Handbook Of Ai And Data Sciences For Sleep Disorders
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Handbook of AI and Data Sciences for Sleep Disorders
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.
Handbook of AI and Data Sciences for Sleep Disorders
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.
Novel Technologies in the Diagnosis and Management of Sleep-disordered Breathing
Author: Henri Korkalainen
language: en
Publisher: Frontiers Media SA
Release Date: 2024-03-13
Sleep-disordered breathing, ranging from habitual snoring to severe obstructive sleep apnea, is highly prevalent and represents a growing global healthcare burden. Besides disrupting sleep, sleep-disordered breathing leads to detrimental outcomes such as excessive daytime sleepiness, neurocognitive impairment, and increased cardiometabolic morbidities. The gold standard diagnostic procedures (e.g., in-lab polysomnography) are cumbersome and standard parameters derived from sleep studies often yield poor long-term prognostic value. Hence, there is a need for innovative diagnostic technologies and novel sleep metrics to enable simple diagnosis and tailored disease management.