首页> 外文会议>2018 International Conference on Artificial Intelligence and Big Data >Analysis of cardiorespiratory interaction in patients submitted to the T-tube test in the weaning process implementing symbolic dynamics and neural networks
【24h】

Analysis of cardiorespiratory interaction in patients submitted to the T-tube test in the weaning process implementing symbolic dynamics and neural networks

机译:断奶过程中采用符号动力学和神经网络进行T管测试的患者的心肺交互作用分析

获取原文
获取原文并翻译 | 示例

摘要

The determination of the optimal time of the patients in weaning trial process from Mechanical Ventilation (MV), between patients capable of maintaining spontaneous breathing and patients that fail to maintain spontaneous breathing, is a very important task in intensive care unit. Symbolic Dynamic (SD) and Neural Networks (NN) techniques were applied in order to develop a classifier for the study of patients on weaning trial process. The respiratory pattern of each patient was characterized through different time series. In order to reduce the dimensionality of the system Forward Selection is implemented, obtaining a classification performance result of 85,96 ±6,26% with 64 variables differentiating between 3 classes analyzed at same time.
机译:在重症监护病房中,根据机械通气(MV)来确定能够自动呼吸的患者与不能自动呼吸的患者之间断奶试验过程中患者的最佳时间是一项非常重要的任务。为了开发一种用于对断奶试验过程中的患者进行研究的分类器,应用了符号动态(SD)和神经网络(NN)技术。通过不同的时间序列来表征每个患者的呼吸模式。为了降低系统的维数,实现了前向选择,获得了分类性能结果为85,96±6,26 \\%,其中64个变量同时区分了3个类别。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号