首页> 外文会议> >Neural network evaluation of slopes from sequential volume segments of expiratory carbon dioxide curves
【24h】

Neural network evaluation of slopes from sequential volume segments of expiratory carbon dioxide curves

机译:神经网络评估呼气二氧化碳曲线的连续体积分段的斜率

获取原文

摘要

Capnography is currently used to evaluate respiratory efficiency in monitored patients with indirect indications of alveolar dead space and the distribution of ventilation perfusion ratios. However, it has not been associated with the typical spirometric values and associated pulmonary obstructive processes. The purpose of this study was to determine if specific segments of the capnogram could be more closely associated with the status of airway obstruction. Two fully connected ANNs were used to compute forced expiratory volume and forced vital capacity.
机译:二氧化碳描记法目前用于评估受监测患者的呼吸效率,这些患者具有肺泡死腔的间接指征和通气灌注比的分布。但是,它与典型的肺活量测定值和相关的肺阻塞过程无关。这项研究的目的是确定二氧化碳图的特定部分是否与气道阻塞的状况更紧密相关。两个完全连接的人工神经网络用于计算强制呼气量和强制肺活量。

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