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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:

Fuzzy classifier based on clustering with pairs of ε-hyperballs and its application to support fetal state assessment
Michał Jeżewski, Robert Czabański, Jacek M. Łęski, et al.
Expert Systems with Applications (2018) Vol. 118, pp. 109-126
Closed Access | Times Cited: 16

Showing 16 citing articles:

An attention-based CNN-BiLSTM hybrid neural network enhanced with features of discrete wavelet transformation for fetal acidosis classification
Mujun Liu, Yaosheng Lu, Shun Long, et al.
Expert Systems with Applications (2021) Vol. 186, pp. 115714-115714
Closed Access | Times Cited: 70
Evaluation of fuzzy membership functions for linguistic rule-based classifier focused on explainability, interpretability and reliability
Sebastian Porębski
Expert Systems with Applications (2022) Vol. 199, pp. 117116-117116
Closed Access | Times Cited: 31
A novel algorithm based on ensemble empirical mode decomposition for non-invasive fetal ECG extraction
Katerina Barnova, Radek Martínek, René Jaroš, et al.
PLoS ONE (2021) Vol. 16, Iss. 8, pp. e0256154-e0256154
Open Access | Times Cited: 30
Evaluation of parameters for fetal behavioural state classification
Lorenzo Semeia, Katrin Sippel, Julia Moser, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 11
Fuzzy Ordered $c$-Means Clustering and Least Angle Regression for Fuzzy Rule-Based Classifier: Study for Imbalanced Data
Jacek M. Łęski, Robert Czabański, Michał Jeżewski, et al.
IEEE Transactions on Fuzzy Systems (2019) Vol. 28, Iss. 11, pp. 2799-2813
Open Access | Times Cited: 18
Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography
Radek Martínek, Katerina Barnova, René Jaroš, et al.
IEEE Access (2020) Vol. 8, pp. 221942-221962
Open Access | Times Cited: 15
On designing a biosignal-based fetal state assessment system: A systematic mapping study
Manuel Gonçalves da Silva Neto, João Paulo do Vale Madeiro, Danielo G. Gomes
Computer Methods and Programs in Biomedicine (2022) Vol. 216, pp. 106671-106671
Closed Access | Times Cited: 8
AI-driven paradigm shift in computerized cardiotocography analysis: A systematic review and promising directions
Weifang Xie, Pufan Cai, Yating Hu, et al.
Neurocomputing (2024) Vol. 607, pp. 128446-128446
Closed Access | Times Cited: 1
Efficient approach for digitization of the cardiotocography signals
Zafer Cömert, Abdulkadir Şengür, Yaman Akbulut, et al.
Physica A Statistical Mechanics and its Applications (2019) Vol. 537, pp. 122725-122725
Closed Access | Times Cited: 10
An efficient compression technique for Foetal phonocardiogram signals in remote healthcare monitoring systems
Islam S. Fathi, Mohamed Ali Ahmed, M. A. Makhlouf
Multimedia Tools and Applications (2022) Vol. 82, Iss. 13, pp. 19993-20014
Open Access | Times Cited: 4
Improving the Quality of Clustering-Based Diagnostic Rules by Lowering Dimension of the Cluster Prototypes
Sebastian Porębski, Ewa Straszecka
Advances in intelligent systems and computing (2019), pp. 47-56
Closed Access | Times Cited: 4
Intrapartum cardiotocography trace pattern pre-processing, features extraction and fetal health condition diagnoses based on RCOG guideline
Shahad Al-Yousif, Ihab Ahmed Najm, Hossam Subhi Talab, et al.
PeerJ Computer Science (2022) Vol. 8, pp. e1050-e1050
Open Access | Times Cited: 3
On ε-insensitive simplification of fuzzy rules for fetal distress assessment
Michał Jeżewski, Robert Czabański, Jacek M. Łęski, et al.
Expert Systems with Applications (2021) Vol. 179, pp. 115052-115052
Closed Access | Times Cited: 3
Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals
Michał Jeżewski, Robert Czabański, Jacek M. Łęski, et al.
(2020), pp. 213-217
Closed Access | Times Cited: 2
Clustering with ε-Hyperballs Based Simplification of Fuzzy Rules to Support the Assessment of Fetal State
Robert Czabański, Michał Jeżewski, Jacek M. Łęski, et al.
(2020)
Closed Access | Times Cited: 2
Refining the rule base of fuzzy classifier to support the evaluation of fetal condition
Robert Czabański, Michał Jeżewski, Jacek M. Łęski, et al.
Applied Soft Computing (2023) Vol. 147, pp. 110790-110790
Closed Access
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