04626nam a22006255i 4500 978-3-031-68263-6 DE-He213 20251030113235.0 cr nn 008mamaa 241019s2024 sz | s |||| 0|eng d 9783031682636 978-3-031-68263-6 10.1007/978-3-031-68263-6 doi QA402.5-402.6 QA315-316 PBU bicssc MAT042000 bisacsh PBU thema Handbook of AI and Data Sciences for Sleep Disorders [electronic resource] / edited by Richard B. Berry, Panos M. Pardalos, Xiaochen Xian. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. X, 304 p. 63 illus., 54 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Springer Optimization and Its Applications, 1931-6836 ; 216 Empowering Sleep Health: Unleashing the Potential of Artificial Intelligence and Data Science in Sleep Disorders -- Polysomnography Raw Data Extraction, Exploration, and Preprocessing -- Sleep stage probabilities derived from neurological or cardio-respiratory signals by means of artificial intelligence -- From Screening at Clinic to Diagnosis at Home: How AI/ ML/DL Algorithms are Transforming Sleep Apnea Detection -- Modeling and Analysis of Mechanical Work of Breathing -- A Probabilistic Perspective: Bayesian Neural Network for Sleep Apnea Detection -- Automatic and machine learning methods for detection and characterization of REM sleep behavior disorder -- Sleep Cyclic Alternating Pattern (CAP) as a Neurophysiological Marker of Brain Health -- Deep Learning with Electrocardiograms -- Machine learning automated analysis applied to mandibular jaw movements during sleep: a window on polysomnography -- Nightmare disorder: An Overview. 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. Mathematical optimization. 65522 Calculus of variations. 67268 Neurology . 66816 Machine learning. 55059 Artificial intelligence Data processing. Calculus of Variations and Optimization. 67270 Neurology. 66816 Machine Learning. 55059 Data Science. Berry, Richard B. editor. edt http://id.loc.gov/vocabulary/relators/edt 86265 Pardalos, Panos M. editor. edt http://id.loc.gov/vocabulary/relators/edt 68568 Xian, Xiaochen. editor. edt http://id.loc.gov/vocabulary/relators/edt 86266 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031682629 Printed edition: 9783031682643 Printed edition: 9783031682650 Springer Optimization and Its Applications, 1931-6836 ; 216 73211 https://doi.org/10.1007/978-3-031-68263-6 ZDB-2-SMA ZDB-2-SXMS 64317 64317