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Ghost in the Machine: Leveraging artificial intelligence in the trauma bay.
Emma Gilman Burke1, Chloe Nobuhara2, Alex H Lee2
1Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, USA.
Trauma Surgery & Acute Care Open
|May 7, 2026
Summary
Artificial intelligence (AI) can improve trauma care by analyzing patient data for faster, more accurate decisions during the critical
Area of Science:
- Emergency Medicine
- Medical Informatics
- Trauma Surgery
Background:
- The initial hour post-injury, or 'golden hour,' demands swift, precise decision-making for effective trauma care.
- Optimal patient outcomes depend on coordinated prehospital resources, triage, resuscitation, and imaging.
- Traditional methods like static algorithms have limitations in integrating complex patient data.
Purpose of the Study:
- To review the current and developing uses of artificial intelligence (AI) in trauma care.
- To examine AI's specific applications within the trauma bay environment.
Main Methods:
- This study employed a narrative review methodology.
- Literature search focused on artificial intelligence applications in trauma resuscitation and decision support.
Main Results:
- AI models can process extensive data, offering superior decision support compared to static tools.
- Emerging AI applications show promise for enhancing trauma bay operations.
Conclusions:
- Artificial intelligence offers significant potential to optimize decision-making in the trauma bay.
- AI integration can lead to more efficient and effective trauma care delivery.
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