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Artificial intelligence in emergency medicine: a narrative review
Angelica Rego1, Juan Pablo Arango-Ibanez2, R Andrew Taylor3
1Department of Emergency Medicine, MaineHealth Maine Medical Center, Portland, ME, USA.
The American Journal of Emergency Medicine
|January 30, 2026
Summary
Artificial intelligence (AI) offers significant potential to enhance emergency medicine (EM) through applications in triage, diagnostics, and operations. Understanding AI's capabilities and limitations is crucial for emergency clinicians.
Area of Science:
- * Computational intelligence and machine learning applications in clinical practice.
- * Advanced data analytics for healthcare decision support.
Background:
- * Artificial intelligence (AI) is increasingly integrated into healthcare systems.
- * Emergency medicine (EM) is a key area experiencing expanding AI applications.
Purpose of the Study:
- * To review the primary applications of AI in emergency medicine.
- * To outline the limitations and future directions of AI relevant to emergency clinicians.
Main Methods:
- * Focused narrative review of existing literature on AI in emergency medicine.
- * Synthesis of information on AI applications across the EM care continuum.
Main Results:
- * AI applications span prehospital care, radiology, point-of-care ultrasound, and emergency department operations.
- * AI aids in triage, diagnostics, prognostication, workflow optimization, and clinical education.
- * Identified limitations include data quality, bias, transparency, generalizability, and workflow integration.
Conclusions:
- * Artificial intelligence shows substantial promise for improving various aspects of emergency medicine.
- * Emergency clinicians must be aware of AI's potential benefits and inherent limitations.
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