Arrhythmia Classification using Deep Learning and Machine Learning with Features Extracted from Waveform-based Signal Processing-Reference-Cited by-同舟云学术

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Arrhythmia Classification using Deep Learning and Machine Learning with Features Extracted from Waveform-based Signal Processing

Published:2020-07 Issue: Volume: Page:
ISSN:
Container-title:2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Hsu Po-Ya,Cheng Chung-Kuan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9167168/9175149/09176679.pdf?arnumber=9176679

Cited by 10 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. ECG‐TransCovNet: A hybrid transformer model for accurate arrhythmia detection using Electrocardiogram signals;CAAI Transactions on Intelligence Technology;2024-02-12

2. Classification of Cardiac Arrhythmia Using Machine Learning Algorithms;Lecture Notes in Networks and Systems;2024

3. Enhancing ECG Classification through Individual 12-lead Analysis and fQRS pattern based on Deep Learning technique;2023 18th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP);2023-11-27

4. Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review;Heliyon;2023-02

5. State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review;JMIR Medical Informatics;2022-08-15

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