The curriculum for the AI Literacy Course curriculum was developed with a focus on promoting practical and clinically relevant AI experience for radiology trainees and establishing a foundational knowledge base. The course begins with Two 30-minute lectures were held each day from October 4-8 and broadcast via Zoom; lecturers were not recorded. To align with the “noon conference” time frame for the host institution, lectures were held from 12-1pm CST, with additional extra time allotted on the first day of the course to allow for the course introduction. The course was available free of charge to all residents, fellows, attendings, and medical students on radiology rotations at participating institutions at the time of the course.

The course will begin with introductory didactic lectures on fundamental terminology and methods of AI, followed by a series of subspecialty-based lectures (Pediatric Radiology, Neuroradiology, Abdominal Imaging, etc.), and then special topics based lectures (Economics and Ethics of AI, Algorithm Bias, The Future of AI in Radiology, etc.). The course concludes with a “Hands-on” session with an FDA approved AI algorithm. In this session, participants will be given a guided introduction to the application and will have the opportunity to complete curated cases/experiences on their own computer.

The course is designed to incorporate feedback from participants and partner programs. Lecturers are encouraged to highlight their areas of expertise, emerging technologies, and clinical AI tools they find relevant to learners. Participants can suggest topics or recommend areas of interest for future courses during the midweek feedback session or in the post-course survey. Most subspecialty and special topics sessions will rotate on a two year cycle, however “Ethics of AI” is planned to recur with each session. A session on the ethics of AI allows course directors to discuss the role physicians and researchers must play to ensure AI advances health equity instead of deepening health disparities and is fundamental to the mission of the AI Literacy Course.