MACHINE LEARNING MODELS SIGNIFICANT IMPROVE OUTCOME PREDICTION AFTER CARDIAC ARREST

Cardiac arrest is associated with a high mortality, and current illness severity scores are limited with regards to predictive accuracy. Our objective was to use logistic regression and machine learning (ML) techniques develop and compare models for in-hospital mortality after cardiac arrest