Artificial intelligence for precision education in radiology

In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (Al) is capable of learning without explicit instruction and has emerging applications in medicine, particularly radiology. Whereas much attention has focused on teaching radiology trainees about Al, here our goal is to instead focus on how Al might be developed to better teach radiology trainees. While the idea of using Al to improve education is not new, the application of Al to medical and radiological education remains very limited. Based on the current educational foundation, we highlight an Al-integrated framework to augment radiology education and provide use case examples informed by our own institution's practice. The coming age of Al-augmented radiology may enable not only precision medicine but also what we describe as precision medical education, where instruction is tailored to individual trainees based oi their learning styles and needs.