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Explainable machine learning model based on clinical and radiological features for predicting hematoma expansion or rebleeding after decompressive craniectomy in traumatic brain injury: a bicentric cohort study
0
Zitationen
7
Autoren
2026
Jahr
Abstract
We developed and externally validated an interpretable XGBoost-based model for the early prediction of hematoma expansion or rebleeding after DC in patients with TBI. This tool offers practical clinical value for perioperative decision-making and targeted monitoring.
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