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Cardiopulmonary resuscitation (CPR) remains a fundamental intervention in the management of cardiac arrest, with timely initiation and optimal performance serving as critical determinants of survival and neurological recovery. In recent years, the application of artificial intelligence (AI) has emerged as a promising approach to enhance the effectiveness of CPR by delivering real-time feedback, supporting clinical decision-making, and enabling individualized resuscitation strategies. This narrative review summarizes the current applications of AI in CPR, including rhythm interpretation, quality monitoring, and post-resuscitation care. In addition, it discusses major challenges related to data privacy, system interoperability, algorithmic fairness, and ethical governance. Future directions emphasize the importance of interdisciplinary collaboration, rigorous model validation, and structured training for clinical users. Although additional validation is required, the integration of AI into resuscitation practices holds significant promise for enhancing patient outcomes and potentially reducing mortality associated with sudden cardiac arrest.
Parizad et al. (Wed,) studied this question.