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新的统计时间序列数据增强和基于机器学习的简单呼吸数据的分类用于呼吸数字双胞胎模型

Sagheer Khan1, Aaesha Alzaabi1, Tharmalingam Ratnarajah1

  • 1School of Engineering, The University of Edinburgh, Edinburgh EH9 3FF, UK.

Computers in biology and medicine
|December 7, 2023
PubMed
概括

本研究引入了一种新的数据增强方法,用于创建合成呼吸数据,用于开发用于呼吸监测的数字双胞胎 (DT). 该方法提高了机器学习模型的准确性,以改善医疗保健决策.

关键词:
数据增强数据增强数据处理数据处理.数字双胞胎 数字双胞胎 数字双胞胎机器学习 机器学习呼吸率是指呼吸速率.没有Wi-Fi的CSI.

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