Hu, Y.-H., Tsai, C.-F.*, and Wang, P.-T. (2025) Combining Multiple Data Resampling Methods and Classifier Ensembles for Better Financial Distress Prediction: Homogeneous and Heterogeneous Approaches. Annals of Operations Research, Special Issue on Ensemble Learning for Operations Research and Business Analytics, vol. 353, pp. 793-814. (管理學院傑出期刊; SCI) (MOST 111-2410-H-008-027-MY3)

Tsai, C.-F., Wei-Chao Lin*, and Chen, Y.-H. (2025) Data Quality Improvement for Financial Distress Prediction: Feature Selection, Data Re-sampling, and their Combinations in Different Orders. Journal of Forecasting, vol. 44, no. 7,pp. 2205-2229.  (SSCI) 

Su, Y.-H. and Tsai, C.-F.* (2025) Predicting Functional Outcomes After a Stroke Event by Clinical Text Notes: A Comparative Study of Traditional Machine Learning and Deep Learning Methods. Health Informatics Journal, vol. 3, no. 3, 14604582251381194. (SCI; IF=2.3; 82/185 in Health Care Sciences & Services)

Hung, C., Tsai, C.-F.*, and Wu, M.-H. (2025) Dimensionality Reduction Strategies for Classification: ML vs. DL Approaches and Their Combinations. Expert Systems, vol. 42, no. 10, e70140. (SCI) (MOST 111-2410-H-008-027-MY3)

Tsai, C.-F., Wang, M.-C., Lin, W.-C.*, and Zheng, X.-Y. (2025) Predicting High Increases in Stock Prices Using Text Mining and Data Resampling Techniques. Applied Soft Computing, vol. 176, 113228. (SCI)

Hu, Y.-H.*, Liu, T.-H., Tsai, C.-F., and Lin, Y.-J. (2025) Handling Class Imbalanced Data in Sarcasm Detection with Ensemble Oversampling Techniques. Applied Artificial Intelligence, vol. 39, no. 1, e2468534. (SCI) 

Huang, M.-W., Tsai, C.-F., Lin, W.-C.*, and Lin, J.-Y. (2025) Interaction Effect between Data Discretization and Data Resampling for Class-Imbalanced Medical Datasets. Technology and Health Care, vol. 33, no. 2, pp. 1000-1013. (SCI) (MOST 111-2410-H-008-027-MY3)

Ke, S.-W., Tsai, C.-F. Pan Y.-Y., and Lin, W.-C.* (2024) Majority Re-sampling via Sub-class Clustering for Imbalanced Datasets. Journal of Experimental and Theoretical Artificial Intelligence, vol. 36, no. 8, pp. 1581-1596.  (SCI)

Sue, K.-L., Tsai, C.-F.*, and Tsau, H.-M. (2024) Missing Value Imputation and the Feature Normalization Effect on Financial Distress Prediction. Journal of Experimental & Theoretical Artificial Intelligence, vol. 36, no. 8, pp. 1467-1483. (SCI)

Tsai, C.-F., Chen, K.-C., and Lin, W.-C.* (2024) Feature Selection and Its Combination with Data Over-sampling for Multi-Class Imbalanced Datasets. Applied Soft Computing, vol. 153, 111267. (SCI)

Ke, S.-W.*, Tsai, C.-F., and Chen, Y.-J. (2024) Managing Emotion in the Workplace: An Empirical Study with Enterprise Instant Messaging. Applied Artificial Intelligence, vol. 38, no. 1, e2297518. (SCI)

Chen, K, Tsai, C.-F., Hu, Y.-H.*, and Hu, C.-W. (2024) The Effect of Review Visibility and Diagnosticity on Review Helpfulness – An Accessibility-Diagnosticity Theory Perspective. Decision Support Systems, vol. 178, 114145. (管理學院傑出期刊; SCI)

Chiu, C.-H., Ke, S.-W., Tsai, C.-F., Lin, W.-C., Huang, M.-W.*, and Ko, Y.-H. (2024) Deep Learning Based Decision Tree Ensembles for Incomplete Medical Datasets. Technology and Health Care, vol. 32, no. 1, pp. 75-87. (SCI) (MOST 105-2410-H-008-043-MY3)

