Detection of Sleep Apnea from Single-Lead ECG: Comparison of Deep Learning Algorithms
Author:
Funder
Natural Sciences and Engineering Research Council of Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9478589/9478590/09478745.pdf?arnumber=9478745
Cited by 32 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Comparison of deep transfer learning models to detect obstructive sleep apnea with single-channel electrocardiogram;Intelligent Computing Techniques in Biomedical Imaging;2025
2. MPCNN: A Novel Matrix Profile Approach for CNN-based Single Lead Sleep Apnea in Classification Problem;IEEE Journal of Biomedical and Health Informatics;2024-08
3. MSAF-Transformer: A Multi-scale attentive feature network for sleep apnea prediction based on single lead ECG signal;2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC);2024-05-24
4. A Sleep Apnea Detection Methodology Based on SE-ResNeXt Model Using Single-Lead ECG;Journal of Biomimetics, Biomaterials and Biomedical Engineering;2024-04-10
5. Sleep Apnea Detection from Single-Lead ECG: A Comprehensive Analysis of Machine Learning and Deep Learning Algorithms;International Journal of Advanced Research in Science, Communication and Technology;2024-04-09
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