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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:

Comparison of Different Machine Learning Algorithms for Detecting Bankruptcy
Maria Sultana Keya, Himu Akter, Md. Atiqur Rahman, et al.
(2021), pp. 705-712
Closed Access | Times Cited: 12

Showing 12 citing articles:

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
Machine Learning for Identifying Risk in Financial Statements: A Survey
Elias Zavitsanos, Eirini Spyropoulou, George Giannakopoulos, et al.
ACM Computing 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
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
Corporate Bankruptcy Prediction Models: A Comparative Study for the Construction Sector in Greece
Kanellos Toudas, Stefanos Archontakis, Paraskevi Boufounou
Computation (2024) Vol. 12, Iss. 1, pp. 9-9
Open Access | Times Cited: 1
Prediction of Bankruptcy of a company using machine learning techniques
Vivek Kothuru, Raman K. Jha, Sasanapuri Ranjit, et al.
2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) (2022), pp. 797-800
Closed Access | Times Cited: 4
A Performance Analysis of Depression Ratio using Machine Learning Approaches
Maria Sultana Keya, Alex Han
2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS) (2022), pp. 215-219
Closed Access | Times Cited: 3
Trapped human victims Machine Learning detection Model Using Recursive Feature Elimination with SVM Classification Algorithm
Jiya Adana Enoch, Ilesanmi B. Oluwafemi, F. Ibikunle, et al.
(2024), pp. 1-7
Closed Access
Predicting Bankruptcy and Suggesting Improvements on Financial Attributes using Machine Learning Models
Jay Shah, Bhargav Rao, Yash Mehta, et al.
2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) (2022), pp. 807-812
Closed Access | Times Cited: 1
A spatiotemporal context aware hierarchical model for corporate bankruptcy prediction
Binayak Chakrabarti, Amol Jain, Pavit Nagpal, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 10, pp. 28281-28303
Closed Access
Bankruptcy Detection on Unbalanced Data with Various Machine Learning Models
Kommareddy Tarun
International Journal for Research in Applied Science and Engineering Technology (2022) Vol. 10, Iss. 6, pp. 1435-1439
Open Access
Machine Learning as a Data Science Tool to Predict Absenteeism for Factory Workers
J Rajath, Deepika Pandita
2021 International Conference on Data Analytics for Business and Industry (ICDABI) (2022), pp. 261-265
Closed Access
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