Explainable machine learning for postoperative respiratory failure prediction in open-heart surgery patients — a study based on the MIMIC-IV database

The GBM model, selected for its balanced performance across discrimination, calibration, and validation stability, provides a promising tool for early PRF risk stratification. The use of SHAP analysis enhances the interpretability of the model, highlighting the role of hemodynamic and metabolic markers in predicting PRF, thus improving clinical understanding and decision-making.