Artificial intelligence education in medical imaging: A scoping review

Background

The rise of Artificial intelligence (AI) is reshaping healthcare, particularly in medical imaging. In this emerging field, clinical imaging personnel need proper training. However, formal AI education is lacking in medical curricula, coupled with a shortage of studies synthesising the availability of AI curricula tailored for clinical imaging personnel. This study therefore addresses the question “what are the current AI training programs or curricula for clinical imaging personnel?”

Methods

This review follows Arksey & O'Malley's framework and the PRISMA Extension for Scoping Reviews checklist. Six electronic databases were searched between June and September 2023 and the screening process comprised two stages. Data extraction was performed using a standardised charting form. Data was summarised in table format and thematically.

Results

Twenty-two studies were included in this review. The goals of the curriculum include enhancing AI knowledge through the delivery of educational content and encouraging practical application and skills development in AI. The learning objectives comprise technical proficiency and model development, foundational knowledge and understanding, literature review and information utilisation, and practical application and problem-solving skills. Course content spanned nine areas, from fundamentals of AI to imaging informatics. Most curricula adopted an online mode of delivery, and the program duration varied significantly. All programs utilised didactic presentations, with several incorporating additional teaching methods and activities to fulfil curriculum goals. The target audiences and participants primarily involved radiology residents, while the creators and instructors comprised a multidisciplinary team of radiology and AI personnel. Various tools and resources were utilised, encompassing online courses and cloud-based notebooks. The curricula were well-received by participants, and time constraint emerged as a major challenge.

Conclusion

This scoping review provides an overview of the AI educational programs from existing literature to guide future developments in AI educational curricula. Future education efforts should prioritise evidence-based curriculum design, expand training offerings to radiographers, increase content offerings in imaging informatics, and effectively utilise different teaching strategies and training tools and resources in the curriculum.