Handbook of AI and Data Sciences for Sleep Disorders
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Beschreibung
The rise of lifestyle changes resulting from constant connectivity, irregular work schedules, heightened stress, and disruptive sleep patterns, have contributed to increasing insomnia rates. Exacerbated by the COVID-19 pandemic, sleep disorders are more prevalent than ever. This handbook offers a comprehensive exploration of the fusion of Artificial Intelligence (AI) and data science within the realm of sleep disorders, presenting innovative approaches to diagnosis, treatment, and personalized care.
The interdisciplinary nature of this handbook fosters collaboration between experts from diverse fields, including computer science, engineering, neuroscience, medicine, public health, AI, data science, and sleep medicine. Each chapter delves into specific aspects of sleep disorder analysis, innovative methodologies, novel insights, and real-world applications that showcase the transformative potential of AI and data science in sleep medicine, from analyzing sleep patterns and predicting disorder risk factors to utilizing big data analytics for large-scale epidemiological studies. This handbook hopes to offer a comprehensive resource for researchers, clinicians, and policymakers striving to address the challenges in sleep medicine.
The rise of lifestyle changes resulting from constant connectivity, irregular work schedules, heightened stress, and disruptive sleep patterns, have contributed to increasing insomnia rates. Exacerbated by the COVID-19 pandemic, sleep disorders are more prevalent than ever. This handbook offers a comprehensive exploration of the fusion of Artificial Intelligence (AI) and data science within the realm of sleep disorders, presenting innovative approaches to diagnosis, treatment, and personalized care.
The interdisciplinary nature of this handbook fosters collaboration between experts from diverse fields, including computer science, engineering, neuroscience, medicine, public health, AI, data science, and sleep medicine. Each chapter delves into specific aspects of sleep disorder analysis, innovative methodologies, novel insights, and real-world applications that showcase the transformative potential of AI and data science in sleep medicine, from analyzing sleep patterns and predicting disorder risk factors to utilizing big data analytics for large-scale epidemiological studies. This handbook hopes to offer a comprehensive resource for researchers, clinicians, and policymakers striving to address the challenges in sleep medicine.
First book to summarize AI and data science techniques in the application of sleep disorders Contains fundamental knowledge and state-of-the-art methodologies Interdisciplinary content appeals to an expansive readership from engineering, medicine, mathematics, computer science, and business
Autor*in
Richard B. Berry
Themen in »Handbook of AI and Data Sciences for Sleep Disorders«
optimization techniques sleep disorder detection sleep disorders sleep disorder analytics machine learning methods sleep order case studies spatiotemporal analysis anomaly detection sleep analysis data acquisition sleep medicine linear signal processing nonlinear signal processing pattern recognition sleep medicine time series analysis sleep medicine spatiotemporal analysis sleep medicine