Demonstrates the effectiveness of machine learning models in identifying sepsis and stroke using EMS data, suggesting implications for early intervention.
This study demonstrates the feasibility of applying machine learning models trained on ED triage data to prehospital EMS data for the early identification of stroke and sepsis. Future work should focus on model retraining using EMS-specific data, prospective validation, and real-world implementation strategies.
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Brown et al. (2026) studied this question.
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