Abstract
Today's radiology trainee must sort through an enormous volume of web-based information and learning resources amidst expanding volumes and complexity of clinical cases. In addition, the complexity of the practicing radiologist's work has become such that there is a need for ready access to the most current and highest-value information to guide image interpretation "in the moment" to support mastery-level practice. Personalized Learning is based on an adaptable computer-based system to deliver contextual knowledge to support every learner based on their preferences, prior experience, and evolving knowledge. We review the historical evolution of personalized education including Intelligent Tutor, the first-of-its-kind machine-learning based model for radiology designed to replace the one-size-fits-all approach to education and training.
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