Artificial Intelligence Curriculum Needs Assessment for a Pediatric Radiology Fellowship Program: What, How, and Why?

Academic Radiology (06/22) Velez-Florez, Maria Camila; Ghosh, Adarsh; Patton, Daniela; et al.

A focus group study assessed the need for developing an artificial intelligence (AI) curriculum in pediatric radiology training and continuing education. The assessment measured seven radiology trainees and attending radiologists' perceptions of AI, perceived competence in interpreting AI literature, and perceived expectations from radiology AI education. The authors identified AI knowledge, previous training, learning preferences, AI expectations, and AI concerns as core themes. Most participants supported a case-based approach to AI education and said that a lack of understanding affected AI's clinical applicability. They also echoed the need for better training in interpreting and applying AI literature in practice. The authors recommend the AI curriculum must factor in a broad spectrum of learners' interests and needs. "Teaching the interpretation of AI research methods, literature critique, and quality control through implementation of specific scenarios could engage a variety of trainees from different backgrounds and interest levels while ensuring a baseline level of competency in AI," they suggest.

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