Sep 2026· Journal of the American College of Emergency Physicians Open· Vol 7· 0 citations· 51 references
Medicine
Abstract
The rapid integration of artificial intelligence (AI) into emergency department workflows has outpaced clinician training, vendor evaluation infrastructure, and specialty-wide governance. Emergency physicians increasingly encounter AI tools spanning triage, imaging, clinical decision support, documentation, and operations, yet most lack the foundational skills to critically evaluate or safely oversee these products. Without a unified framework, departments struggle to distinguish safe tools from risky ones, and no national standard exists to guide education, vetting, or implementation. This expert consensus opinion, an official work product of the American College of Emergency Physicians (ACEP) AI Task Force formally endorsed by the ACEP Board of Directors in 2025, proposes 3 coordinated priorities to address these gaps. Educate: outlines a standardized AI education framework spanning residency training through continuing medical education, anchored in existing specialty-specific competencies. Evaluate: proposes an expert-derived, structured, clinician-led three-stage framework for vetting AI tools and industry partners prior to deployment. Advise: calls for the establishment of a national Emergency Medicine AI Advisory Council to issue shared terminology, best-practice guidance, and implementation toolkits across academic, community, and critical access settings. Together, these recommendations provide an adaptable, expert-derived foundation for ensuring that AI integration in emergency medicine is safe, equitable, and clinically effective.
Background: Artificial intelligence (AI) is rapidly transforming laboratory medicine by integrating it into diagnostic interpretation, digital pathology, molecular diagnostics, laboratory automation, quality management systems, and predictive analytics. While AI competency frameworks have emerged across health professi...
Ahmed M. Hjazi· Recent advances in Evolution...· 0 citations
This narrative review seeks to synthesize current literature on the applications, benefits, limitations, and future directions of AI in emergency medicine education across undergraduate, graduate, and continuing medical education for medical educators.
Jessica Pelletier, Juan Pablo Arango-Ibañez, R. Taylor et al.· American Journal of Emergenc...· 0 citations
Artificial intelligence (AI) is increasingly incorporated into clinical screening and diagnostic workflows worldwide. However, the effectiveness and safety of AI implementation depend largely on physicians’ readiness, including their knowledge, attitudes, and perceived barriers. In Saudi Arabia, where healthcare digita...
Haneen Abu Alsoud, Abdulhameed Abu Alsoud, Abdulelah K. Alqawlaq et al.· Medicine· 0 citations
Emergency departments (EDs) operate under time pressure, diagnostic uncertainty, and cognitive overload. Artificial intelligence (AI)–driven clinical decision support systems (CDSS) promise to enhance diagnostic accuracy, risk stratification, and workflow efficiency. However, translation from algorithmic performance to...
Ritu Khandelwal, C. Gadkari, Aditya Pundkar et al.· International Journal of Eme...· 0 citations
A three-tier curricular organization is proposed: baseline competencies for all physicians; proficient competencies for physicians involved in local appraisal and implementation of AI systems; and advanced competencies for clinician-scientists, institutional leaders, and professionals with formal responsibilities in AI...
João Frutuoso, A. Maria, Helena Donato et al.· Acta Médica Portuguesa· 0 citations
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