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相关概念视频

Sleep Apnea01:21

Sleep Apnea

483
Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
The condition is more prevalent among...
483

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Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea
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深度神经网络算法使用心电图检测阻塞性睡眠呼吸暂停.

Naima Covassin1, Kan Liu1, Jan Bukartyk1

  • 1Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.

JACC. Advances
|September 17, 2025
PubMed
概括

一个新的人工智能 (AI) -ECG算法有效地使用常规心电图来选阻塞性睡眠呼吸暂停 (OSA). 这种AI-ECG工具对广泛的,低成本的OSA查,特别是对女性的查充满了希望.

关键词:
人工智能的人工智能是人工智能.卷积神经网络是一种卷积神经网络.电心电图 (ECG) 是一种心电图.机器学习是机器学习.阻塞性睡眠呼吸暂停症是什么

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科学领域:

  • 心脏病学 心脏病学
  • 睡眠医学 睡眠医学
  • 人工智能的人工智能

背景情况:

  • 阻塞性睡眠呼吸暂停 (OSA) 非常普遍,但往往被诊断不足.
  • 有效的查工具对于早期发现和管理OSA至关重要.

研究的目的:

  • 开发和评估一种基于机器学习的算法,用于从12导电心电图 (ECG) 中识别OSA.
  • 在大量临床人群中评估AI-ECG模型的诊断性能.

主要方法:

  • 训练了一种深度卷积神经网络模型,从11,299名患者的12导电图数据中检测OSA.
  • 模型的预测性能使用接收器运行特征曲线 (AUC) 下的面积来评估.
  • 评估了整体人口的表现,并按性别分层.

主要成果:

  • 在AI-ECG模型中,在测试样本中检测OSA的AUC达到0.80.
  • 该模型在女性 (AUC:0.82) 与男性 (AUC:0.73) 相比,显示出更高的歧视性表现.
  • 算法的预测能力在各种条件和心电图异常中保持稳健.

结论:

  • 开发的AI-ECG模型显示了作为OSA的非侵入性查工具的巨大潜力.
  • 这项技术可以促进广泛的,低成本的OSA查,改善早期诊断和治疗启动.
  • 该模型在女性中的增强性能需要进一步调查,并突出其潜在的临床实用性.