The application achieves impressive performance, with models showing test set Area Under Curve values exceeding 0.85.
Key clinical variables used for predictions include ejection fraction, serum creatinine, and follow-up time, demonstrating the model's practical utility.
Stratified cross-validation (10-fold) ensures robust evaluation of predictive accuracy, sensitivity, and specificity, confirming model effectiveness.
The open-source R-Shiny framework allows for real-time risk predictions and enhances model interpretability and educational resources.