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Titlebook: Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea; From Feature-Enginee Fernando Vaquerizo Villa

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發(fā)表于 2025-3-21 17:01:15 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea
期刊簡稱From Feature-Enginee
影響因子2023Fernando Vaquerizo Villar
視頻videohttp://file.papertrans.cn/167/166244/166244.mp4
發(fā)行地址Nominated as an outstanding PhD thesis by the Bioengineering Group of Comité Espa?ol de Automática.Reports on novel feature engineering and deep learning approaches applied to overnight oximetry.Descr
學(xué)科分類Springer Theses
圖書封面Titlebook: Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea; From Feature-Enginee Fernando Vaquerizo Villa
影響因子.This book describes the application of novel signal processing algorithms to improve the diagnostic capability of the blood oxygen saturation signal (SpO.2.) from nocturnal oximetry in the simplification of pediatric obstructive sleep apnea (OSA) diagnosis. For this purpose, 3196 SpO.2.?recordings from three different databases were analyzed using feature-engineering and deep-learning methodologies. Particularly, three novel feature extraction algorithms (bispectrum, wavelet, and detrended fluctuation analysis), as well as a novel deep-learning architecture based on convolutional neural networks are proposed. The proposed feature-engineering and deep-learning models outperformed conventional features from the oximetry signal, as well as state-of-the-art approaches. On the one hand, this book shows that bispectrum, wavelet, and detrended fluctuation analysis can be used to characterize changes in the SpO.2.?signal caused by apneic events in pediatric subjects. On the other hand, it demonstrates that deep-learning algorithms can learn complex features from oximetry dynamics that allow to enhance the diagnostic capability of nocturnal oximetry in the context of childhood OSA. All in
Pindex Book 2023
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沙發(fā)
發(fā)表于 2025-3-21 22:24:21 | 只看該作者
,Hypotheses and?Objectives, on the overall health and life quality of the affected children when it is untreated, including cardiometabolic malfunctioning and neurobehavioral abnormalities (Capdevila et al. in Proc Am Thorac Soc 5(2):274–282, 2008 [.]).
板凳
發(fā)表于 2025-3-22 03:03:16 | 只看該作者
2190-5053 nd, it demonstrates that deep-learning algorithms can learn complex features from oximetry dynamics that allow to enhance the diagnostic capability of nocturnal oximetry in the context of childhood OSA. All in 978-3-031-32834-3978-3-031-32832-9Series ISSN 2190-5053 Series E-ISSN 2190-5061
地板
發(fā)表于 2025-3-22 04:44:13 | 只看該作者
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發(fā)表于 2025-3-22 12:33:52 | 只看該作者
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發(fā)表于 2025-3-22 16:22:13 | 只看該作者
2190-5053 deep learning approaches applied to overnight oximetry.Descr.This book describes the application of novel signal processing algorithms to improve the diagnostic capability of the blood oxygen saturation signal (SpO.2.) from nocturnal oximetry in the simplification of pediatric obstructive sleep apne
7#
發(fā)表于 2025-3-22 20:37:02 | 只看該作者
Book 2023(SpO.2.) from nocturnal oximetry in the simplification of pediatric obstructive sleep apnea (OSA) diagnosis. For this purpose, 3196 SpO.2.?recordings from three different databases were analyzed using feature-engineering and deep-learning methodologies. Particularly, three novel feature extraction a
8#
發(fā)表于 2025-3-23 00:58:35 | 只看該作者
https://doi.org/10.1007/978-3-031-32832-9Pediatric Obstructive Sleep Apnea; Pediatric OSA Diagnosis; Automated Analysis of the Oximetry Signal;
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發(fā)表于 2025-3-23 03:54:01 | 只看該作者
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發(fā)表于 2025-3-23 06:34:51 | 只看該作者
Introduction,cant adverse consequences affecting metabolic, cardiovascular, neurocognitive, and behavioral systems, thus resulting in a decline of overall health and quality of life. Consequently, it is of paramount importance to accelerate the diagnosis and treatment in these children.
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