Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis.

Machine learning models, particularly the superior-performing Random Forest, are proven to reliably predict long-term adverse outcomes in NBM patients, aiding in the identification of high-risk individuals. Further validation in broader cohorts is warranted to enhance generalizability and clinical applicability.