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1. Bankruptcy prediction using optimal ensemble models under balanced and imbalanced data.

2. Advancements in Bankruptcy Prediction Models and Bibliometric Analysis.

3. Application of the Altman Model for the Prediction of Financial Distress in the Case of Slovenian Companies

4. Fuzzy Entropy: An Application to a Model of Fuzzy Business Diagnosis.

5. Tri-XGBoost model improved by BLSmote-ENN: an interpretable semi-supervised approach for addressing bankruptcy prediction.

6. Bankruptcy prediction using the Black-Scholes asset pricing model (Experimental evidence: Tehran Stock Exchange).

7. Applying sustainable development goals in financial forecasting using machine learning techniques.

8. Predicting business bankruptcy: A comparative analysis with machine learning models

9. Application of Machine Learning Tools in Bankruptcy Prediction: A Comparative Study Between Extra Trees Classifier and Logistic Regression

10. Predicting Corporate Bankruptcy Using Machine Learning Models

12. Prediction of Bankruptcy Using Machine Learning Models

15. Improving the Accuracy of Financial Bankruptcy Prediction Using Ensemble Learning Techniques

17. Machine Learning Algorithm Applications in Empirical Finance: A Review of the Empirical Literature

19. Artificial Intelligence Techniques for Bankruptcy Prediction of Tunisian Companies: An Application of Machine Learning and Deep Learning-Based Models.

20. An Ensemble Stacking Algorithm to Improve Model Accuracy in Bankruptcy Prediction.

21. A comparative study of feature selection and feature extraction methods for financial distress identification.

22. A Multi-Head LSTM Architecture for Bankruptcy Prediction with Time Series Accounting Data.

23. A spatiotemporal context aware hierarchical model for corporate bankruptcy prediction.

24. Natural Language Processing and Deep Learning for Bankruptcy Prediction: An End-to-End Architecture

25. A New Discrete Learning-Based Logistic Regression Classifier for Bankruptcy Prediction.

26. An Enhanced Ant Colony Optimisation Algorithm with the Hellinger Distance for Shariah-Compliant Securities Companies Bankruptcy Prediction.

27. Enhancing Bankruptcy Prediction with White Shark Optimizer and Deep Learning: A Hybrid Approach for Accurate Financial Risk Assessment.

28. Bankruptcy Prediction for Sustainability of Businesses: The Application of Graph Theoretical Modeling.

29. Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models.

30. A comparative study of feature selection and feature extraction methods for financial distress identification

31. Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction

32. Can corporate Social Responsibility Contribute to Bankruptcy Prediction? Evidence from Croatia

33. Bankruptcy Prediction Using Bi-Level Classification Technique

34. CatBoost: The Case of Bankruptcy Prediction

35. An Enhanced Ant Colony Optimisation Algorithm with the Hellinger Distance for Shariah-Compliant Securities Companies Bankruptcy Prediction

36. Efficiency of Working Capital & Assets Management in the Function of SMEs Bankruptcy Prediction

37. The informational value contained in the different types of auditor’s opinions: Evidence from Portugal

38. A neuro-structural framework for bankruptcy prediction.

39. ENSEMBLE MODEL - BASED BANKRUPTCY PREDICTION.

40. Comparative Analysis of Machine Learning Models for Bankruptcy Prediction in the Context of Pakistani Companies.

41. Corporate Probability of Default: A Single-Index Hazard Model Approach.

42. The Effect of Imbalanced Data and Parameter Selection via Genetic Algorithm Long Short-Term Memory (LSTM) for Financial Distress Prediction.

43. Efficiency of Working Capital & Assets Management in the Function of SMEs Bankruptcy Prediction.

44. Handling outliers in bankruptcy prediction models based on logistic regression.

46. A Multi-Head LSTM Architecture for Bankruptcy Prediction with Time Series Accounting Data

48. FACTORS AFFECTING THE CONCLUSION OF AN ARRANGEMENT IN RESTRUCTURING PROCEEDINGS: EVIDENCE FROM POLAND.

49. Designing topological data to forecast bankruptcy using convolutional neural networks.

50. Application of an Improved Optimization Using Learning Strategies and Long Short Term-Memory for Bankruptcy Prediction.

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