Publikationen in Zusammenarbeit mit Forschern von Hospital Universitario Pío del Río Hortega (106)

2024

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

    Biomedical Signal Processing and Control, Vol. 87

  2. Exploring the disruptions of the neurophysiological organization in Alzheimer's disease: An integrative approach

    Computer Methods and Programs in Biomedicine, Vol. 250

2023

  1. 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

  2. Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses

    NeuroImage, Vol. 280

  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. Quantification of the robustness of functional neural networks: application to the characterization of Alzheimer's disease continuum

    Journal of neural engineering, Vol. 20, Núm. 3

2022

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

    MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings

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

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

  3. 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

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

    Sleep, Vol. 45, Núm. 2

  5. 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

  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

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. Abnormal meta-state activation of dynamic brain networks across the Alzheimer spectrum

    NeuroImage, Vol. 232

  3. Bispectral analysis of heart rate variability to characterize and help diagnose pediatric sleep apnea

    Entropy, Vol. 23, Núm. 8

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

    Computers in Biology and Medicine, Vol. 129

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

    Applied Soft Computing, Vol. 111

  6. Erratum to: Martín-montero et al. bispectral analysis of heart rate variability to characterize and help diagnose pediatric sleep apnea. entropy 2021, 23, 1016

    Entropy

  7. Exploring the alterations in the distribution of neural network weights in dementia due to Alzheimer’s disease

    Entropy, Vol. 23, Núm. 5

  8. Heart rate variability spectrum characteristics in children with sleep apnea

    Pediatric Research, Vol. 89, Núm. 7, pp. 1771-1779