A CatBoost model trained on MIMIC-III/IV elderly SICU admissions achieves AUROC 0.8868 for stroke risk, but outcome timing and feature selection make the result unreliable.
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Global, regional, and national burden of stroke, 1990-2016: A systematic analysis for the Global Burden of Disease Study 2016
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Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
A CatBoost model trained on MIMIC-III/IV elderly SICU admissions achieves AUROC 0.8868 for stroke risk, but outcome timing and feature selection make the result unreliable.