从大数据到人工智能驱动的睡眠呼吸暂停决策:整合DDPP框架的叙述审查
Mengying Wu1,2, Kexin Wang2, Huai Huang2
1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Nature and science of sleep
|August 27, 2025
概括
人工智能 (AI) 在阻塞性睡眠呼吸暂停 (OSA) 研究中未得到充分利用,专注于睡眠信号,但忽视了其他数据. 个性化治疗分析 (处方) 很少,这阻碍了临床决策.
科学领域:
- 睡眠医学
- 人工智能
- 数据科学
背景情况:
- 阻塞性睡眠呼吸暂停 (OSA) 是一种常见的疾病,
- 人工智能 (AI) 的发展为OSA管理提供了潜在的解决方案.
- 公共交通运输的多模式数据资源正在迅速扩大.
研究的目的:
- 在阻塞性睡眠呼吸暂停 (OSA) 数据资源中全面审查人工智能技术的利用.
- 分析AI在不同数据类型和分析阶段 (描述性,诊断性,预测性,规范性) 的应用.
- 识别当前的OSA人工智能应用中的差距,并为未来的研究提供建议.
主要方法:
- 从2020年4月到2025年4月,主要科学数据库 (PubMed,科学网,Scopus,IEEE Xplore) 进行了系统的文献搜索.
- 搜索词组合了与人工智能相关的关键词和"阻塞性睡眠呼吸暂停".
- 使用DDPP (描述性,诊断性,预测性,规范性) 分析模型对人工智能应用进行分类.
主要成果:
- 在575项研究中, 大多数人工智能研究集中在睡眠监测信号上.
- 患者报告的结果,电子健康记录和环境数据仍未得到充分利用.
- 目前的临床应用主要集中在描述性和诊断性AI上,对个性化治疗的处方分析有限.
结论:
- 现有的OSA数据和当前的AI应用之间存在很大的差距.
- 未来的研究应该利用各种OSA数据维度并选择适当的AI技术.
- 增强人工智能利用可以改善临床决策和OSA的个性化治疗.
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