Conventional Medical Education and the History of Simulation in Radiology

Simulation is a promising method for improving clinician performance, enhancing team training, increasing patient safety, and preventing errors. Training scenarios to enrich medical student and resident education, and apply toward competency assessment, recertification, and credentialing are important applications of simulation in radiology. This review will describe simulation training for procedural skills, interpretive and noninterpretive skills, team-based training and crisis management, professionalism and communication skills, as well as hybrid and in situ applications of simulation training. A brief overview of current simulation equipment and software and the barriers and strategies for implementation are described. Finally, methods of measuring competency and assessment are described, so that the interested reader can successfully implement simulation training into their practice

Review of Artificial Intelligence Training Tools and Courses for Radiologists.

Artificial intelligence (AI) systems play an increasingly important role in all parts of the imaging chain, from image creation to image interpretation to report generation. In order to responsibly manage radiology AI systems and make informed purchase decisions about them, radiologists must understand the underlying principles of AI. Our task force was formed by the Radiology Research Alliance (RRA) of the Association of University Radiologists to identify and summarize a curated list of current educational materials available for radiologists