Artificial Intelligence in Emergency Medicine: A Primer for the Nonexpert

Moira E. Smith; C. Christopher Zalesky; Sangil Lee; Michael Gottlieb; Srikar Adhikari; Mat Goebel; Martin Wegman; Nidhi Garg; Samuel H.F. Lam

doi:10.1016/j.acepjo.2025.100051

Artificial Intelligence in Emergency Medicine: A Primer for the Nonexpert

Moira E. Smith, C. Christopher Zalesky, Sangil Lee, Michael Gottlieb, Srikar Adhikari, Mat Goebel, Martin Wegman, Nidhi Garg, Samuel H.F. Lam

Emergency Medicine

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Artificial intelligence (AI) is increasingly being utilized to augment the practice of emergency medicine due to rapid technological advances and breakthroughs. AI applications have been used to enhance triage systems, predict disease-specific risk, estimate staffing needs, forecast patient decompensation, and interpret imaging findings in the emergency department setting. This article aims to help readers without formal training become informed end-users of AI in emergency medicine. The authors will briefly discuss the principles and key terminology of AI, the reasons for its rising popularity, its potential applications in the emergency department setting, and its limitations. Additionally, resources for further self-studying will also be provided.

Original language	English (US)
Article number	100051
Journal	JACEP Open
Volume	6
Issue number	2
DOIs	https://doi.org/10.1016/j.acepjo.2025.100051
State	Published - Apr 2025

Keywords

artificial intelligence
education
informatics
machine learning
natural language processing
neural networks

ASJC Scopus subject areas

Emergency Medicine

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10.1016/j.acepjo.2025.100051

Cite this

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title = "Artificial Intelligence in Emergency Medicine: A Primer for the Nonexpert",

abstract = "Artificial intelligence (AI) is increasingly being utilized to augment the practice of emergency medicine due to rapid technological advances and breakthroughs. AI applications have been used to enhance triage systems, predict disease-specific risk, estimate staffing needs, forecast patient decompensation, and interpret imaging findings in the emergency department setting. This article aims to help readers without formal training become informed end-users of AI in emergency medicine. The authors will briefly discuss the principles and key terminology of AI, the reasons for its rising popularity, its potential applications in the emergency department setting, and its limitations. Additionally, resources for further self-studying will also be provided.",

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AU - Lee, Sangil

AU - Gottlieb, Michael

AU - Adhikari, Srikar

AU - Goebel, Mat

AU - Wegman, Martin

AU - Garg, Nidhi

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Artificial Intelligence in Emergency Medicine: A Primer for the Nonexpert

Abstract

Keywords

ASJC Scopus subject areas

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