AI has the potential to complement emergency surgeons’ clinical judgment, but its routine adoption in emergency surgical practice remains limited. Addressing methodological, ethical, and regulatory challenges, together with the development of robust data infrastructures and targeted training pathways, is essential to support safe, effective, and equitable implementation in acute care settings. In addition, the lack of dedicated investment and sustainable funding models for large-scale clinical implementation and prospective evaluation represents a critical barrier to the translation of AI from research into routine emergency surgical practice.
Artificial intelligence in emergency surgery: a scoping review within the artificial intelligence in emergency and trauma surgery (ARIES) project / Belinda De Simone, Lucienne Kasongo, Andrew A. Gumbs, Fabrizio Vecchio, Alberto De Franceschi, Nicola DèAngelis, Andrew W. Kirkpatrick, Juan P. Wachs, Tyler J. Loftus, Fikri M. Abu-Zidan, Rifat Latifi, Genevieve Deeken, Elie Chouillard, Andrey Litvin, Massimo Sartelli, Desire' Pantalone, Ari Leppäniemi, Mehmet Eryilmaz, Kemal Rasa, Arda Isik, Haytham M. Kaafarani, Gustavo Fraga, Raul Coimbra, Ernest E. Moore, Walter L. Biffl, and Fausto Catena. - In: WORLD JOURNAL OF EMERGENCY SURGERY. - ISSN 1749-7922. - ELETTRONICO. - 21:(2026), pp. 12.0-12.0. [10.1186/s13017-026-00674-2]
Artificial intelligence in emergency surgery: a scoping review within the artificial intelligence in emergency and trauma surgery (ARIES) project
Desire' PantaloneValidation
;
2026
Abstract
AI has the potential to complement emergency surgeons’ clinical judgment, but its routine adoption in emergency surgical practice remains limited. Addressing methodological, ethical, and regulatory challenges, together with the development of robust data infrastructures and targeted training pathways, is essential to support safe, effective, and equitable implementation in acute care settings. In addition, the lack of dedicated investment and sustainable funding models for large-scale clinical implementation and prospective evaluation represents a critical barrier to the translation of AI from research into routine emergency surgical practice.
| File | Dimensione | Formato | |
|---|---|---|---|
|
s13017-026-00674-2.pdf
accesso aperto
Descrizione: To map and critically appraise the current literature on Artificial Intelligence (AI) applications in emergency general surgery, with a focus on clinical decision-support tools for preoperative risk stratification and intraoperative assistance, and to identify ethical, structural, and regulatory barriers to implementation.
Tipologia:
Pdf editoriale (Version of record)
Licenza:
Solo lettura
Dimensione
1.89 MB
Formato
Adobe PDF
|
1.89 MB | Adobe PDF |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
