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Despite their promising performance, the clinical utility and cross-study comparability of ML models are constrained. This is mainly due to variability in outcome definitions, data heterogeneity, class imbalance and analysis concerns, inadequate external or prospective validation, and limited real-world deployment and ethical concerns. 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