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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:

A Novel Ensemble Method for Imbalanced Data Learning: Bagging of Extrapolation-SMOTE SVM
Qi Wang, Zhihao Luo, Jincai Huang, et al.
Computational Intelligence and Neuroscience (2017) Vol. 2017, pp. 1-11
Open Access | Times Cited: 135

Showing 1-25 of 135 citing articles:

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary
Alberto Fernández, Salvador García, Francisco Herrera, et al.
Journal of Artificial Intelligence Research (2018) Vol. 61, pp. 863-905
Open Access | Times Cited: 1533
Class Weights Random Forest Algorithm for Processing Class Imbalanced Medical Data
Min Zhu, Jing Xia, Xiaoqing Jin, et al.
IEEE Access (2018) Vol. 6, pp. 4641-4652
Open Access | Times Cited: 168
Learning imbalanced datasets based on SMOTE and Gaussian distribution
Tingting Pan, Junhong Zhao, Wei Wu, et al.
Information Sciences (2019) Vol. 512, pp. 1214-1233
Closed Access | Times Cited: 152
A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation
Azal Ahmad Khan, Omkar Chaudhari, Rohitash Chandra
Expert Systems with Applications (2023) Vol. 244, pp. 122778-122778
Open Access | Times Cited: 117
Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data
Philipp Thölke, Yorguin-José Mantilla-Ramos, Hamza Abdelhedi, et al.
NeuroImage (2023) Vol. 277, pp. 120253-120253
Open Access | Times Cited: 64
Examining the Ability of Artificial Neural Networks Machine Learning Models to Accurately Predict Complications Following Posterior Lumbar Spine Fusion
Jun Kim, Robert Merrill, Varun Arvind, et al.
Spine (2017) Vol. 43, Iss. 12, pp. 853-860
Open Access | Times Cited: 155
Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery
Manish Tripathi, Abhigyan Nath, T.P. Singh, et al.
Molecular Diversity (2021) Vol. 25, Iss. 3, pp. 1439-1460
Open Access | Times Cited: 94
Improvement of Bagging performance for classification of imbalanced datasets using evolutionary multi-objective optimization
Seyed Ehsan Roshan, Shahrokh Asadi
Engineering Applications of Artificial Intelligence (2019) Vol. 87, pp. 103319-103319
Closed Access | Times Cited: 91
Entropy and Confidence-Based Undersampling Boosting Random Forests for Imbalanced Problems
Zhe Wang, Chenjie Cao, Yujin Zhu
IEEE Transactions on Neural Networks and Learning Systems (2020) Vol. 31, Iss. 12, pp. 5178-5191
Closed Access | Times Cited: 88
Predicting Surgical Complications in Adult Patients Undergoing Anterior Cervical Discectomy and Fusion Using Machine Learning
Varun Arvind, Jun Kim, Eric K. Oermann, et al.
Neurospine (2018) Vol. 15, Iss. 4, pp. 329-337
Open Access | Times Cited: 85
Deep Focus Parallel Convolutional Neural Network for Imbalanced Classification of Machinery Fault Diagnostics
Andongzhe Duan, Liang Guo, Hongli Gao, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 69, Iss. 11, pp. 8680-8689
Closed Access | Times Cited: 85
Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers
Kerim Koç, Ömer Ekmekcioğlu, Aslı Pelin Gürgün
Automation in Construction (2021) Vol. 131, pp. 103896-103896
Closed Access | Times Cited: 67
Scenario-based automated data preprocessing to predict severity of construction accidents
Kerim Koç, Aslı Pelin Gürgün
Automation in Construction (2022) Vol. 140, pp. 104351-104351
Closed Access | Times Cited: 48
A novel Random Forest integrated model for imbalanced data classification problem
Qinghua Gu, Jingni Tian, Xuexian Li, et al.
Knowledge-Based Systems (2022) Vol. 250, pp. 109050-109050
Closed Access | Times Cited: 39
Predicting Surgical Complications in Patients Undergoing Elective Adult Spinal Deformity Procedures Using Machine Learning
Jun Kim, Varun Arvind, Eric K. Oermann, et al.
Spine Deformity (2018) Vol. 6, Iss. 6, pp. 762-770
Closed Access | Times Cited: 80
Learning temporal representation of transaction amount for fraudulent transaction recognition using CNN, Stacked LSTM, and CNN-LSTM
Yaya Heryadi, Harco Leslie Hendric Spits Warnars
(2017), pp. 84-89
Closed Access | Times Cited: 75
Application of machine learning approaches for osteoporosis risk prediction in postmenopausal women
Jae‐Geum Shim, Dong Woo Kim, Kyoung-Ho Ryu, et al.
Archives of Osteoporosis (2020) Vol. 15, Iss. 1
Closed Access | Times Cited: 66
Explainable Machine Learning Approach as a Tool to Understand Factors Used to Select the Refractive Surgery Technique on the Expert Level
Tae Keun Yoo, Ik Hee Ryu, Hannuy Choi, et al.
Translational Vision Science & Technology (2020) Vol. 9, Iss. 2, pp. 8-8
Open Access | Times Cited: 64
Improving Classification Performance for a Novel Imbalanced Medical Dataset using SMOTE Method
Ahmed Jameel Mohammed
International Journal of Advanced Trends in Computer Science and Engineering (2020) Vol. 9, Iss. 3, pp. 3161-3172
Open Access | Times Cited: 56
SSOMaj-SMOTE-SSO
Seba Susan, Amitesh Kumar
Applied Soft Computing (2019) Vol. 78, pp. 141-149
Closed Access | Times Cited: 55
An Imbalanced-Data Processing Algorithm for the Prediction of Heart Attack in Stroke Patients
Meng Wang, Xinghua Yao, Yixiang Chen
IEEE Access (2021) Vol. 9, pp. 25394-25404
Open Access | Times Cited: 48
HS-KDNet: A Lightweight Network Based on Hierarchical-Split Block and Knowledge Distillation for Fault Diagnosis With Extremely Imbalanced Data
Jin Deng, Wenjuan Jiang, Ye Zhang, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-9
Closed Access | Times Cited: 48
Human knee abnormality detection from imbalanced sEMG data
Ankit Vijayvargiya, Chandra Prakash, Rajesh Kumar, et al.
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102406-102406
Closed Access | Times Cited: 46
PF-SMOTE: A novel parameter-free SMOTE for imbalanced datasets
Qiong Chen, Zhong-Liang Zhang, Wenpo Huang, et al.
Neurocomputing (2022) Vol. 498, pp. 75-88
Closed Access | Times Cited: 36
A survey on computational taste predictors
Marta Malavolta, Lorenzo Pallante, Bojan Mavkov, et al.
European Food Research and Technology (2022) Vol. 248, Iss. 9, pp. 2215-2235
Open Access | Times Cited: 29
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