GFDLECG: PAC Classification for ECG Signals Using Gradient Features and Deep Learning-Reference-Cited by-同舟云学术

GFDLECG: PAC Classification for ECG Signals Using Gradient Features and Deep Learning

Published:2021 Issue: Volume: Page:369-382
ISSN:2569-7072
Container-title:Advances in Data Science and Information Engineering
language:
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Author:

Abu-gellban Hashim,Nguyen Long,Jin Fang

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-71704-9_24

Reference33 articles.

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4. J. Werth, X. Long, E. Zwartkruis-Pelgrim, H. Niemarkt, W. Chen, R.M. Aarts, P. Andriessen, Unobtrusive assessment of neonatal sleep state based on heart rate variability retrieved from electrocardiography used for regular patient monitoring. Early Hum. Dev. 113, 104–113 (2017)

5. M. Kachuee, S. Fazeli, M. Sarrafzadeh, ECG heartbeat classification: a deep transferable representation, in IEEE International Conference on Healthcare Informatics (ICHI) (IEEE, Piscataway, 2018), pp. 443–444

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