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Predicting Breast Cancer Recurrence Using Machine Learning Techniques: A Systematic Review.

, , , , and . ACM Comput. Surv., 49 (3): 52:1-52:40 (2016)

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On the joint-effect of class imbalance and overlap: a critical review., , , , , , and . Artif. Intell. Rev., 55 (8): 6207-6275 (2022)A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research., , , , and . Inf. Fusion, (2023)Exploring the Effects of Data Distribution in Missing Data Imputation., , , , and . IDA, volume 11191 of Lecture Notes in Computer Science, page 251-263. Springer, (2018)FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes., , , and . IEEE Access, (2021)Cross-Validation for Imbalanced Datasets: Avoiding Overoptimistic and Overfitting Approaches Research Frontier., , , , and . IEEE Comput. Intell. Mag., 13 (4): 59-76 (2018)The impact of heterogeneous distance functions on missing data imputation and classification performance., , , , and . Eng. Appl. Artif. Intell., (2022)HCC Survival., , , , and . (November 2017)MNAR Imputation with Distributed Healthcare Data., , , and . EPIA (2), volume 11805 of Lecture Notes in Computer Science, page 184-195. Springer, (2019)ydata-profiling: Accelerating data-centric AI with high-quality data., , , , , and . Neurocomputing, (October 2023)A new cluster-based oversampling method for improving survival prediction of hepatocellular carcinoma patients., , , , and . J. Biomed. Informatics, (2015)