Narrative review on applications of artificial intelligence in vascular trauma
Objective: Artificial intelligence (AI) applications in vascular trauma are vast and revolutionizing the approach to patient care. AI has demonstrated to have potential to aid in complex medical decision-making across the continuum of trauma care from injury prognostication and prehospital triage, t...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | JVS-Vascular Insights |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949912725000856 |
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| Summary: | Objective: Artificial intelligence (AI) applications in vascular trauma are vast and revolutionizing the approach to patient care. AI has demonstrated to have potential to aid in complex medical decision-making across the continuum of trauma care from injury prognostication and prehospital triage, to initial evaluation and postoperative surveillance. AI’s transformative footprint is guiding the way in the era of “big data.” The present review seeks to provide a comprehensive overview of the current applications of AI in vascular trauma management, provide awareness for future directions in this field, and discuss limitations to its widespread adoption. Methods: A narrative review of full text articles evaluating AI-based interventions in vascular trauma from inception to 2025 was performed. Results: Our review focuses on the AI applications in vascular trauma in three specific domains of vascular trauma: blunt cerebrovascular injury, traumatic amputation and peripheral arterial injury, and blunt thoracic aortic injury. Present work thus far has focused on outcome prognostication compared with pre-existing and historic models. We also describe several studies that discuss leveraging AI’s strengths in identifying injury risk factors that may not be readily clinically apparent. Advances in computational surgery with the aid of AI in complex endovascular repair has improved precision that has seen promise in improving outcomes. Future applications of AI may help improve trauma resuscitation, access to care, and survivorship. Current limitations to widespread adoption include the need for integration into time-sensitive clinical care processes, lack of familiarity, and the required technical expertise to build and maintain AI models. Conclusions: Current applications of AI in vascular trauma have demonstrated important utility to benefit patient care with a wide range of influence. As current barriers are addressed, clinicians can expect AI applications in vascular trauma to flourish and vascular trauma health care delivery to be more streamlined. |
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| ISSN: | 2949-9127 |