由计算机模拟生理学驱动的下一代患者监护仪。
Next generation patient monitor powered by in-silico physiology.
作者信息
Baronov Dimitar, McManus Michael, Butler Evan, Chung Douglas, Almodovar Melvin C
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:4447-53. doi: 10.1109/EMBC.2015.7319382.
Abstract
The goal of this paper is to introduce a next generation patient monitoring technology that relies on objective and continuous data analytics to alleviate the data overload in the critical care unit. The technology provides the foundation for increasing the consistency and efficacy of data use in clinical practice and improving outcomes. This paper presents results for applying the approach to the hemodynamic monitoring of infants immediately following cardiac surgery and demonstrates its efficacy of estimating the probability of inadequate systemic oxygen delivery, which is an essential risk attribute in the management of critically ill patients.
摘要
本文的目标是介绍一种下一代患者监测技术，该技术依靠客观且持续的数据分析来缓解重症监护病房的数据过载问题。这项技术为提高临床实践中数据使用的一致性和有效性以及改善治疗结果奠定了基础。本文展示了将该方法应用于心脏手术后婴儿血流动力学监测的结果，并证明了其在估计全身氧输送不足概率方面的有效性，而全身氧输送不足概率是重症患者管理中的一项关键风险指标。
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