Machine Learning for Predicting Mortality in Intensive Care Unit Patients: A Prognostic Performance Systematic Review and Meta‐Analysis

Machine learning-based mortality prediction models, when integrated into clinical decision-support systems, have the potential to significantly enhance nursing practice. These tools could assist in the early identification of high-risk patients, enabling prioritisation for intensified monitoring, facilitating timely escalation of care and supporting proactive goals-of-care discussions with families. Future implementation should focus on improving model interpretability and seamless workflow integration to foster trust and utility among frontline physicians and nurses.