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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:

Bankruptcy prediction using machine learning models with the text-based communicative value of annual reports
Tsung‐Kang Chen, Hsien-Hsing Liao, G. M. Chen, et al.
Expert Systems with Applications (2023) Vol. 233, pp. 120714-120714
Closed Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

A two-stage case-based reasoning driven classification paradigm for financial distress prediction with missing and imbalanced data
Lean Yu, Mengxin Li, Xiaojun Liu
Expert Systems with Applications (2024) Vol. 249, pp. 123745-123745
Closed Access | Times Cited: 8
Corporate financial distress prediction using the risk-related information content of annual reports
Petr Hájek, Michal Munk
Information Processing & Management (2024) Vol. 61, Iss. 5, pp. 103820-103820
Closed Access | Times Cited: 6
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: 6
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
Cost-sensitive stacking ensemble learning for company financial distress prediction
Shanshan Wang, Guotai Chi
Expert Systems with Applications (2024) Vol. 255, pp. 124525-124525
Closed Access | Times Cited: 5
Deciphering Long‐Term Economic Growth: An Exploration With Leading Machine Learning Techniques
Zin Mar Oo, Ching‐Yang Lin, Makoto Kakinaka
Journal of Forecasting (2025)
Closed Access
An experimental survey of imbalanced learning algorithms for bankruptcy prediction
Peter Gnip, Róbert Kanász, Martin Zoričák, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open 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
Bankruptcy prediction using machine learning and Shapley additive explanations
Hoang Hiep Nguyen, Jean‐Laurent Viviani, Sami Ben Jabeur
Review of Quantitative Finance and Accounting (2023)
Closed Access | Times Cited: 11
Incorporating earned value management into income statements to improve project management profitability and elevate application in the business and management
Rudy Setyopurnomo, Sudarso Kaderi Wiryono, Yuliani Dwi Lestari, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0312956-e0312956
Open Access
Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset
Ummey Hany Ainan, Lip Yee Por, Yen‐Lin Chen, et al.
IEEE Access (2024) Vol. 12, pp. 9369-9381
Open Access | Times Cited: 3
Financial distress prediction in private firms: developing a model for troubled debt restructuring
Asad Mehmood, Francesco De Luca
Journal of Applied Accounting Research (2023)
Open Access | Times Cited: 7
Predicting failure of P2P lending platforms through machine learning: The case in China
Jen-Yin Yeh, Hsin‐Yu Chiu, Jhih-Huei Huang
Finance research letters (2023) Vol. 59, pp. 104784-104784
Closed Access | Times Cited: 5
The Application of Machine Learning in Diagnosing the Financial Health and Performance of Companies in the Construction Industry
Jarmila Horváthová, Martina Mokrišová, Alexander Schneider
Information (2024) Vol. 15, Iss. 6, pp. 355-355
Open Access | Times Cited: 1
Enhancing Bankruptcy Prediction with White Shark Optimizer and Deep Learning: A Hybrid Approach for Accurate Financial Risk Assessment

International journal of intelligent engineering and systems (2023) Vol. 17, Iss. 1, pp. 140-148
Open Access | Times Cited: 3
Dictionaries for post-bankruptcy success prediction: A machine learning approach
Wolfgang Breuer, Andreas Knetsch, Katharina Mersmann
SSRN Electronic Journal (2024)
Closed Access
Using Decision Trees to Predict Insolvency in Spanish SMEs: Is Early Warning Possible?
Andrés Navarro Galera, Juan Lara‐Rubio, Pavel Novoa‐Hernández, et al.
Computational Economics (2024)
Closed Access
Balancing Techniques for Advanced Financial Distress Detection Using Artificial Intelligence
Dovilė Kuizinienė, Tomas Krilavičius
Electronics (2024) Vol. 13, Iss. 8, pp. 1596-1596
Open Access
The Dilemma of Accuracy in Bankruptcy Prediction. A New Approach Using Explainable Ai Techniques to Predict Corporate Crises
Carlo Adornetto, Francesco Fasano, Iliess Zahid, et al.
(2024)
Closed Access
Text Mining and Financial Analysis Modeling for Financial Statement Disclosure
Huiying Kang
Deleted Journal (2024) Vol. 20, Iss. 6s, pp. 2230-2240
Open Access
Prediction of Bankruptcy Using Machine Learning Models
G. K. Kamalam, S. Naveen Kumar, G. Subiga, et al.
Lecture notes in networks and systems (2024), pp. 313-322
Closed Access
Financial distress prediction with annual reports-based deep textual feature extraction: A hybrid approach
Jiaming Liu, Ming Jia
Information Sciences (2024) Vol. 686, pp. 121318-121318
Closed Access
Research of data mining methods for classification of imbalanced data sets
Anastasiya Doroshenko, Dmytro Savchuk
Ukrainian Journal of Information Technology (2024) Vol. 6, Iss. 1, pp. 48-57
Closed Access
Leveraging machine learning to uncover the dynamic evolution of business models in intelligent manufacturing
Weihong Xie, Rongkang Chen, Zhongshun Li
Computers & Industrial Engineering (2024), pp. 110597-110597
Closed Access
Exploring Random Forest Regression for Financial Distress Detection
Guo Dong Hou, Dong Tong, Soung‐Yue Liew, et al.
(2024), pp. 7-12
Closed Access
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