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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:

Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction
Vicente García, Ana I. Marqués, J. Salvador Sánchez
Information Fusion (2018) Vol. 47, pp. 88-101
Open Access | Times Cited: 118

Showing 1-25 of 118 citing articles:

Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection
Gang Kou, Yong Xu, Yi Peng, et al.
Decision Support Systems (2020) Vol. 140, pp. 113429-113429
Open Access | Times Cited: 325
A benchmark of machine learning approaches for credit score prediction
Vincenzo Moscato, Antonio Picariello, Giancarlo Sperlì
Expert Systems with Applications (2020) Vol. 165, pp. 113986-113986
Closed Access | Times Cited: 176
Remaining Financially Healthy and Competitive: The Role of Financial Predictors
Tomáš Klieštik, Katarína Valašková, George Lăzăroiu, et al.
Journal of Competitiveness (2020) Vol. 12, Iss. 1, pp. 74-92
Open Access | Times Cited: 164
Machine learning-driven credit risk: a systemic review
Si Shi, Rita Tse, Wuman Luo, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 17, pp. 14327-14339
Open Access | Times Cited: 74
Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis
Ajithakumari Vijayappan Nair Biju, Ann Susan Thomas, J Thasneem
Quality & Quantity (2023) Vol. 58, Iss. 1, pp. 849-878
Open Access | Times Cited: 43
A Survey of Decision Trees: Concepts, Algorithms, and Applications
Ibomoiye Domor Mienye, Nobert Jere
IEEE Access (2024) Vol. 12, pp. 86716-86727
Open Access | Times Cited: 41
Improving financial bankruptcy prediction in a highly imbalanced class distribution using oversampling and ensemble learning: a case from the Spanish market
Hossam Faris, Ruba Abukhurma, Waref Almanaseer, et al.
Progress in Artificial Intelligence (2019) Vol. 9, Iss. 1, pp. 31-53
Closed Access | Times Cited: 94
A novel ensemble classification model based on neural networks and a classifier optimisation technique for imbalanced credit risk evaluation
Feng Shen, Xingchao Zhao, Zhiyong Li, et al.
Physica A Statistical Mechanics and its Applications (2019) Vol. 526, pp. 121073-121073
Closed Access | Times Cited: 91
DBIG-US: A two-stage under-sampling algorithm to face the class imbalance problem
Angélica Guzmán-Ponce, J. Salvador Sánchez, Rosa María Valdovinos Rosas, et al.
Expert Systems with Applications (2020) Vol. 168, pp. 114301-114301
Closed Access | Times Cited: 76
XGBoost Optimized by Adaptive Particle Swarm Optimization for Credit Scoring
Chao Qin, Yunfeng Zhang, Fangxun Bao, et al.
Mathematical Problems in Engineering (2021) Vol. 2021, pp. 1-18
Open Access | Times Cited: 76
A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain
Gang Yao, Xiaojian Hu, Guanxiong Wang
Expert Systems with Applications (2022) Vol. 200, pp. 117002-117002
Closed Access | Times Cited: 59
Combining feature selection, instance selection, and ensemble classification techniques for improved financial distress prediction
Chih‐Fong Tsai, Kuen‐Liang Sue, Ya‐Han Hu, et al.
Journal of Business Research (2021) Vol. 130, pp. 200-209
Closed Access | Times Cited: 57
An explainable artificial intelligence approach for financial distress prediction
Zijiao Zhang, Chong Wu, Shiyou Qu, et al.
Information Processing & Management (2022) Vol. 59, Iss. 4, pp. 102988-102988
Closed Access | Times Cited: 56
A novel XGBoost extension for credit scoring class-imbalanced data combining a generalized extreme value link and a modified focal loss function
Jonah Mushava, Michael P. Murray
Expert Systems with Applications (2022) Vol. 202, pp. 117233-117233
Closed Access | Times Cited: 54
Bagging Supervised Autoencoder Classifier for credit scoring
Mahsan Abdoli, Mohammad Akbari, Jamal Shahrabi
Expert Systems with Applications (2022) Vol. 213, pp. 118991-118991
Open Access | Times Cited: 45
An Explainable AI framework for credit evaluation and analysis
M. K. Nallakaruppan, Balamurugan Balusamy, M. Lawanya Shri, et al.
Applied Soft Computing (2024) Vol. 153, pp. 111307-111307
Closed Access | Times Cited: 16
Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends
Jana Doering, Renatas Kizys, Ángel A. Juan, et al.
Operations Research Perspectives (2019) Vol. 6, pp. 100121-100121
Open Access | Times Cited: 75
Ensemble learning with label proportions for bankruptcy prediction
Zhensong Chen, Wei Chen, Yong Shi
Expert Systems with Applications (2019) Vol. 146, pp. 113155-113155
Closed Access | Times Cited: 75
A MCDM-Based Evaluation Approach for Imbalanced Classification Methods in Financial Risk Prediction
Yongming Song, Yi Peng
IEEE Access (2019) Vol. 7, pp. 84897-84906
Open Access | Times Cited: 70
Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods
Elena Gregová, Katarína Valašková, Peter Adamko, et al.
Sustainability (2020) Vol. 12, Iss. 10, pp. 3954-3954
Open Access | Times Cited: 66
A novel approach to define the local region of dynamic selection techniques in imbalanced credit scoring problems
Leopoldo Melo, Franco Maria Nardini, Chiara Renso, et al.
Expert Systems with Applications (2020) Vol. 152, pp. 113351-113351
Open Access | Times Cited: 55
A conservative approach for online credit scoring
Afshin Ashofteh, Jorge Miguel Bravo
Expert Systems with Applications (2021) Vol. 176, pp. 114835-114835
Open Access | Times Cited: 44
Systematic Review of Financial Distress Identification using Artificial Intelligence Methods
Dovilė Kuizinienė, Tomas Krilavičius, Robertas Damaševičius, et al.
Applied Artificial Intelligence (2022) Vol. 36, Iss. 1
Open Access | Times Cited: 33
Flexible loss functions for binary classification in gradient-boosted decision trees: An application to credit scoring
Jonah Mushava, Michael P. Murray
Expert Systems with Applications (2023) Vol. 238, pp. 121876-121876
Open Access | Times Cited: 17
Leveraging network topology for credit risk assessment in P2P lending: A comparative study under the lens of machine learning
Yiting Liu, Lennart John Baals, Joerg Osterrieder, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124100-124100
Open Access | Times Cited: 7
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