Machine learning can classify vital sign alerts as real or artifact in online continuous monitoring data

M Hravnak; L Chen; A Dubrawski; D Wang; E Bose; G Clermont; AM Kaynar; D Wallace; A Holder; MR Pinsky

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Machine learning can classify vital sign alerts as real or artifact in online continuous monitoring data

机译：机器学习可以将生命体征警报分类为在线连续监视数据中的真实警报或人工警报

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《Intensive Care Medicine Experimental》 |2015年第s1期|共页
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M Hravnak; L Chen; A Dubrawski; D Wang; E Bose; G Clermont; AM Kaynar; D Wallace; A Holder; MR Pinsky;
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中图分类护理学;
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入库时间 2022-08-18 08:43:28

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1. Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data [J] . Chen Lujie, Dubrawski Artur, Wang Donghan, Critical care medicine . 2016,第7期

机译：使用监督机器学习对在线多信号生命体征监测数据中的真实警报和伪像进行分类
2. Real alerts and artifact classification in archived multi-signal vital sign monitoring data: implications for mining big data [J] . Hravnak Marilyn, Chen Lujie, Dubrawski Artur, Journal of clinical monitoring and computing . 2016,第6期

机译：归档的多信号生命体征监测数据中的实时警报和伪影分类：对挖掘大数据的影响
3. Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach [J] . Castineira David, Schlosser Katherine R., Geva Alon, Respiratory care . 2020,第9期

机译：将连续生命标志信息添加到静态临床数据中，提高了插管后的逗留时间的预测：数据驱动的机器学习方法
4. Energy efficient sensors data stream model for real-time and continuous vital signs monitoring [C] . Todor Ivaşcu, Marc Frîncu, Viorel Negru International Symposium on INnovations in Intelligent SysTems and Applications . 2016

机译：节能传感器数据流模型，用于实时连续监测生命体征
5. MobiEye: An Approach towards Ubiquitous Smart Health Platform for Continuous User Identification and Vital Sign Monitoring [D] . Patil, Omkar Ramesh. 2020

机译：Mobieye：用于连续用户识别和生命符号监测的普遍存在智能卫生平台的一种方法
6. Machine learning can classify vital sign alerts as real or artifact in online continuous monitoring data [O] . M Hravnak, L Chen, A Dubrawski, 2015

机译：机器学习可以将生命体征警报分类为在线连续监控数据中的真实警报或人工警报
7. Machine learning can classify vital sign alerts as real or artifact in online continuous monitoring data [O] . 2015

机译：机器学习可以将生命体征警报分类为在线连续监控数据中的真实警报或人工警报
8. Computational Gene Mapping to Analyze Continuous Automated Real-Time Vital Signs Monitoring Data. [R] . Stansbury, L., Miller, C., Yang, S., 2013

机译：计算基因图谱分析连续自动实时生命体征监测数据。

Machine learning can classify vital sign alerts as real or artifact in online continuous monitoring data

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