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Development and validation of interpretable machine learning models to predict 30-day mortality in patients with intracerebral hemorrhage
Abstract Intracerebral hemorrhage (ICH) carries high early mortality. To enable personalized decision-making, we developed and validated interpretable machine learning models for 30-day mortality prediction. This retrospective cohort study included patients with ICH extracted from the Medical Information Mart for Intensive Care (MIMIC) clinical database.
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