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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:

Comparing the Performance of Deep Learning Methods to Predict Companies’ Financial Failure
Huthaifa Aljawazneh, Antonio M. Mora, Pablo García‐Sánchez, et al.
IEEE Access (2021) Vol. 9, pp. 97010-97038
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Impacts of crisis on SME bankruptcy prediction models’ performance
Mário Papík, Lenka Papíková
Expert Systems with Applications (2022) Vol. 214, pp. 119072-119072
Closed Access | Times Cited: 33
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 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
Development of MCS based-ensemble models using CEEMDAN decomposition and machine intelligence
Sandip Garai, Ranjit Kumar Paul
Intelligent Systems with Applications (2023) Vol. 18, pp. 200202-200202
Open Access | Times Cited: 15
Challenges of Artificial Intelligence for the Prevention and Identification of Bankruptcy Risk in Financial Institutions: A Systematic Review
Luis-Javier Vásquez-Serpa, Ciro Rodríguez, Jhelly Pérez, et al.
Journal of risk and financial management (2025) Vol. 18, Iss. 1, pp. 26-26
Open Access
Predicting Financial Distress in India: A Deep Learning Approach
Alay Peralungal, Natchimuthu Natchimuthu
Smart innovation, systems and technologies (2025), pp. 587-603
Closed Access
Machine Learning for Identifying Risk in Financial Statements: A Survey
Elias Zavitsanos, Eirini Spyropoulou, George Giannakopoulos, et al.
ACM Computing Surveys (2025)
Closed Access
Cost-Sensitive Metaheuristic Optimization-Based Neural Network with Ensemble Learning for Financial Distress Prediction
Salah Al-Deen Safi, Pedro Á. Castillo, Hossam Faris
Applied Sciences (2022) Vol. 12, Iss. 14, pp. 6918-6918
Open Access | Times Cited: 21
The possibilities of using AutoML in bankruptcy prediction: Case of Slovakia
Mário Papík, Lenka Papíková
Technological Forecasting and Social Change (2025) Vol. 215, pp. 124098-124098
Open Access
A survey on deep learning for financial risk prediction
Kuashuai Peng, Guofeng Yan
Quantitative Finance and Economics (2021) Vol. 5, Iss. 4, pp. 716-737
Open Access | Times Cited: 23
Exploring Resampling Techniques in Credit Card Default Prediction
Mark Lokanan
Research Square (Research Square) (2024)
Open Access | Times Cited: 2
The composition of time-series images and using the technique SMOTE ENN for balancing datasets in land use/cover mapping
Hai Ngo, Huu Duy Nguyen, Peio Loubière, et al.
Acta Montanistica Slovaca (2022), Iss. 27, pp. 342-359
Open Access | Times Cited: 10
A review of data mining methods in financial markets
Haihua Liu, Shan Huang, Peng Wang, et al.
Data Science in Finance and Economics (2021) Vol. 1, Iss. 4, pp. 362-392
Open Access | Times Cited: 13
Comprehensive review of different artificial intelligence-based methods for credit risk assessment in data science
Vadipina Amarnadh, Nageswara Rao Moparthi
Intelligent Decision Technologies (2023) Vol. 17, Iss. 4, pp. 1265-1282
Closed Access | Times Cited: 4
Enhancing financial distress prediction through integrated Chinese Whisper clustering and federated learning
Amel Ibrahim Al Ali, Sheeja Rani S, Ahmed M. Khedr
Journal of Open Innovation Technology Market and Complexity (2024) Vol. 10, Iss. 3, pp. 100344-100344
Open Access | Times Cited: 1
The Use of Machine Learning to Forecast Financial Performance: A Literature Review
Ahmed Abdulaziz Khudhur, Adel Ismail Al‐Alawi
(2024), pp. 1-6
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
Benchmarking Machine Learning Techniques for Bankruptcy Prediction under Benign and Adversarial Behaviors
Xinghan Yin, Thai Le
(2024), pp. 259-265
Closed Access
Splitting long‐term and short‐term financial ratios for improved financial distress prediction: Evidence from Taiwanese public companies
Asyrofa Rahmi, Chia-Chi Lu, Deron Liang, et al.
Journal of Forecasting (2024) Vol. 43, Iss. 7, pp. 2886-2903
Closed Access
A Neural Network-Based Approach to Forecasting Bankruptcy Using Feature Importance Analysis
Aditi Aatmaja, D. S. Bhagwat, B. Prakash, et al.
(2024), pp. 296-300
Closed Access
Explainable Deep Ensemble Learning for Improved Credit Default Prediction
Kagaba Dennis, B Caroline, Barbara Nansamba, et al.
(2024), pp. 256-270
Closed Access
Design and Implementation of an Intelligent Financial Management System Based on Enterprise Legal System
S.J. Daniel Patrick Huang
Journal of Organizational and End User Computing (2024) Vol. 36, Iss. 1, pp. 1-25
Open Access
STATE REGULATOR’S ROLE IN THE COUNTRY’S BANKING SYSTEM DURING WARTIME
Nataliya Sokrovolska, Аліна Корбутяк, Artur Oleksyn, et al.
Financial and credit activity problems of theory and practice (2023) Vol. 2, Iss. 49, pp. 43-55
Open Access | Times Cited: 1
Bankruptcy prediction using ensemble of autoencoders optimized by genetic algorithm
Róbert Kanász, Peter Gnip, Martin Zoričák, et al.
PeerJ Computer Science (2023) Vol. 9, pp. e1257-e1257
Open Access | Times Cited: 1
Correlation Analysis of Stock Index Data Features Using Sequential Rule Mining Algorithms
Nayanjyoti Mazumdar, Pankaj Kumar Deva Sarma
Algorithms for intelligent systems (2023), pp. 3-17
Closed Access | Times Cited: 1
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