OSA

Ali Mohammad Alqudah1, Walid Ashraf1, Brian Lithgow1,2,3,4

  • 1Biomedical Engineering Program, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

PubMed
概括

这项研究开发了一种非侵入性机器学习模型,使用气管呼吸声音和人体测量数据来分类阻塞性睡眠呼吸暂停 (OSA) 的严重程度. 该方法提供了一个可扩展和可访问的方法,用于较早的OSA检测,而不是传统的多睡眠学.

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