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

Objectives 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. Methods 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.” Results 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. Conclusions 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 wor