Extracting deep features from short ECG signals for early atrial fibrillation detection-Reference-Cited by-同舟云学术

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Extracting deep features from short ECG signals for early atrial fibrillation detection

Published:2020-09 Issue: Volume:109 Page:101896
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Wu Xiaodan,Zheng Yumeng,Chu Chao-Hsien,He Zhen

Funder

Natural Science Foundation of Hebei Province, China

100 Excellent Talents Foundation of Hebei Province of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference42 articles.

1. Atrial fibrillation pulse detection based on complex network mapping;Li;Comput Sci,2017

2. Inflection point analysis: a machine learning approach for extraction of IEGM active intervals during atrial fibrillation;Hajimolahoseini;Artif Intell Med,2018

3. Automatic detection of atrial fibrillation and other arrhythmias in ECG recordings acquired by a smartphone device;Billeci;Electronics,2018

4. Automatic P-wave analysis of patients prone to atrial fibrillation;Clavier;Med Biol Eng Comput,2002

5. A novel method for real‐time atrial fibrillation detection in electrocardiograms using multiple parameters;Du;Ann Noninvasive Electrocardiol,2014

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