Initial seizure episodes risk factors identification during hospitalization of ICU patients: A retrospective analysis of the eICU collaborative research database

CONCLUSION: The ensemble learning model, combining Gradient Boosting and Logistic Regression via a stacking technique, demonstrated superior performance for identifying risk factors for initial seizure episodes in ICU patients. This model was evaluated using a range of performance metrics, including accuracy, sensitivity, specificity, and the AUC-ROC curve, and was validated through 10-fold cross-validation to ensure its robustness and generalizability. These results offer clinically relevant...