Ring-Topology Echo State Networks for ICU Sepsis Classification

M. Alfaras, Rui Varandas, H. Gamboa
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引用次数: 4

Abstract

Sepsis is a life threatening condition that can be treated if detected early. This paper presents a study of the application of a Ring Topology Echo State Network (ESN) algorithm to a sepsis prediction task based on ICU records. The implemented algorithm is compared with commonly used classifiers and a combination of both approaches. Finally, we address how different causal strategies on filling missing record values affected the final classification performances. Having a dataset with a limited number of time entries per patient, the utility score U = 0.188 obtained (team 51: PLUX) suggests that further research is needed in order for the ESN to capture the temporal dynamics of the problem at hand.
环状拓扑回声状态网络用于ICU脓毒症分类
败血症是一种威胁生命的疾病,如果及早发现可以治疗。本文研究了环形拓扑回声状态网络(ESN)算法在基于ICU记录的脓毒症预测任务中的应用。将实现的算法与常用的分类器以及两种方法的组合进行了比较。最后,我们讨论了填充缺失记录值的不同因果策略如何影响最终的分类性能。拥有一个数据集,每个病人的时间条目数量有限,获得的效用得分U = 0.188(小组51:PLUX)表明,需要进一步的研究,以便回声状态网络捕捉手头问题的时间动态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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