Description: Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea by Fernando Vaquerizo Villar Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This book describes the application of novel signal processing algorithms to improve the diagnostic capability of the blood oxygen saturation signal (SpO2) from nocturnal oximetry in the simplification of pediatric obstructive sleep apnea (OSA) diagnosis. Publisher Description This book describes the application of novel signal processing algorithms to improve the diagnostic capability of the blood oxygen saturation signal (SpO2) from nocturnal oximetry in the simplification of pediatric obstructive sleep apnea (OSA) diagnosis. For this purpose, 3196 SpO2 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 SpO2 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 all, this book offers a comprehensive and timely guide to the use of signal processing and AI methods in the diagnosis of pediatric OSA, including novel methodological insights concerning the automated analysis of the oximetry signal. It also discusses some open questions for future research. Details ISBN 3031328310 ISBN-13 9783031328312 Title Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea Author Fernando Vaquerizo Villar Format Hardcover Year 2023 Pages 90 Edition 2023rd Publisher Springer International Publishing AG GE_Item_ID:144161332; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 223.99 USD
Location: Fairfield, Ohio
End Time: 2024-11-27T01:07:37.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9783031328312
Type: NA
Publication Name: NA
Book Title: Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea : From Feature-Engineering to Deep-Learning Approaches
Number of Pages: Xviii, 90 Pages
Language: English
Publisher: Springer
Publication Year: 2023
Topic: Signals & Signal Processing, Intelligence (Ai) & Semantics, Probability & Statistics / General, Electronics / General, Biomedical
Illustrator: Yes
Genre: Mathematics, Computers, Technology & Engineering
Item Weight: 11.9 Oz
Item Length: 9.3 in
Author: Fernando Vaquerizo-Villar
Book Series: Springer Theses Ser.
Item Width: 6.1 in
Format: Hardcover
