[HTML][HTML] ECG-based convolutional neural network in pediatric obstructive sleep apnea diagnosis
C García-Vicente, GC Gutiérrez-Tobal… - Computers in Biology …, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a prevalent respiratory condition in children and is
characterized by partial or complete obstruction of the upper airway during sleep. The …
characterized by partial or complete obstruction of the upper airway during sleep. The …
A 2D convolutional neural network to detect sleep apnea in children using airflow and oximetry
The gold standard approach to diagnose obstructive sleep apnea (OSA) in children is
overnight in-lab polysomnography (PSG), which is labor-intensive for clinicians and onerous …
overnight in-lab polysomnography (PSG), which is labor-intensive for clinicians and onerous …
Automatic assessment of pediatric sleep apnea severity using overnight oximetry and convolutional neural networks
F Vaquerizo-Villar, D Álvarez… - 2020 42nd annual …, 2020 - ieeexplore.ieee.org
In this study, we use the overnight blood oxygen saturation (SpO 2) signal along with
convolutional neural networks (CNN) for the automatic estimation of pediatric sleep apnea …
convolutional neural networks (CNN) for the automatic estimation of pediatric sleep apnea …
Convolutional neural networks to detect pediatric apnea-hypopnea events from oximetry
F Vaquerizo-Villar, D Álvarez… - 2019 41st annual …, 2019 - ieeexplore.ieee.org
Pediatric sleep apnea-hypopnea syndrome (SAHS) is a highly prevalent breathing disorder
that is related to many negative consequences for the children's health and quality of life …
that is related to many negative consequences for the children's health and quality of life …
[HTML][HTML] An explainable deep-learning architecture for pediatric sleep apnea identification from overnight airflow and oximetry signals
J Jiménez-García, M García, GC Gutiérrez-Tobal… - … Signal Processing and …, 2024 - Elsevier
Deep-learning algorithms have been proposed to analyze overnight airflow (AF) and
oximetry (SpO 2) signals to simplify the diagnosis of pediatric obstructive sleep apnea …
oximetry (SpO 2) signals to simplify the diagnosis of pediatric obstructive sleep apnea …
SCNN: Scalogram-based convolutional neural network to detect obstructive sleep apnea using single-lead electrocardiogram signals
Sleep apnea is a common symptomatic disease affecting nearly 1 billion people around the
world. The gold standard approach for determining the severity of sleep apnea is full-night …
world. The gold standard approach for determining the severity of sleep apnea is full-night …
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 …
F Vaquerizo-Villar, D Álvarez… - 2023 45th Annual …, 2023 - ieeexplore.ieee.org
Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but
relies on manual scoring of overnight polysomnography (PSG) recordings, which is onerous …
relies on manual scoring of overnight polysomnography (PSG) recordings, which is onerous …
Obstructive sleep apnea detection from single-lead electrocardiogram signals using one-dimensional squeeze-and-excitation residual group network
Q Yang, L Zou, K Wei, G Liu - Computers in biology and medicine, 2022 - Elsevier
Obstructive sleep apnea (OSA), which has high morbidity and complications, is diagnosed
via polysomnography (PSG). However, this method is expensive, time-consuming, and …
via polysomnography (PSG). However, this method is expensive, time-consuming, and …
[HTML][HTML] DCDA-Net: dual-convolutional dual-attention network for obstructive sleep apnea diagnosis from single-lead electrocardiograms
Obstructive sleep apnea (OSA) is a breathing-related chronic disease in which the soft
palate and tongue collapse and block the upper airway for at least 10 s during sleep. It can …
palate and tongue collapse and block the upper airway for at least 10 s during sleep. It can …
Pediatric obstructive sleep apnea diagnosis: leveraging machine learning with linear discriminant analysis
H Qin, L Zhang, X Li, Z Xu, J Zhang, S Wang… - Frontiers in …, 2024 - frontiersin.org
Objective The objective of this study was to investigate the effectiveness of a machine
learning algorithm in diagnosing OSA in children based on clinical features that can be …
learning algorithm in diagnosing OSA in children based on clinical features that can be …