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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:

Validating an SVM-based neonatal seizure detection algorithm for generalizability, non-inferiority and clinical efficacy
Karoliina Tapani, Päivi Nevalainen, Sampsa Vanhatalo, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105399-105399
Open Access | Times Cited: 22

Showing 22 citing articles:

A Class-Imbalance Aware and Explainable Spatio-Temporal Graph Attention Network for Neonatal Seizure Detection
Khadijeh Raeisi, Mohammad Khazaei, Gabriella Tamburro, et al.
International Journal of Neural Systems (2023) Vol. 33, Iss. 09
Open Access | Times Cited: 22
Clinical outcome prediction with an automated EEG trend, Brain State of the Newborn, after perinatal asphyxia
Saeed Montazeri Moghadam, Päivi Nevalainen, Marjo Metsäranta, et al.
Clinical Neurophysiology (2024) Vol. 162, pp. 68-76
Open Access | Times Cited: 8
Epileptic seizure prediction via multidimensional transformer and recurrent neural network fusion
Rong Zhu, Wen-Xin Pan, Jin‐Xing Liu, et al.
Journal of Translational Medicine (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 8
Scaling convolutional neural networks achieves expert level seizure detection in neonatal EEG
R. C. Hogan, Sean Mathieson, Aurel Luca, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access
An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation
Saeed Montazeri Moghadam, Manu Airaksinen, Päivi Nevalainen, et al.
The Lancet Digital Health (2022) Vol. 4, Iss. 12, pp. e884-e892
Open Access | Times Cited: 22
A Modified Aquila-Based Optimized XGBoost Framework for Detecting Probable Seizure Status in Neonates
Khondoker Mirazul Mumenin, Prapti Biswas, Md. Al-Masrur Khan, et al.
Sensors (2023) Vol. 23, Iss. 16, pp. 7037-7037
Open Access | Times Cited: 12
Updates in Neonatal Neuromonitoring
Giulia M. Benedetti, Zachary A. Vesoulis
Clinics in Perinatology (2025)
Closed Access
TATPat based explainable EEG model for neonatal seizure detection
Türker Tuncer, Şengül Doğan, İrem Taşçı, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Scaling convolutional neural networks achieves expert-level seizure detection in neonatal EEG
R. C. Hogan, Sean Mathieson, Aurel Luca, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 2
Ensemble Learning Using Individual Neonatal Data for Seizure Detection
Ana Borovac, Steinn Guðmundsson, Gardar Thorvardsson, et al.
IEEE Journal of Translational Engineering in Health and Medicine (2022) Vol. 10, pp. 1-11
Open Access | Times Cited: 9
Barnes–Hut approximation based accelerating t-SNE for seizure detection
Salim Rukhsar, Anil Kumar Tiwari
Biomedical Signal Processing and Control (2023) Vol. 84, pp. 104833-104833
Closed Access | Times Cited: 5
Multiband seizure type classification based on 3D convolution with attention mechanisms
Hui Huang, Peiyu Chen, Jianfeng Wen, et al.
Computers in Biology and Medicine (2023) Vol. 166, pp. 107517-107517
Closed Access | Times Cited: 5
Weighted directed graph-based automatic seizure detection with effective brain connectivity for EEG signals
Qi Sun, Yuanjian Liu, Shuangde Li
Signal Image and Video Processing (2023) Vol. 18, Iss. 1, pp. 899-909
Open Access | Times Cited: 4
Automatic Classification Framework for Neonatal Seizure Using Wavelet Scattering Transform and Nearest Component Analysis
Vipin Prakash Yadav, Kamlesh Kumar Sharma
IRBM (2024) Vol. 45, Iss. 4, pp. 100842-100842
Closed Access | Times Cited: 1
Free access via computational cloud to deep learning-based EEG assessment in neonatal hypoxic-ischemic encephalopathy: revolutionary opportunities to overcome health disparities
Robertino Dilena, Maria Roberta Cilio
Pediatric Research (2024) Vol. 96, Iss. 4, pp. 841-843
Closed Access | Times Cited: 1
Analysis of the impact of deep learning know-how and data in modelling neonatal EEG
Aengus Daly, Gordon Lightbody, Andriy Temko
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
A general sample-weighted framework for epileptic seizure prediction
Yikai Gao, Aiping Liu, Xinrui Cui, et al.
Computers in Biology and Medicine (2022) Vol. 150, pp. 106169-106169
Closed Access | Times Cited: 7
Weighted directed graph-based automatic seizure detection with effective brain connectivity for EEG signals
Qi Sun, Yuanjian Liu, Shuangde Li
Research Square (Research Square) (2023)
Open Access | Times Cited: 3
Computational method for aromatase-related proteins using machine learning approach
S. Muthu Krishnan, Jasmeet Kaur
PLoS ONE (2023) Vol. 18, Iss. 3, pp. e0283567-e0283567
Open Access | Times Cited: 1
Neonatal Seizure Detection Combining Sparse Representation and Deep Learning
Guangmiao Gao, Jie Liu, Qi Yuan, et al.
Frontiers in artificial intelligence and applications (2023)
Open Access | Times Cited: 1
Research on education management system based on machine learning and multidimensional data modeling
Qiaonan Xu, Hui Deng
Applied Mathematics and Nonlinear Sciences (2023) Vol. 9, Iss. 1
Open Access
Quantitative Analysis of the Influence of Coal Mining on the Underflow Zone of Rivers by Using Double Integro-differential Equations
Yuan Wan, Chen Zhang, Jing Wang, et al.
Applied Mathematics and Nonlinear Sciences (2023) Vol. 8, Iss. 2, pp. 1325-1338
Open Access
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