Predicting major adverse cardiac events in diabetes and chronic kidney disease: a machine learning study from the Silesia Diabetes-Heart Project

Ten features-based ML models, especially the LGBM model, had acceptable performance in predicting CVEs in persons with DM and CKD. A decrease in eGFR, aging, and elevated inflammatory markers significantly enhanced the predictive capability of the model. Future external validation of our model is required prior to implementation in a clinical environment.