Argitalpenak (55) FERNANDO VAQUERIZO VILLAR argitalpenak

2024

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

    IFMBE Proceedings

  2. An explainable deep-learning architecture for pediatric sleep apnea identification from overnight airflow and oximetry signals

    Biomedical Signal Processing and Control, Vol. 87

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. Derivation and validation of a blood biomarker score for 2-day mortality prediction from prehospital care: a multicenter, cohort, EMS-based study

    Internal and Emergency Medicine, Vol. 18, Núm. 6, pp. 1797-1806

  4. Detección automática de la apnea del sueño infantil utilizando técnicas de deep learning y explainable artificial intelligence en señales de flujo aéreo

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

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. Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea

    Advances in experimental medicine and biology, Vol. 1384, pp. 131-146

  4. Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea-Hypopnea Events from the Oximetry Signal

    Advances in experimental medicine and biology, Vol. 1384, pp. 255-264

  5. ECG and Heart Rate Variability in Sleep-Related Breathing Disorders

    Advances in experimental medicine and biology, Vol. 1384, pp. 159-183

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

    Sleep, Vol. 45, Núm. 2

  7. Oximetry Indices in the Management of Sleep Apnea: From Overnight Minimum Saturation to the Novel Hypoxemia Measures

    Advances in experimental medicine and biology, Vol. 1384, pp. 219-239

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

  2. Automatic Sleep Staging in Children with Sleep Apnea using Photoplethysmography and Convolutional Neural Networks

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, Vol. 2021, pp. 216-219

  3. Bispectral analysis of overnight airflow to improve the pediatric sleep apnea diagnosis

    Computers in Biology and Medicine, Vol. 129

  4. Ensemble-learning regression to estimate sleep apnea severity using at-home oximetry in adults

    Applied Soft Computing, Vol. 111

  5. Heart rate variability during wakefulness as a marker of obstructive sleep apnea severity

    Sleep, Vol. 44, Núm. 5

  6. The Different Facets of Heart Rate Variability in Obstructive Sleep Apnea

    Frontiers in Psychiatry, Vol. 12

  7. Wavelet analysis of overnight airflow to detect obstructive sleep apnea in children

    Sensors, Vol. 21, Núm. 4, pp. 1-19