Rahmi, A., Lu, H.-Y., Liang, D., Novitasari, D., and Tsai, C.-F. (2023) Role of comprehensive income in predicting bankruptcy. Computational Economics, vol. 62, pp. 689-720. (SSCI)

Hung, C., Wermter, S., Chi, Y.-L., and Tsai, C.-F.* (2023) An Adaptive Growing Grid Model for A Non-stationary Environment. Neurocomputing, vol. 550, 126405. (SCI)

Fang, C.-L., Wang, M.-C., Tsai, C.-F., and Lin, W.-C.*, and Liao, P.-Q. (2023) Instance Selection using One-vs-All and One-vs-One Decomposition Approaches in Multiclass Classification Datasets. Expert Systems, vol. 40, no. 6, e13217. (SCI)

Sue, K.-L., Tsai, C.-F.*, Chiu, A. (2023) The Data Sampling Effect on Financial Distress Prediction by Single and Ensemble Learning Techniques. Communications in Statistics – Theory and Methods, vol. 52, no. 12, pp. 4344-4355. (SCI)

Lin, C., Tsai, C.-F., and Lin, W.-C.* (2023) Towards Hybrid Combinations of Over- and Under-Sampling for Class Imbalanced Datasets: An Experimental Study. Artificial Intelligence Review, vol. 56, pp. 845-863. (SCI)

Lin, W.-C., Tsai, C.-F.*, and Chen, H. (2022) Factors Affecting Text Mining Based Stock Prediction: Text Feature Representations, Machine Learning Models, and News Platforms. Applied Soft Computing, vol. 130, 109673. (SCI)

Hu, Y.-H. and Tsai, C.-F.* (2022) An Investigation of Solutions for Handling Incomplete Online Review Datasets with Missing Values. Journal of Experimental & Theoretical Artificial Intelligence, vol. 34, no. 6, pp. 971-987. (SCI) (MOST 105-2410-H-008-043-MY3)

Lin, W.-C., Tsai, C.-F.* and Zhong, J.R. (2022) Deep Learning for Missing Value Imputation of Continuous Data and the Effect of Data Discretization. Knowledge-Based Systems, vol. 239, 108079. (SCI)

Tsai, C.-F.* and Hu, Y.-H. (2022) Empirical Comparison of Supervised Learning Techniques for Missing Value Imputation. Knowledge and Information Systems, vol. 64, pp. 1047-1075. (SCI) (MOST 105-2410-H-008-043-MY3)

Hung, L.-C., Hu, Y.-H., Tsai, C.-F., and Huang, M.-W.* (2022) A Dynamic Time Warping Approach for Handling Class Imbalanced Medical Datasets with Missing Values: A Case Study of Protein Localization Site Prediction. Expert Systems with Applications, vol. 192, 116437. (SCI) (MOST 105-2410-H-008-043-MY3)

Wang, Z., Tsai, C.-F., and Lin, W.-C.* (2021) Data Cleaning Issues in Class Imbalanced Datasets: Instance Selection and Missing Values Imputation for One-Class Classifiers. Data Technologies and Applications, vol. 55, no. 5, pp. 771-787. (SSCI)

Wang, M.-C., Tsai, C.-F., and Lin, W.-C.* (2021) Towards Missing Electric Power Data Imputation for Energy Management Systems. Expert Systems with Applications, vol. 174, 114743. (SCI)

Tsai, C.-F., Sue, K.-L., Hu, Y.-H.*, and Chiu, A. (2021) Combining Feature Selection, Instance Selection, and Ensemble Classification Techniques for Improved Financial Distress Prediction. Journal of Business Research, vol. 130, pp. 200-209. (管理學院傑出期刊; SSCI)

Huang, M.-W., Tsai, C.-F., and Lin, W.-C.* (2021) Instance Selection in Medical Datasets: A Divide-and-Conquer Framework. Computers & Electrical Engineering, vol. 90, 106957. (SCI)