sepsis/non-sepsis we can detect changes in the physiological factors that signal the presence of sepsis. We demonstrate that the performance of our model for the detection of sepsis is not statistically different from the auto-regressive HMM of Stanculescu et al. (2013), despite the fact that their model is given "ground truth" annotations of the physiological factors, while our HSLDS must infer them from the raw vital signs data.
影响因子：
5.1
作者：
Moorman, Joseph Randall;Carlo, Waldemar A.;Kattwinkel, John;Schelonka, Robert L.;Porcelli, Peter J.;Navarrete, Christina T.;Bancalari, Eduardo;Aschner, Judy L.;Walker, Marshall Whit;Perez, Jose A.;Palmer, Charles;Stukenborg, George J.;Lake, Douglas E.;O'Shea, Thomas Michael
通讯作者：
O'Shea, Thomas Michael