Imagine learning to read X-rays and CT scans. You write a report, and an AI gives you instant feedback on what you missed. That's the promise of large language models (LLMs) in medical imaging education, according to a new review of 7 studies.
The review found that when radiology residents and fellows used LLMs for automated feedback, their report quality, diagnostic accuracy, and efficiency in spotting discrepancies all improved. Trainees liked it too, and many said they preferred a hybrid model where AI and human experts work together.
But here's the catch: the evidence is still early and limited. The studies were small, used different methods, and didn't compare LLMs against standard teaching. Also, fine-tuned models did better than general-purpose ones, but their agreement with expert humans varied.
So while AI shows promise as a teaching tool, human oversight remains essential. More research is needed before we know if this approach truly boosts long-term learning.
