Development and external validation of an interpretable machine learning model for early prediction of in-hospital mortality in neurocritical care
Background Early risk assessment is a routine part of neurocritical care, yet mortality prediction remains difficult because neurological injury often coexists with respiratory, circulatory, renal, and inflammatory dysfunction. This study aimed to develop and externally validate an interpretable machine learning (ML) m...