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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:

Corporate Bankruptcy Prediction Using Machine Learning Methodologies with a Focus on Sequential Data
Hyeongjun Kim, Hoon Cho, Doojin Ryu
Computational Economics (2021) Vol. 59, Iss. 3, pp. 1231-1249
Closed Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Artificial Intelligence in Accounting and Finance: Challenges and Opportunities
Ziwei Yi, Xinwei Cao, Zuyan Chen, et al.
IEEE Access (2023) Vol. 11, pp. 129100-129123
Open Access | Times Cited: 26
A transformer-based model for default prediction in mid-cap corporate markets
Kamesh Korangi, Christophe Mues, Cristián Bravo
European Journal of Operational Research (2022) Vol. 308, Iss. 1, pp. 306-320
Open Access | Times Cited: 31
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: 31
Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest Based FinTech Application for Hyper-automation
M. Prakash, S. Neelakandan, Abbas Mardani, et al.
Enterprise Information Systems (2023) Vol. 17, Iss. 10
Closed Access | Times Cited: 17
Bankruptcy prediction with low-quality financial information
Eduardo da Silva Mattos, Dennis Shasha
Expert Systems with Applications (2023) Vol. 237, pp. 121418-121418
Closed Access | Times Cited: 14
Machine learning techniques in bankruptcy prediction: A systematic literature review
Απόστολος Δασίλας, Anna Rigani
Expert Systems with Applications (2024) Vol. 255, pp. 124761-124761
Closed Access | Times Cited: 5
Cognitive Modelling of Bankruptcy Risk: A Comparative Analysis of Machine Learning Models to Predict the Bankruptcy
Jahirul Islam, Sabuj Saha, Mahadi Hasan, et al.
(2024), pp. 1-6
Closed Access | Times Cited: 4
Multi-modal deep learning for credit rating prediction using text and numerical data streams
Mahsa Tavakoli, Rohitash Chandra, Fengrui Tian, et al.
Applied Soft Computing (2025), pp. 112771-112771
Open Access
Bankruptcy prediction: Integration of convolutional neural networks and explainable artificial intelligence techniques
Yu-Cheng Lin, Roni Padliansyah, Yu‐Hsin Lu, et al.
International Journal of Accounting Information Systems (2025) Vol. 56, pp. 100744-100744
Closed Access
Artificial Intelligence in Economics Research: What Have We Learned? What Do We Need to Learn?
Salman Bahoo, John W. Goodell, Rachid Rhattat, et al.
Journal of Economic Surveys (2025)
Closed Access
Bankruptcy Prediction with Optuna-Enhanced Ensemble Machine Learning Methods: A Comparison of Oversampling and Undersampling Techniques
Vahid Sinap
DÜMF Mühendislik Dergisi (2025) Vol. 16, Iss. 1, pp. 97-113
Open Access
An Empirical Assessment of Credit Risk of Indian Companies Using Machine Learning Algorithms
R. Sujatha, D. Kavitha, B. Uma Maheswari, et al.
Communications in computer and information science (2025), pp. 315-334
Closed Access
Comparing the Performance of Corporate Bankruptcy Prediction Models Based on Imbalanced Financial Data
Seol-Hyun Noh
Sustainability (2023) Vol. 15, Iss. 6, pp. 4794-4794
Open Access | Times Cited: 11
Improved credit risk prediction based on an integrated graph representation learning approach with graph transformation
Yong Shi, Yi Qu, Zhensong Chen, et al.
European Journal of Operational Research (2023) Vol. 315, Iss. 2, pp. 786-801
Closed Access | Times Cited: 9
Bankruptcy Prediction Using Machine Learning
Komal Saxena, Shikhar Tiwar
2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (2024), pp. 1-4
Closed Access | Times Cited: 3
Risk Analysis of Bankruptcy in the U.S. Healthcare Industries Based on Financial Ratios: A Machine Learning Analysis
Hadi Gholampoor, Majid Asadi
Journal of theoretical and applied electronic commerce research (2024) Vol. 19, Iss. 2, pp. 1303-1320
Open Access | Times Cited: 3
Forecasting oil futures markets using machine learning and seasonal trend decomposition
A. Kim, Doojin Ryu, Alexander Webb
Investment Analysts Journal (2024), pp. 1-14
Closed Access | Times Cited: 3
Measuring corporate failure risk: Does long short-term memory perform better in all markets?
Hyeongjun Kim, Hoon Cho, Doojin Ryu
Investment Analysts Journal (2023) Vol. 52, Iss. 1, pp. 40-52
Closed Access | Times Cited: 7
Gated recurrent unit network: A promising approach to corporate default prediction
Michał Thor, Łukasz Postek
Journal of Forecasting (2024) Vol. 43, Iss. 5, pp. 1131-1152
Closed Access | Times Cited: 2
Machine learning approach for carbon disclosure in the Korean market: The role of environmental performance
J Lee, Jin Hyung Cho, Bong Jun Kim, et al.
Science Progress (2024) Vol. 107, Iss. 1
Open Access | Times Cited: 2
Các nhân tố ảnh hưởng đến kiệt quệ tài chính của các doanh nghiệp xây dựng và doanh nghiệp bất động sản niêm yết trên thị trường chứng khoán Việt Nam
Dương Phan Thùy, Nga Ngô Thị Thanh
Tạp chí Kinh tế và Phát triển (2024)
Closed Access | Times Cited: 2
Capturing locational effects: application of the K-means clustering algorithm
Doojin Ryu, Jengei Hong, Hyunjae Jo
The Annals of Regional Science (2024) Vol. 73, Iss. 1, pp. 265-289
Closed Access | Times Cited: 2
Default prediction modeling (DPM) with machine learning algorithms: case of non-financial listed companies in Pakistan
Jahanzaib Alvi, Imtiaz Arif
Kybernetes (2024)
Closed Access | Times Cited: 2
Application of Machine Learning in Enterprise Financial Risk Assessment: A Study About China’s A-Share Listed Manufacturing Companies
Kexin Yu, Zengyi Yu, Shuomin Ma, et al.
Communications in computer and information science (2024), pp. 132-147
Closed Access | Times Cited: 1
Forecasting Indian Goods and Services Tax revenue using TBATS, ETS, Neural Networks, and hybrid time series models
P. V. Thayyib, Muhammed Navas Thorakkattle, Faisal Usmani, et al.
Cogent Economics & Finance (2023) Vol. 11, Iss. 2
Open Access | Times Cited: 4
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