udy enrolled patients with return of spontaneous circulation after cardiac arrest from March 2010 to March 2020. The inclusion criteria were (1) older than the age of 16 years and (2) patients who had both EEG and NSE. The median time for EEG and NSE were 3 days (interquartile range 2–5 days) and 3 days (interquartile range 2–4 days), respectively. The quantification of background activity was conducted with the suppression ratio (SR). We used a machine learning (eXtreme Gradient Boosting algorithm) to evaluate whether the SR could improve the accuracy of prognostication. Results: We enrolled 151 patients. The receiver operating characteristic analysis revealed a cut-off value of serum NSE and the SR for poor outcome, serum NSE (>31.9 μg/L, area under curve [AUC] = 0.88), and the SR (>21.5%, AUC = 0.75 in the right hemisphere, >34.4%, AUC = 0.76 in the left hemisphere). There was a significant positive correlation between the severity of SR and the level of NSE (ρ = 0.57, p < 0.0001 fo