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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Deep neural network based approach for ECG classification using hybrid differential features and active learning
Kazım HANBAY
IET Signal Processing (2018) Vol. 13, Iss. 2, pp. 165-175
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

A Survey of Deep Active Learning
Pengzhen Ren, Yun Xiao, Xiaojun Chang, et al.
ACM Computing Surveys (2021) Vol. 54, Iss. 9, pp. 1-40
Open Access | Times Cited: 742
Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review
Fatma Murat, Özal Yıldırım, Muhammed Talo, et al.
Computers in Biology and Medicine (2020) Vol. 120, pp. 103726-103726
Open Access | Times Cited: 265
Deep learning in ECG diagnosis: A review
Xinwen Liu, Huan Wang, Zongjin Li, et al.
Knowledge-Based Systems (2021) Vol. 227, pp. 107187-107187
Closed Access | Times Cited: 242
Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017–2023
Mohammed Yaqoob Ansari, Omar Mourad, Khalid Qaraqe, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 54
Automated heartbeat classification based on deep neural network with multiple input layers
Haotian Shi, Chengjin Qin, Dengyu Xiao, et al.
Knowledge-Based Systems (2019) Vol. 188, pp. 105036-105036
Closed Access | Times Cited: 85
Review of ECG detection and classification based on deep learning: Coherent taxonomy, motivation, open challenges and recommendations
Shan Wei Chen, Shir Li Wang, Xiu Zhi Qi, et al.
Biomedical Signal Processing and Control (2022) Vol. 74, pp. 103493-103493
Closed Access | Times Cited: 43
Advances in Deep Learning for Natural Language Processing
Huaping Zhang, Jianyun Shang
(2025), pp. 43-71
Closed Access | Times Cited: 1
Artificial intelligence methods for analysis of electrocardiogram signals for cardiac abnormalities: state-of-the-art and future challenges
Sanjeev Saini, Rashmi Gupta
Artificial Intelligence Review (2021) Vol. 55, Iss. 2, pp. 1519-1565
Closed Access | Times Cited: 45
A novel myocardial infarction localization method using multi-branch DenseNet and spatial matching-based active semi-supervised learning
Ziyang He, Shuaiying Yuan, Jianhui Zhao, et al.
Information Sciences (2022) Vol. 606, pp. 649-668
Closed Access | Times Cited: 31
Detection of ventricular arrhythmia using hybrid time–frequency-based features and deep neural network
Sukanta Sabut, Om Pandey, Bhabani Shankar Prasad Mishra, et al.
Physical and Engineering Sciences in Medicine (2021) Vol. 44, Iss. 1, pp. 135-145
Closed Access | Times Cited: 36
Performance evaluation of convolution neural network models for detection of abnormal and ventricular ectopic beat cardiac episodes
N. Sriraam, Avvaru Srinivasulu
Multimedia Tools and Applications (2024) Vol. 83, Iss. 24, pp. 65149-65188
Closed Access | Times Cited: 4
Two3-AnoECG: ECG anomaly detection with two-stream networks and two-stage training using two double-throw switches
Yifan Li, Xiaoyan Peng, Weixun Cai, et al.
Knowledge-Based Systems (2024) Vol. 286, pp. 111396-111396
Open Access | Times Cited: 3
Analysis and classification of cardiac arrhythmia based on general sparsed neural network of ECG signals
Sanjay Tanaji Sanamdikar, Satish T. Hamde, Vinayak G. Asutkar
SN Applied Sciences (2020) Vol. 2, Iss. 7
Open Access | Times Cited: 24
Fusing deep metric learning with KNN for 12-lead multi-labelled ECG classification
Zicong Li, Henggui Zhang
Biomedical Signal Processing and Control (2023) Vol. 85, pp. 104849-104849
Open Access | Times Cited: 8
A novel transformer‐based ECG dimensionality reduction stacked auto‐encoders for arrhythmia beat detection
Ding Chun, Shenglun Wang, Xiaopeng Jin, et al.
Medical Physics (2023) Vol. 50, Iss. 9, pp. 5897-5912
Closed Access | Times Cited: 8
A comparative study and analysis of LSTM deep neural networks for heartbeats classification
Srinidhi Hiriyannaiah, G. M. Siddesh, M Kiran, et al.
Health and Technology (2021) Vol. 11, Iss. 3, pp. 663-671
Closed Access | Times Cited: 19
A robust myocardial infarction localization system based on multi-branch residual shrinkage network and active learning with clustering
Ziyang He, Shuaiying Yuan, Jianhui Zhao, et al.
Biomedical Signal Processing and Control (2022) Vol. 80, pp. 104238-104238
Closed Access | Times Cited: 12
A comprehensive review on efficient artificial intelligence models for classification of abnormal cardiac rhythms using electrocardiograms
Utkarsh Gupta, Naveen Paluru, Deepankar Nankani, et al.
Heliyon (2024) Vol. 10, Iss. 5, pp. e26787-e26787
Open Access | Times Cited: 2
An active learning enhanced data programming (ActDP) framework for ECG time series
Priyanka Gupta, Manik Gupta, Vijay Kumar
Machine Learning Science and Technology (2024) Vol. 5, Iss. 3, pp. 035016-035016
Open Access | Times Cited: 1
Accurate Arrhythmia Classification with Multi-Branch, Multi-Head Attention Temporal Convolutional Networks
Suzhao Bi, Rongjian Lu, Qiang Xu, et al.
Sensors (2024) Vol. 24, Iss. 24, pp. 8124-8124
Open Access | Times Cited: 1
GAN-Based Data Imbalance Techniques for ECG Synthesis to Enhance Classification Using Deep Learning Techniques and Evaluation
Shaik Janbhasha, S Nagakishore Bhavanam, Kalva Harshita
(2023), pp. 1-8
Closed Access | Times Cited: 4
A robust multiple heartbeats classification with weight-based loss based on convolutional neural network and bidirectional long short-term memory
Mengting Yang, Weichao Liu, Henggui Zhang
Frontiers in Physiology (2022) Vol. 13
Open Access | Times Cited: 6
Cardiac Severity Classification Using Pre Trained Neural Networks
P. Naga Malleswari, Ch. Hima Bindu, K. Satya Prasad
Interdisciplinary Sciences Computational Life Sciences (2021) Vol. 13, Iss. 3, pp. 443-450
Closed Access | Times Cited: 8
GABC based neuro-fuzzy classifier with hybrid features for ECG Beat classification
K. Muthuvel, S. Anto, T. Jerry Alexander
Multimedia Tools and Applications (2019) Vol. 78, Iss. 24, pp. 35351-35372
Closed Access | Times Cited: 7
An Interpretable Model for ECG Data Based on Bayesian Neural Networks
Hua Qiao, Yaqin Ye, Bo Wan, et al.
IEEE Access (2021) Vol. 9, pp. 57001-57009
Open Access | Times Cited: 6
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