Challenges of Radiology education in the era of artificial intelligence

被引:0
|
作者
Gorospe-Sarasua, L. [1 ]
Munoz-Olmedo, J. M. [2 ]
Sendra-Portero, F. [3 ]
de Luis-Garcia, R. [4 ]
机构
[1] Hosp Univ Ramon y Cajal, Serv Radiodiagnost, Madrid, Spain
[2] Hosp Univ La Princesa, Serv Radiodiagnost, Madrid, Spain
[3] Univ Malaga, Fac Med, Serv Radiol & Med Fis, Malaga, Spain
[4] Univ Valladolid, Escuela Ingn Telecomunicac, Valladolid, Spain
来源
RADIOLOGIA | 2022年 / 64卷 / 01期
关键词
Radiology; Training; Artificial intelligence;
D O I
10.1016/j.rx.2020.10.003
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Artificial intelligence is a branch of computer science that is generating great expectations in medicine and particularly in radiology. Artificial intelligence will change not only the way we practice our profession, but also the way we teach it and learn it. Although the advent of artificial intelligence has led some to question whether it is necessary to continue training radiologists, there seems to be a consensus in the recent scientific literature that we should continue to train radiologists and that we should teach future radiologists about artificial intelligence and how to exploit it. The acquisition of competency in artificial intelligence should start in medical school, be consolidated in residency programs, and be maintained and updated during continuing medical education. This article aims to describe some of the challenges that artificial intelligencve can pose in the different stages of training in radiology, from medical school through continuing medical education. (C) 2020 SERAM. Published by Elsevier Espana, S.L.U. All rights reserved.
引用
收藏
页码:54 / 59
页数:6
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