Implementing Microhospital Emergency Medicine in an Academic Emergency Department: A Framework for Academic Health Systems [0.03%]
学术医疗体系中微医院急诊医学的实施：学术医疗机构急诊部门应急医学实施框架
Sean A Mackman,Brady Bollinger,Anshul Bhatnagar et al.
Sean A Mackman et al.
Background: Academic emergency medicine faces significant challenges, including capacity constraints at tertiary care centers and financial stressors. Obj...
Measuring Pediatric Disaster Readiness of United States Emergency Departments [0.03%]
美国急诊科儿科灾难应对能力的评估
Sarita Chung,Deanna Dahl-Grove,David McCarthy et al.
Sarita Chung et al.
Objectives: The state of pediatric disaster readiness of United States emergency departments is largely unknown. Using the questions from the National Pediatric Readiness Project (NPRP) 2021 assessment, we sought to defin...
Antony Hsu,Michael A Light,Callan Fockele et al.
Antony Hsu et al.
Homelessness is a growing public health crisis across the United States. Emergency physicians are uniquely positioned to address immediate medical concerns and the underlying social drivers of health for patients experiencing homelessness. ...
Xiangnan Li,Rui Fu,Xiaoming Zhou et al.
Xiangnan Li et al.
A Machine Learning Strategy to Predict the Number of High-Acuity Children Who Leave Without Being Seen From the Emergency Department [0.03%]
一种预测急诊科高重症儿童离开人数的机器学习策略
Brandon Kappy,Patrick Butler,Yiqi Su et al.
Brandon Kappy et al.
Objectives: The purpose of this study was to create an operationally useful machine learning model that predicts the number of high-acuity left without being seen (LWBS) patients from the pediatric emergency department (E...
Progressed Ulcerative Chest Wall Mass: A Case of Delayed Diagnosis and Intervention [0.03%]
迟发型诊断和治疗的溃疡型胸部肿块病例报告
Shreya Suresh,Eric Shipley,Jou-Tzu Jennifer Chen
Shreya Suresh
What Do We Mean When We Say "AI?" Why Context-Not Volume-Should Guide Emergency Medicine [0.03%]
当我们说“AI”时我们在谈论什么？为什么应该用场景（而非体量）来指导急诊医学中的人工智能应用？
Christian Rose,Carl Preiksaitis
Christian Rose
Early Insights Among Emergency Medicine Physicians on Artificial Intelligence: A National, Convenience-sample Survey of the American College of Emergency Physicians [0.03%]
美国急诊医师协会便利抽样调查中的早期见解：关于人工智能的全国性调查
Bradley D Shy,Cristiana Baloescu,Isaac V Faustino et al.
Bradley D Shy et al.
Objectives: This study aimed to assess the current utilization of artificial intelligence (AI) tools among emergency physicians, their attitudes toward AI in clinical practice, and how a national physician professional or...
Julia Isaacson,Jennifer Frush,Andrew Mittelman
Julia Isaacson
Understanding and Addressing Bias in Artificial Intelligence Systems: A Primer for the Emergency Medicine Physician [0.03%]
理解并解决人工智能系统中的偏见：急诊医师入门指南
Ethan E Abbott,Tehreem Rehman,Anthony Rosania et al.
Ethan E Abbott et al.
Artificial intelligence (AI) tools and technologies are increasingly being integrated into emergency medicine (EM) practice, not only offering potential benefits such as improved efficiency, better patient experience, and increased safety, ...