Training opportunities of artificial intelligence (AI) in radiology: a systematic review

Floor Schuur, Mohammad H. Rezazade Mehrizi*, Erik Ranschaert

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


The aim is to offer an overview of the existing training programs and critically examine them and suggest avenues for further development of AI training programs for radiologists.

Deductive thematic analysis of 100 training programs offered in 2019 and 2020 (until June 30). We analyze the public data about the training programs based on their “contents,” “target audience,” “instructors and offering agents,” and “legitimization strategies.”

There are many AI training programs offered to radiologists, yet most of them (80%) are short, stand-alone sessions, which are not part of a longer-term learning trajectory. The training programs mainly (around 85%) focus on the basic concepts of AI and are offered in passive mode. Professional institutions and commercial companies are active in offering the programs (91%), though academic institutes are limitedly involved.

There is a need to further develop systematic training programs that are pedagogically integrated into radiology curriculum. Future training programs need to further focus on learning how to work with AI at work and be further specialized and customized to the contexts of radiology work
Original languageEnglish
Pages (from-to)6021-6029
Number of pages9
JournalEuropean Radiology
Issue number8
Early online date15 Feb 2021
Publication statusPublished - Aug 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s).

Copyright 2021 Elsevier B.V., All rights reserved.


  • AI
  • Artificial intelligence
  • Curriculum
  • Radiologists
  • Training


Dive into the research topics of 'Training opportunities of artificial intelligence (AI) in radiology: a systematic review'. Together they form a unique fingerprint.

Cite this