Machine Learning Innovations in CPR: A Comprehensive Survey on Enhanced Resuscitation Techniques

• URL: http://arxiv.org/abs/2411.03131v1
• Date: Sun, 03 Nov 2024 18:01:50 GMT
• Title: Machine Learning Innovations in CPR: A Comprehensive Survey on Enhanced Resuscitation Techniques
• Authors: Saidul Islam, Gaith Rjoub, Hanae Elmekki, Jamal Bentahar, Witold Pedrycz, Robin Cohen,
• Abstract summary: This survey paper explores the transformative role of Machine Learning (ML) and Artificial Intelligence (AI) in Cardiopulmonary Resuscitation (CPR) It highlights the impact of predictive modeling, AI-enhanced devices, and real-time data analysis in improving resuscitation outcomes. The paper provides a comprehensive overview, classification, and critical analysis of current applications, challenges, and future directions in this emerging field.
• Score: 52.71395121577439
• License:
• Abstract: This survey paper explores the transformative role of Machine Learning (ML) and Artificial Intelligence (AI) in Cardiopulmonary Resuscitation (CPR). It examines the evolution from traditional CPR methods to innovative ML-driven approaches, highlighting the impact of predictive modeling, AI-enhanced devices, and real-time data analysis in improving resuscitation outcomes. The paper provides a comprehensive overview, classification, and critical analysis of current applications, challenges, and future directions in this emerging field.

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