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人工智能模型用于睡眠医学标准诊断的自动化-系统性审查

Maha Alattar¹, Alok Govind², Shraddha Mainali³

¹Division of Adult Neurology, Sleep Medicine, Vascular Neurology, Department of Neurology, Virginia Commonwealth University, Richmond, VA 23284, USA.

Bioengineering (Basel, Switzerland)

|March 27, 2024

概括

人工智能 (AI) 为诊断睡眠障碍提供了一种有希望的,易于使用的方法,超越了昂贵的手动多睡眠图 (PSG). 在各种临床数据上对AI模型的严格验证对于它们融入睡眠医学实践至关重要.

科学领域:

睡眠医学睡眠医学
人工智能的人工智能
医学诊断医学诊断医学诊断

背景情况:

睡眠障碍是常见的,并带来了重大的健康挑战.
目前用于诊断的多睡眠图 (PSG) 分析是耗时且昂贵的.
人工智能为更容易获得和个性化的睡眠障碍诊断提供了机会.

研究的目的:

系统地审查基于人工智能的睡眠障碍诊断模型.
评估这些AI模型在临床数据集上的验证和测试.
突出需要严格的验证在睡眠医学.

主要方法:

在PubMed和IEEE数据库中的系统文献搜索.
根据人工智能模型培训,验证和测试的严格标准选择研究.
分析了214篇获取的文章,其中18篇被选中进行审查.

主要成果:

确定了有限数量的经过彻底验证的AI模型用于睡眠障碍诊断 (在2114篇文章中,有18篇).
稀缺性强调了需要更强大的AI开发和验证在这个领域.
人工智能模型显示出改善诊断可访问性的潜力,特别是在服务不足的人群中.

结论:

使用多模式临床数据严格验证AI模型对于临床整合至关重要.
需要进一步的研究和开发,以满足AI在睡眠医学中的标准.
这与美国睡眠医学学会对睡眠诊断中人工智能研究的支持一致.

关键词:

人工智能的人工智能是人工智能.深度学习是一种深度学习.睡眠和人工智能睡眠障碍睡眠障碍睡眠障碍睡眠的药物睡眠的药物

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