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Evaluating Predictive Performance of Machine Learning Algorithms That Integrate Routine Clinical Variables With Imaging-Derived Information in Stroke Recurrence Risk
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4
Autoren
2026
Jahr
Abstract
ML-based algorithms that integrate routine clinical variables with imaging-derived data can predict stroke recurrence risk effectively, with the XGBoost model demonstrating superior predictive performance, which may further support more individualized clinical decision-making.
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