The Year in Graduate Medical Education: Selected Highlights from 2023

被引:1
作者
Patel, Saumil J. [1 ]
Notarianni, Andrew P. [2 ]
Martin, Archer Kilbourne [3 ]
Tsai, Albert [4 ]
Pulton, Danielle A. [5 ]
Linganna, Regina E. [1 ]
Bhatte, Sai [6 ]
Montealegre-Gallegos, Mario [2 ]
Patel, Bhoumesh [2 ]
Waldron, Nathan H. [3 ]
Nimma, Sindhuja R. [3 ]
Kothari, Perin [4 ]
Kiwakyou, Larissa [4 ]
Baskin, Sean M. [5 ]
Feinman, Jared W. [1 ]
机构
[1] Perelman Sch Med, Dept Anesthesiol & Crit Care, Philadelphia, PA USA
[2] Yale Univ, Sch Med, Dept Anesthesiol, Cardiothorac Div, New Haven, CT USA
[3] Mayo Clin, Dept Anesthesiol & Perioperat Med, Div Cardiovasc & Thorac Anesthesiol, Jacksonville, FL USA
[4] Stanford Univ, Sch Med, Dept Anesthesiol Perioperat & Pain Med, Div Cardiothorac Anesthesiol, Stanford, CA USA
[5] Temple Univ Hosp & Med Sch, Lewis Katz Sch Med, Dept Anesthesiol, Philadelphia, PA USA
[6] Perelman Sch Med, Philadelphia, PA USA
关键词
ARTIFICIAL-INTELLIGENCE; ANESTHESIOLOGY; SIMULATION; SAFETY;
D O I
10.1053/j.jvca.2024.05.003
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
This special article is the third in an annual series of the Journal of Cardiothoracic and Vascular Anesthesia that highlights significant literature from the world of graduate medical education published over the past year. Major themes addressed in this review include the potential uses and pitfalls of artificial intelligence in graduate medical education, trainee well-being and the rise of unionized house staff, the effect of gender and race/ethnicity on residency application and attrition rates, and the adoption of novel technologies in medical simulation and education. The authors thank the editorial board for again allowing us to draw attention to some of the more interesting work published in the field of graduate medical education during 2023. We hope that the readers find these highlights thought-provoking and informative as we all strive to successfully educate the next generation of anesthesiologists. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:2906 / 2914
页数:9
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