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Artificial Intelligence in Cardiopulmonary Resuscitation.

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Artificial intelligence (AI) and machine learning (ML) show great promise in improving cardiopulmonary resuscitation (CPR) outcomes. These technologies can enhance early recognition, CPR quality, and post-arrest care, revolutionizing resuscitation science.

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Area of Science:

  • Cardiopulmonary resuscitation science
  • Artificial intelligence in medicine
  • Machine learning applications

Background:

  • Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into cardiopulmonary resuscitation (CPR).
  • Evidence suggests AI/ML improves early recognition, intervention quality, and post-cardiac arrest outcomes.
  • This review synthesizes AI/ML advancements and challenges in resuscitation.

Purpose of the Study:

  • To review and synthesize current advancements in AI/ML-enhanced resuscitation science.
  • To categorize AI/ML applications across the American Heart Association's Chain of Survival.
  • To identify challenges and future directions for AI/ML in CPR.

Main Methods:

  • Targeted literature search in Web of Science (2018-2025).
  • Keywords: "artificial intelligence" and "cardiopulmonary resuscitation".
  • Studies reviewed and categorized by resuscitation phase.

Main Results:

  • AI/ML shows promise in early recognition and EMS activation.
  • Optimization of high-quality CPR, including feedback and defibrillation prediction.
  • Support for advanced interventions, outcome prediction, and integrated systems.
  • AI applications in resuscitation education and training are emerging.

Conclusions:

  • AI/ML technologies can significantly augment clinical performance across the Chain of Survival.
  • Effective implementation requires addressing ethical considerations, data representativeness, and validation.
  • Future research should focus on multicenter data, transparency, bias mitigation, and clinical evaluation.