,

Chih-Fan Kuo1,2,3, Cheng-Yu Tsai4,5, Wun-Hao Cheng6,7

  • 1School of Medicine, China Medical University, Taichung City, Taichung, Taiwan.

Digital health
|October 17, 2023
PubMed
概括

这项研究使用心率变化和氧和来预测睡眠唤醒,这是阻塞性睡眠呼吸暂停查的关键. 机器学习模型确定了特定的心率模式作为兴奋的关键预测因素.

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