Performance of Machine Learning Models for Sepsis and Stroke Detection Using EMS Data

Key Points

• The study aims to explore the use of machine learning models for early detection of stroke and sepsis in prehospital settings.
• Trained machine learning models on Emergency Department triage data
• Applied models to prehospital EMS data
• Recommended future model retraining with EMS-specific data
• Validated the feasibility of using machine learning for early detection
• Highlighted the need for prospective validation
• Emphasized the importance of real-world implementation strategies