Publikationen, an denen er mitarbeitet David Gozal (57)

2024

  1. Accurate and Interpretable Deep Learning Model for Sleep Staging in Children with Sleep Apnea from Pulse Oximetry

    IFMBE Proceedings

  2. Persistent sleep-disordered breathing independently contributes to metabolic syndrome in prepubertal children

    Pediatric Pulmonology, Vol. 59, Núm. 1, pp. 111-120

2023

  1. A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, Vol. 2023, pp. 1-4

  2. An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea

    Computers in Biology and Medicine, Vol. 165

  3. Are we missing something? Different obstructive sleep apnea phenotypes as a possible driver of discrepancies in cognitive recovery after continuous positive airway pressure treatment

    Sleep

  4. Characterization of Cardiopulmonary Coupling in Pediatric Patients with Obstructive Sleep Apnea

    Computing in Cardiology

  5. ECG-ENET: Red neuronal convolucional explicable para la ayuda en el diagnóstico de la apnea del sueño infantil

    CASEIB 2023. Libro de Actas del XLI Congreso Anual de la Sociedad Española de Ingeniería Biomédica: Contribuyendo a la salud basada en valor

  6. ECG-based convolutional neural network in pediatric obstructive sleep apnea diagnosis

    Computers in Biology and Medicine, Vol. 167

  7. Editorial: Unraveling sleep and its disorders using novel analytical approaches, volume II

    Frontiers in Neuroscience

  8. Pediatric sleep apnea: Characterization of apneic events and sleep stages using heart rate variability

    Computers in Biology and Medicine, Vol. 154

  9. Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals

    Diagnostics, Vol. 13, Núm. 20

  10. Validation of a predictive model for obstructive sleep apnea in people with Down syndrome

    American Journal of Medical Genetics, Part A, Vol. 191, Núm. 2, pp. 518-525

2022

  1. A 2D convolutional neural network to detect sleep apnea in children using airflow and oximetry

    Computers in biology and medicine, Vol. 147, pp. 105784

  2. A convolutional neural network to classify sleep stages in pediatric sleep apnea from pulse oximetry signals

    MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings

  3. Characterization of Changes in HRV Metrics During Sleep Apnea Episodes in Pediatric Patients

    2022 12th Conference of the European Study Group on Cardiovascular Oscillations, ESGCO 2022

  4. Editorial: Unraveling Sleep and Its Disorders Using Novel Analytical Approaches

    Frontiers in Neuroscience

  5. Heart rate variability as a potential biomarker of pediatric obstructive sleep apnea resolution

    Sleep, Vol. 45, Núm. 2

  6. Reliability of machine learning to diagnose pediatric obstructive sleep apnea: Systematic review and meta-analysis

    Pediatric Pulmonology, Vol. 57, Núm. 8, pp. 1931-1943

  7. Slow EEG Oscillation to Characterize Pediatric Sleep Apnea and Associated Cognitive Impairments

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, Vol. 2022, pp. 2957-2960

2021

  1. A Convolutional Neural Network Architecture to Enhance Oximetry Ability to Diagnose Pediatric Obstructive Sleep Apnea

    IEEE Journal of Biomedical and Health Informatics, Vol. 25, Núm. 8, pp. 2906-2916