Artificial Intelligence in Cardiopulmonary Resuscitation: Revolutionizing Resuscitation Through Precision and Prediction – A Narrative Review

Razieh Parizad,1 Juniali Hatwal,2 Elnaz Javanshir,1 Akash Batta,3 Bishav Mohan3 1Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; 2Department of Internal Medicine, Advanced Cardiac Centre, Post Graduate Institute of Medical Education & Research (PGIMER), Chandigarh, 160012, India; 3Department of Cardiology, Dayanand Medical College and Hospital (DMCH), Ludhiana, Punjab, 141001, IndiaCorrespondence: Akash Batta, Department of Cardiology, Dayanand Medical College and Hospital, Civil Lines, Ludhiana, Punjab, 141001, India, Tel +91 9815496786, Email [email protected]: 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.Keywords: artificial intelligence, cardiopulmonary resuscitation, cardiac arrest, machine learning, clinical decision-making, emergency medicine, resuscitation outcomes