Artificial intelligence (AI) is rapidly transforming acute care surgery (ACS), encompassing trauma, emergency general surgery, and critical care. This article synthesizes key insights from the “Artificial Intelligence in Surgery: The Future is Now” panel session at the 2025 American Association for the Surgery of Trauma Annual Meeting. Panelists discussed current clinical applications including large language models for documentation and evidence synthesis, physiologic foundation models for intensive care unit monitoring, AI-enhanced feedback systems for surgical education, video-based performance analytics, and interpretable risk prediction tools. Emerging technologies including digital twins, augmented reality navigation, and AI-enabled robotics were also examined. Cross-cutting themes emphasized interpretability over opaque “black-box” models, rigorous bias auditing, and the critical importance of external validation and pragmatic human versus human plus AI study designs. Implementation requires robust data infrastructure, institutional governance, and staged deployment prioritizing augmentation over automation. The panel concluded that responsible AI adoption in ACS rests on three pillars: rigorous evaluation standards commensurate with clinical influence, institutional investment in infrastructure and “algorithmic stewardship,” and AI literacy as a core professional competency. Meeting these conditions positions AI to reduce administrative burden and support more precise, equitable care for acutely ill and injured patients.
Kewalramani et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: