Roberto
Hornero Sanchez
University of Missouri
Columbia, Estados UnidosPublicaciones en colaboración con investigadores/as de University of Missouri (28)
2024
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An explainable deep-learning architecture for pediatric sleep apnea identification from overnight airflow and oximetry signals
Biomedical Signal Processing and Control, Vol. 87
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Persistent sleep-disordered breathing independently contributes to metabolic syndrome in prepubertal children
Pediatric Pulmonology, Vol. 59, Núm. 1, pp. 111-120
2023
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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
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Editorial: Unraveling sleep and its disorders using novel analytical approaches, volume II
Frontiers in Neuroscience
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Pediatric sleep apnea: Characterization of apneic events and sleep stages using heart rate variability
Computers in Biology and Medicine, Vol. 154
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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
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A 2D convolutional neural network to detect sleep apnea in children using airflow and oximetry
Computers in biology and medicine, Vol. 147, pp. 105784
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A convolutional neural network to classify sleep stages in pediatric sleep apnea from pulse oximetry signals
MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings
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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
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Editorial: Unraveling Sleep and Its Disorders Using Novel Analytical Approaches
Frontiers in Neuroscience
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Heart rate variability as a potential biomarker of pediatric obstructive sleep apnea resolution
Sleep, Vol. 45, Núm. 2
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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
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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
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Bispectral analysis of heart rate variability to characterize and help diagnose pediatric sleep apnea
Entropy, Vol. 23, Núm. 8
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Bispectral analysis of overnight airflow to improve the pediatric sleep apnea diagnosis
Computers in Biology and Medicine, Vol. 129
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Ensemble-learning regression to estimate sleep apnea severity using at-home oximetry in adults
Applied Soft Computing, Vol. 111
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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
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Heart rate variability spectrum characteristics in children with sleep apnea
Pediatric Research, Vol. 89, Núm. 7, pp. 1771-1779
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Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker
Frontiers in Neuroscience, Vol. 15
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Wavelet analysis of overnight airflow to detect obstructive sleep apnea in children
Sensors, Vol. 21, Núm. 4, pp. 1-19