Artificial intelligence (AI) is poised to revolutionize radiology training, providing tools for tasks like image interpretation, triaging, reporting, and personalized learning. However, integrating AI into radiology education requires addressing diverse perspectives from stakeholders such as attendings, residents, fellows, medical students, and researchers. Tailored AI-enhanced curricula and best practice guidelines are essential to meet these needs and optimize training programs. This session, led by residents and a senior radiologist from major academic institutions, will explore literature, methods, and current industry applications of AI in radiology training. Through group discussions and survey results, participants will gain actionable insights to implement AI effectively in their educational settings.

Objectives

• Explain best practices for integrating AI into radiology and subspecialty training.
• List methods by which AI enhances radiology and other medical training.
• Discuss varied viewpoints on the optimal use of AI in radiology education.
• Use best practices to implement AI-enhanced workflows in their institutions.