Investigating the impact of feature extraction methods on prediction accuracy of neurological recovery levels in comatose patients post-cardiac arrest.

Cardiac arrest can cause irreversible Post-Cardiac Arrest Brain Injury (PCABI), but predicting PCABI with certainty remains challenging. This study aims to improve prognostication by predicting neurological recovery using EEG data from the 'I-CARE: International Cardiac Arrest Research Consortium Database.' Data were preprocessed with an FIR Equiripple Bandpass Filter, and three feature extraction methods were applied.