睡眠医学中的人工智能：背景及对临床医生的启示
Artificial intelligence in sleep medicine: background and implications for clinicians.
作者信息
Goldstein Cathy A, Berry Richard B, Kent David T, Kristo David A, Seixas Azizi A, Redline Susan, Westover M Brandon
机构信息
Sleep Disorders Center, Department of Neurology, University of Michigan, Ann Arbor, Michigan.
Division of Pulmonary, Critical Care and Sleep Medicine, University of Florida, Gainesville, Florida.
出版信息
J Clin Sleep Med. 2020 Apr 15;16(4):609-618. doi: 10.5664/jcsm.8388.
Polysomnography remains the cornerstone of objective testing in sleep medicine and results in massive amounts of electrophysiological data, which is well-suited for analysis with artificial intelligence (AI)-based tools. Combined with other sources of health data, AI is expected to provide new insights to inform the clinical care of sleep disorders and advance our understanding of the integral role sleep plays in human health. Additionally, AI has the potential to streamline day-to-day operations and therefore optimize direct patient care by the sleep disorders team. However, clinicians, scientists, and other stakeholders must develop best practices to integrate this rapidly evolving technology into our daily work while maintaining the highest degree of quality and transparency in health care and research. Ultimately, when harnessed appropriately in conjunction with human expertise, AI will improve the practice of sleep medicine and further sleep science for the health and well-being of our patients.
多导睡眠图仍然是睡眠医学客观测试的基石，会产生大量的电生理数据，非常适合使用基于人工智能（AI）的工具进行分析。结合其他健康数据来源，人工智能有望提供新的见解，为睡眠障碍的临床护理提供参考，并加深我们对睡眠在人类健康中所起的整体作用的理解。此外，人工智能有潜力简化日常操作，从而优化睡眠障碍团队对患者的直接护理。然而，临床医生、科学家和其他利益相关者必须制定最佳实践，将这项快速发展的技术融入我们的日常工作，同时在医疗保健和研究中保持最高程度的质量和透明度。最终，当与人类专业知识适当地结合使用时，人工智能将改善睡眠医学的实践，并进一步推动睡眠科学的发展，以促进我们患者的健康和福祉。
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