Moira E Smith, C Christopher Zalesky, Sangil Lee, Michael Gottlieb, Srikar Adhikari, Mat Goebel, Martin Wegman, Nidhi Garg, Samuel H F Lam
{"title":"Artificial Intelligence in Emergency Medicine: A Primer for the Nonexpert.","authors":"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","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":73967,"journal":{"name":"Journal of the American College of Emergency Physicians open","volume":"6 2","pages":"100051"},"PeriodicalIF":1.9000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11874537/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American College of Emergency Physicians open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.acepjo.2025.100051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"EMERGENCY MEDICINE","Score":null,"Total":0}
引用次数: 0
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.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
