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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:

Machine learning models and bankruptcy prediction
Flávio Barboza, Herbert Kimura, Edward I. Altman
Expert Systems with Applications (2017) Vol. 83, pp. 405-417
Closed Access | Times Cited: 692

Showing 1-25 of 692 citing articles:

Machine Learning in Agriculture: A Review
Κωνσταντίνος Λιάκος, Patrizia Busato, Dimitrios Moshou, et al.
Sensors (2018) Vol. 18, Iss. 8, pp. 2674-2674
Open Access | Times Cited: 2140
Comparative analysis of surface water quality prediction performance and identification of key water parameters using different machine learning models based on big data
Kangyang Chen, Hexia Chen, Chuanlong Zhou, et al.
Water Research (2019) Vol. 171, pp. 115454-115454
Closed Access | Times Cited: 421
Machine Learning in Banking Risk Management: A Literature Review
Martin Leo, Suneel Sharma, K. Maddulety
Risks (2019) Vol. 7, Iss. 1, pp. 29-29
Open Access | Times Cited: 331
Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting
Jie Sun, Hui Li, Hamido Fujita, et al.
Information Fusion (2019) Vol. 54, pp. 128-144
Closed Access | Times Cited: 284
Statistical and machine learning models in credit scoring: A systematic literature survey
Xolani Dastile, Turgay Çelik, Moshe Moses Potsane
Applied Soft Computing (2020) Vol. 91, pp. 106263-106263
Closed Access | Times Cited: 274
CatBoost model and artificial intelligence techniques for corporate failure prediction
Sami Ben Jabeur, Cheima Gharib, Salma Mefteh‐Wali, et al.
Technological Forecasting and Social Change (2021) Vol. 166, pp. 120658-120658
Closed Access | Times Cited: 252
Machine learning approaches in COVID-19 diagnosis, mortality, and severity risk prediction: A review
Norah Alballa, Isra Al-Turaiki
Informatics in Medicine Unlocked (2021) Vol. 24, pp. 100564-100564
Open Access | Times Cited: 194
Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering
Sami Ben Jabeur, Nicolae Stef, Pedro Carmona
Computational Economics (2022) Vol. 61, Iss. 2, pp. 715-741
Closed Access | Times Cited: 101
Financial applications of machine learning: A literature review
Noella Nazareth, Y.V. Reddy
Expert Systems with Applications (2023) Vol. 219, pp. 119640-119640
Closed Access | Times Cited: 100
Assessing credit risk of commercial customers using hybrid machine learning algorithms
Marcos Machado, Salma Karray
Expert Systems with Applications (2022) Vol. 200, pp. 116889-116889
Closed Access | Times Cited: 82
Financial distress prediction using integrated Z-score and multilayer perceptron neural networks
Desheng Wu, Xiyuan Ma, David L. Olson
Decision Support Systems (2022) Vol. 159, pp. 113814-113814
Open Access | Times Cited: 74
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: 71
Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction
Jinxian Zhao, Jamal Ouenniche, Johannes De Smedt
Machine Learning with Applications (2024) Vol. 15, pp. 100527-100527
Open Access | Times Cited: 16
Management of financial risks in Slovak enterprises using regression analysis
Katarína Valašková, Tomáš Klieštik, Mária Kováčová
Oeconomia Copernicana (2018) Vol. 9, Iss. 1, pp. 105-121
Open Access | Times Cited: 138
Predicting mortgage default using convolutional neural networks
Håvard Kvamme, Nikolai Sellereite, Kjersti Aas, et al.
Expert Systems with Applications (2018) Vol. 102, pp. 207-217
Open Access | Times Cited: 135
Machine learning improves accounting estimates: evidence from insurance payments
Kexing Ding, Baruch Lev, Xuan Peng, et al.
Review of Accounting Studies (2020) Vol. 25, Iss. 3, pp. 1098-1134
Closed Access | Times Cited: 132
An Investigation of Credit Card Default Prediction in the Imbalanced Datasets
Talha Mahboob Alam, Kamran Shaukat, Ibrahim A. Hameed, et al.
IEEE Access (2020) Vol. 8, pp. 201173-201198
Open Access | Times Cited: 127
Data analytic approach for bankruptcy prediction
Hyunwoo Son, Chongseok Hyun, Dinh‐Van Phan, et al.
Expert Systems with Applications (2019) Vol. 138, pp. 112816-112816
Closed Access | Times Cited: 116
A new perspective of performance comparison among machine learning algorithms for financial distress prediction
Yu‐Pei Huang, Meng-Feng Yen
Applied Soft Computing (2019) Vol. 83, pp. 105663-105663
Closed Access | Times Cited: 114
Combining corporate governance indicators with stacking ensembles for financial distress prediction
Deron Liang, Chih‐Fong Tsai, Hung-Yuan Lu, et al.
Journal of Business Research (2020) Vol. 120, pp. 137-146
Closed Access | Times Cited: 110
A Comparative Performance Assessment of Ensemble Learning for Credit Scoring
Yiheng Li, Weidong Chen
Mathematics (2020) Vol. 8, Iss. 10, pp. 1756-1756
Open Access | Times Cited: 108
Forecasting credit ratings of decarbonized firms: Comparative assessment of machine learning models
Baojun Yu, Changming Li, Nawazish Mirza, et al.
Technological Forecasting and Social Change (2021) Vol. 174, pp. 121255-121255
Closed Access | Times Cited: 101
Machine learning towards intelligent systems: applications, challenges, and opportunities
MohammadNoor Injadat, Abdallah Moubayed, Ali Bou Nassif, et al.
Artificial Intelligence Review (2021) Vol. 54, Iss. 5, pp. 3299-3348
Closed Access | Times Cited: 99
Machine Learning for Financial Risk Management: A Survey
Akib Mashrur, Wei Luo, Nayyar A. Zaidi, et al.
IEEE Access (2020) Vol. 8, pp. 203203-203223
Open Access | Times Cited: 98
Research on financial early warning of mining listed companies based on BP neural network model
Xiaojun Sun, Yalin Lei
Resources Policy (2021) Vol. 73, pp. 102223-102223
Closed Access | Times Cited: 98
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