• Chao Wang, Huanhuan Xie, Shan Wang, Siyu Yang, and Ling Hu.
• Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
• Medicine (Baltimore). 2023 Jan 6; 102 (1): e32518e32518.

AbstractIn the era of artificial intelligence (AI), a great deal of attention is being paid to AI in radiological practice. There are a large number of AI products on the radiological market based on X-rays, computed tomography, magnetic resonance imaging, and ultrasound. AI will not only change the way of radiological practice but also the way of radiological education. It is still not clearly defined about the exact role AI will play in radiological practice, but it will certainly be consolidated into radiological education in the foreseeable future. However, there are few literatures that have comprehensively summarized the attitudes, opportunities and challenges that AI can pose in the different training phases of radiologists, from university education to continuing education. Herein, we describe medical students' attitudes towards AI, summarize the role of AI in radiological education, and analyze the challenges that AI can pose in radiological education.Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.

19 keywords...

hide…