Machine Learning Innovations in CPR: A Comprehensive Survey on Enhanced Resuscitation Techniques
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866915006049681408 |
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| author | Islam, Saidul Rjoub, Gaith Elmekki, Hanae Bentahar, Jamal Pedrycz, Witold Cohen, Robin |
| author_facet | Islam, Saidul Rjoub, Gaith Elmekki, Hanae Bentahar, Jamal Pedrycz, Witold Cohen, Robin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_03131 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Machine Learning Innovations in CPR: A Comprehensive Survey on Enhanced Resuscitation Techniques Islam, Saidul Rjoub, Gaith Elmekki, Hanae Bentahar, Jamal Pedrycz, Witold Cohen, Robin Machine Learning Artificial Intelligence 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. |
| title | Machine Learning Innovations in CPR: A Comprehensive Survey on Enhanced Resuscitation Techniques |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2411.03131 |