Differentiating between GPT-generated and human-written feedback for radiology residents.

Purpose: Recent competency-based medical education (CBME) implementation within Canadian radiology programs has required faculty to conduct more assessments. The rise of narrative feedback in CBME, coinciding with the rise of large language models (LLMs), raises questions about the potential of these models to generate informative comments matching human experts and associated challenges. This study compares human-written feedback to GPT-3.