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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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | JVS-Vascular Insights |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949912725000856 |
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| author | Zachary Tran, MD Michael C. Wilkinson, MD Glenn Guardamondo, MD Mohamed H. El-Farra, MD, MS Allan B. Peetz, MD Roger T. Tomihama, MD, MBA Sharon C. Kiang, MD |
| author_facet | Zachary Tran, MD Michael C. Wilkinson, MD Glenn Guardamondo, MD Mohamed H. El-Farra, MD, MS Allan B. Peetz, MD Roger T. Tomihama, MD, MBA Sharon C. Kiang, MD |
| author_sort | Zachary Tran, MD |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e9a7b3ae59b241dd92ddd8bdfd6ab5e7 |
| institution | Kabale University |
| issn | 2949-9127 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | JVS-Vascular Insights |
| spelling | doaj-art-e9a7b3ae59b241dd92ddd8bdfd6ab5e72025-08-20T03:41:26ZengElsevierJVS-Vascular Insights2949-91272025-01-01310026810.1016/j.jvsvi.2025.100268Narrative review on applications of artificial intelligence in vascular traumaZachary Tran, MD0Michael C. Wilkinson, MD1Glenn Guardamondo, MD2Mohamed H. El-Farra, MD, MS3Allan B. Peetz, MD4Roger T. Tomihama, MD, MBA5Sharon C. Kiang, MD6Section of Surgical Sciences, Division of Acute Care Surgery, Department of Surgery, Vanderbilt University Medical Center, Nashville, TNDivision of Vascular Surgery, Department of Surgery, Loma Linda University School of Medicine, Loma Linda, CA; Center for Artificial Intelligence and Vascular Engineering, Division of Vascular Surgery, Department of Surgery, VA Loma Linda Healthcare System, Loma Linda, CADivision of Vascular Surgery, Department of Surgery, Loma Linda University School of Medicine, Loma Linda, CADivision of Vascular Surgery, Department of Surgery, Loma Linda University School of Medicine, Loma Linda, CASection of Surgical Sciences, Division of Acute Care Surgery, Department of Surgery, Vanderbilt University Medical Center, Nashville, TNDepartment of Radiology, Section of Interventional Radiology, VA Long Beach Healthcare System, Long Beach, CADivision of Vascular Surgery, Department of Surgery, Loma Linda University School of Medicine, Loma Linda, CA; Center for Artificial Intelligence and Vascular Engineering, Division of Vascular Surgery, Department of Surgery, VA Loma Linda Healthcare System, Loma Linda, CA; Correspondence: Sharon C. Kiang, MD, Center for Artificial Intelligence and Vascular Engineering, Division of Vascular Surgery, Department of Surgery, VA Loma Linda Healthcare System, 11201 Benton St, Loma Linda, CA 92357; Division of Vascular Surgery, Department of Surgery, Loma Linda University School of Medicine, 11175 Campus St, Ste 21123, Loma Linda, CA 92350Objective: 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.http://www.sciencedirect.com/science/article/pii/S2949912725000856Artificial intelligenceBlunt thoracic injuryMachine learningTraumaVascular trauma |
| spellingShingle | Zachary Tran, MD Michael C. Wilkinson, MD Glenn Guardamondo, MD Mohamed H. El-Farra, MD, MS Allan B. Peetz, MD Roger T. Tomihama, MD, MBA Sharon C. Kiang, MD Narrative review on applications of artificial intelligence in vascular trauma JVS-Vascular Insights Artificial intelligence Blunt thoracic injury Machine learning Trauma Vascular trauma |
| title | Narrative review on applications of artificial intelligence in vascular trauma |
| title_full | Narrative review on applications of artificial intelligence in vascular trauma |
| title_fullStr | Narrative review on applications of artificial intelligence in vascular trauma |
| title_full_unstemmed | Narrative review on applications of artificial intelligence in vascular trauma |
| title_short | Narrative review on applications of artificial intelligence in vascular trauma |
| title_sort | narrative review on applications of artificial intelligence in vascular trauma |
| topic | Artificial intelligence Blunt thoracic injury Machine learning Trauma Vascular trauma |
| url | http://www.sciencedirect.com/science/article/pii/S2949912725000856 |
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