Biomedical datasets constitute a rich source of information, containing multivariate data collected during medical practice. In spite of inherent challenges, such as missing or imbalanced data, these types of datasets are increasingly utilized as a basis for the construction of predictive machine-learning models. The prediction of disease outcomes and complications could inform the process of decision-making in the hospital setting and ensure the best possible patient management according to the patient's features.
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