转化式学习
人工智能
睡眠(系统调用)
人工智能应用
失眠症
领域(数学)
安眠药
构造(python库)
注意
计算机科学
心理学
睡眠障碍
机器学习
数据科学
精神科
临床心理学
发展心理学
数学
纯数学
程序设计语言
操作系统
作者
Mohammad Nasir,Mohammad Shabbir Alam,Farhad Shahi,Mohammad Shahid Kamal,Kamal Upreti,Prashant Vats
标识
DOI:10.1109/etncc59188.2023.10284945
摘要
Disruptions to sleep have a substantial influence on people's overall health and quality of life. The conventional techniques for diagnosing and managing sleep disorders usually rely on subjective assessments and qualitative evaluations, that may have some accuracy and efficacy limitations. Nevertheless, recent developments in the field of artificial intelligence (AI) have presented new opportunities for better diagnosing and treating problems with insomnia. The paper reviews in depth the uses of AI in the domain of medical sleep medicine. We look at the use of algorithmic techniques for deep learning and machine learning for identifying indicators of sleep-related issues, the assessment of sleep quality, sleep tracking, and the establishment of individualized sleep therapeutics. We also discuss how AI is being used to construct forecasting models that may be used to identify individuals who are at risk of experiencing sleep issues and improve treatment strategies. In addition, we talk about the challenges and potential outcomes of incorporating AI-based techniques into clinical practice. Overall, our research highlights how AI has the potential to transform the field of sleeping medicine and improve outcomes for people with sleep-related conditions.
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