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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:

Distributed ReliefF-based feature selection in Spark
Raúl-José Palma-Mendoza, Daniel Rodríguez, Luis de‐Marcos
Knowledge and Information Systems (2018) Vol. 57, Iss. 1, pp. 1-20
Closed Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys
Jie Xiong, San‐Qiang Shi, Tong-Yi Zhang
Materials & Design (2019) Vol. 187, pp. 108378-108378
Open Access | Times Cited: 223
Transforming big data into smart data: An insight on the use of the k‐nearest neighbors algorithm to obtain quality data
Isaac Triguero, Diego García‐Gil, Jesús Maillo, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2018) Vol. 9, Iss. 2
Open Access | Times Cited: 188
Online streaming feature selection using adapted Neighborhood Rough Set
Peng Zhou, Xuegang Hu, Peipei Li, et al.
Information Sciences (2018) Vol. 481, pp. 258-279
Open Access | Times Cited: 88
A Hybrid Gene Selection Method Based on ReliefF and Ant Colony Optimization Algorithm for Tumor Classification
Lin Sun, Xianglin Kong, Jiucheng Xu, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 75
Diagnosis of Obstructive Sleep Apnea from ECG Signals Using Machine Learning and Deep Learning Classifiers
Alaa Sheta, Hamza Turabieh, Thaer Thaher, et al.
Applied Sciences (2021) Vol. 11, Iss. 14, pp. 6622-6622
Open Access | Times Cited: 68
Predicting Chronic Kidney Disease Using Hybrid Machine Learning Based on Apache Spark
Manal A. Abdel-Fattah, Nermin Abdelhakim Othman, Nagwa Goher
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-12
Open Access | Times Cited: 46
A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches
Saba Bashir, Irfan Ullah Khattak, Aihab Khan, et al.
Complexity (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 28
Distributed correlation-based feature selection in spark
Raúl-José Palma-Mendoza, Luis de‐Marcos, Daniel Rodríguez, et al.
Information Sciences (2018) Vol. 496, pp. 287-299
Open Access | Times Cited: 47
Comparison of machine learning models to provide preliminary forecasts of real estate prices
Jui‐Sheng Chou, Dillon-Brandon Fleshman, Dinh‐Nhat Truong
Journal of Housing and the Built Environment (2022) Vol. 37, Iss. 4, pp. 2079-2114
Closed Access | Times Cited: 27
Comparison of Feature Selection and Supervised Methods for Classifying Gait Disorders
Mohsen Shayestegan, Jan Kohout, Ludmila Verešpejová, et al.
IEEE Access (2024) Vol. 12, pp. 17876-17894
Open Access | Times Cited: 5
Condition Rating Prediction for Highway Bridge Based on Elman Neural Networks and Markov Chains
Tian Zhang, Haonan Chen, Xinjia Cui, et al.
Applied Sciences (2024) Vol. 14, Iss. 4, pp. 1444-1444
Open Access | Times Cited: 4
A hybrid clustering and boosting tree feature selection (CBTFS) method for credit risk assessment with high-dimensionality
Jianxin Zhu, Xiong Wu, Lean Yu, et al.
Technological and Economic Development of Economy (2025), pp. 1-33
Open Access
Challenges and Future Trends for Microarray Analysis
Verónica Bolón‐Canedo, Amparo Alonso‐Betanzos, Ignacio López‐de‐Ullibarri, et al.
Methods in molecular biology (2019), pp. 283-293
Closed Access | Times Cited: 40
Detecting biomarkers from microarray data using distributed correlation based gene selection
Alok Kumar Shukla, Diwakar Tripathi
Genes & Genomics (2020) Vol. 42, Iss. 4, pp. 449-465
Closed Access | Times Cited: 34
Waste Segregation FMEA Model Integrating Intuitionistic Fuzzy Set and the PAPRIKA Method
María Carmen Carnero
Mathematics (2020) Vol. 8, Iss. 8, pp. 1375-1375
Open Access | Times Cited: 32
Feature Selection and Deep Learning for Deterioration Prediction of the Bridges
Jinsong Zhu, Yanlei Wang
Journal of Performance of Constructed Facilities (2021) Vol. 35, Iss. 6
Closed Access | Times Cited: 27
Feature selection using a sinusoidal sequence combined with mutual information
Gaoteng Yuan, Lu Lu, Xiaofeng Zhou
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107168-107168
Closed Access | Times Cited: 12
FG-HFS: A feature filter and group evolution hybrid feature selection algorithm for high-dimensional gene expression data
Zhaozhao Xu, Fangyuan Yang, Chaosheng Tang, et al.
Expert Systems with Applications (2023) Vol. 245, pp. 123069-123069
Open Access | Times Cited: 11
An intelligent grinding burn detection system based on two-stage feature selection and stacked sparse autoencoder
Weicheng Guo, Beizhi Li, Shouguo Shen, et al.
The International Journal of Advanced Manufacturing Technology (2019) Vol. 103, Iss. 5-8, pp. 2837-2847
Closed Access | Times Cited: 29
Scalable feature selection using ReliefF aided by locality‐sensitive hashing
Carlos Eiras‐Franco, Bertha Guijarro‐Berdiñas, Amparo Alonso‐Betanzos, et al.
International Journal of Intelligent Systems (2021) Vol. 36, Iss. 11, pp. 6161-6179
Open Access | Times Cited: 22
Ensemble Variable Selection for Naive Bayes to Improve Customer Behaviour Analysis
R. Sıva Subramanıan, D. Prabha
Computer Systems Science and Engineering (2021) Vol. 41, Iss. 1, pp. 339-355
Open Access | Times Cited: 18
Identifying key soil characteristics for Francisella tularensis classification with optimized Machine learning models
Fareed Ahmad, Kashif Javed, Ahsen Tahir, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Detecting Constraints and Their Relations from Regulatory Documents Using NLP Techniques
Karolin Winter, Stefanie Rinderle‐Ma
Lecture notes in computer science (2018), pp. 261-278
Closed Access | Times Cited: 21
Feasibility analysis of extreme learning machine for predicting thermal conductivity of rocks
Jianguo Kang, Ziwang Yu, Shaohua Wu, et al.
Environmental Earth Sciences (2021) Vol. 80, Iss. 13
Closed Access | Times Cited: 13
A critical review of the machine learning guided design of metallic glasses for superior glass-forming ability
Ziqing Zhou, Yinghui Shang, Yong Yang
Journal of Materials Informatics (2022)
Open Access | Times Cited: 9
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