Servicio de Radiodiagnóstico, Hospital Universitario Ramón y Cajal, Madrid, Spain.
Servicio de Radiodiagnóstico, Hospital Universitario de La Princesa, Madrid, Spain.
Radiologia (Engl Ed). 2022 Jan-Feb;64(1):54-59. doi: 10.1016/j.rxeng.2020.10.012.
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.
人工智能是计算机科学的一个分支，它在医学领域，特别是在放射学领域引起了极大的期望。人工智能不仅将改变我们实践专业的方式，也将改变我们教授和学习的方式。尽管人工智能的出现导致一些人质疑是否有必要继续培训放射科医生，但最近的科学文献似乎达成了共识，即我们应该继续培训放射科医生，我们应该向未来的放射科医生教授人工智能以及如何利用它。人工智能能力的获得应该从医学院开始，在住院医师培训计划中得到巩固，并在继续医学教育中得到维护和更新。本文旨在描述人工智能在放射学培训的不同阶段（从医学院到继续医学教育）可能带来的一些挑战。
