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A scoping review of artificial intelligence in acute care surgerypromise, pitfalls, and a path forward
0
Zitationen
21
Autoren
2025
Jahr
Abstract
While AI holds promise for enhancing ACS, current applications are narrowly focused on pre-operative risk prediction using limited data modalities. Future efforts must prioritize prospective validation, real-time dynamic predictions, clinician-centered design, and multimodal data integration to realize AI's potential for improving ACS patient outcomes in time-sensitive, high-acuity surgical settings.
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Autoren
- Divya Kewalramani
- Kaustav Chattopadhyay
- Justin Benton
- Jason Hua
- Sruti Cheruvu
- Hana Ben Ali
- Shaina Anuncio
- Advika Joshi
- Swati Mylarappa
- Gowthami Vidhya
- Rachel L. Choron
- Amanda L. Teichman
- Jeffrey K. Jopling
- Amin Madani
- Gabriel A. Brat
- Julia Coleman
- Julian Varas Cohen
- Carla M. Pugh
- Philip S. Barie
- Tyler J Loftus
- Mayur Narayan
Institutionen
- Rutgers, The State University of New Jersey(US)
- Johnson University(US)
- Beth Israel Deaconess Medical Center(US)
- University Health Network(CA)
- Johns Hopkins University(US)
- Pontificia Universidad Católica de Chile(CL)
- University of Toronto(CA)
- Cornell University(US)
- Johns Hopkins Medicine(US)
- University of Florida Health(US)
- Stanford Medicine(US)
- Weill Cornell Medicine(US)
- The Ohio State University(US)
- Artificial Intelligence in Medicine (Canada)(CA)