Systematic review of artificial intelligence competitions in radiology: a focus on design, evaluation, and trends

Abstract

This article explores the characteristics and scope of artificial intelligence (AI) competitions in medical imaging. A retrospective evaluation of AI competitions related to medical imaging was conducted between 2017 and 2023. Relevant terms associated with AI and competitions were searched using the PubMed database and the grand-challenge website, and applicable studies were included in the review. The 26 AI competitions included in the review covered a wide range of topics, from brain imaging to extremities and from stroke detection to bone age estimation, with many organized through international collaborations between engineering and medical professionals. Various national screening and teleradiology databases, as well as university databases, were used. Teams from different regions worldwide participated in these competitions. These initiatives contribute to the global adoption of AI technologies in healthcare. Moreover, they help raise awareness among high school students, medical students, radiology trainees, and young radiologists of the intersection between AI and medical imaging. AI competitions play a crucial role in fostering collaboration between the medical field and AI, driving innovation, and increasing societal awareness of AI applications in healthcare.

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