Description

Book Synopsis

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.

Handbook of AI and Data Sciences for Sleep Disorders

    Product form

    £119.99

    Includes FREE delivery

    RRP £159.99 – you save £40.00 (25%)

    Order before 4pm today for delivery by Sat 13 Jun 2026.

    A Hardback by Richard B. Berry

    1 in stock

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Handbook of AI and Data Sciences for Sleep Disorders by Richard B. Berry

      Publisher: Springer
      Publication Date: 19/10/2024
      ISBN13: 9783031682629, 978-3031682629
      ISBN10:
      Also in:
      Mathematics Optimization

      Description

      Book Synopsis

      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.

      Recently viewed products

      © 2026 Book Curl

        • American Express
        • Apple Pay
        • Diners Club
        • Discover
        • Google Pay
        • Maestro
        • Mastercard
        • PayPal
        • Shop Pay
        • Union Pay
        • Visa

        Login

        Forgot your password?

        Don't have an account yet?
        Create account