Open Access Helper

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 Learning Convolutional Neural Network for ECG Signal Classification Aggregated Using IoT
S. Karthiga, A. M. Abirami
Computer Systems Science and Engineering (2022) Vol. 42, Iss. 3, pp. 851-866
Open Access | Times Cited: 10

Showing 10 citing articles:

Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review
Luca Neri, Matt T. Oberdier, Kirsten C. J. van Abeelen, et al.
Sensors (2023) Vol. 23, Iss. 10, pp. 4805-4805
Open Access | Times Cited: 46
Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals
Yared Daniel Daydulo, Bheema Lingaiah Thamineni, Ahmed Ali Dawud
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 27
Comprehensive Learning Salp Swarm Algorithm with Ensemble Deep Learning-based ECG Signal Classification on Internet of Things Environment
Mohamed Tounsi, Adnan Ali, Ahmad Taher Azar, et al.
Engineering Technology & Applied Science Research (2025) Vol. 15, Iss. 1, pp. 19492-19500
Open Access
A deep Bi-CapsNet for analysing ECG signals to classify cardiac arrhythmia
Anitha Thiyagarajan, S. Aanjankumar, Rajesh Kumar Dhanaraj, et al.
Computers in Biology and Medicine (2025) Vol. 189, pp. 109924-109924
Closed Access
A deep learning framework optimised by Harris Hawks algorithm for intelligent ECG classification in WSN-IoT environment
P. Anuradha, Ch. Navitha, G. Renuka, et al.
Journal of Intelligent & Fuzzy Systems (2023) Vol. 45, Iss. 5, pp. 8489-8501
Closed Access | Times Cited: 2
Analysis & prediction of cardiac arrhythmia using deep learning techniques
Gaurav Ameta, Pushpendra Singh Sisodia
AIP conference proceedings (2024) Vol. 3107, pp. 050009-050009
Closed Access
Cardiac Arrhythmia Classification Using Convolutional Neural Network
Oumaima Gamgami, Reda Korikache, Amine Chaieb
(2024), pp. 297-308
Closed Access
Deep learning-assisted arrhythmia classification using 2-D ECG spectrograms
P. Naga Malleswari, Venkata Krishna Odugu, T. J. V. Subrahmanyeswara Rao, et al.
EURASIP Journal on Advances in Signal Processing (2024) Vol. 2024, Iss. 1
Open Access
Automated Arrhythmia Classification Using Farmland Fertility Algorithm with Hybrid Deep Learning Model on Internet of Things Environment
Ahmed S. Almasoud, Hanan Abdullah Mengash, Majdy M. Eltahir, et al.
Sensors (2023) Vol. 23, Iss. 19, pp. 8265-8265
Open Access | Times Cited: 1
A Novel Personalized Incremental Arrhythmias Classification Method for ECG Monitoring
Zhiyuan Li, Yuanyuan Tian, Yanrui Jin, et al.
Frontiers in artificial intelligence and applications (2023)
Open Access
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