Human-AI collaboration in large language model-assisted brain MRI differential diagnosis: a usability study

Abstract

Question While large language models (LLM) have the potential to support radiological differential diagnosis, the role of human-LLM collaboration in this context remains underexplored. Findings LLM-assisted brain MRI differential diagnosis yielded superior accuracy over conventional internet search. Inaccurate case descriptions, LLM hallucinations, and insufficient contextualization were identified as potential challenges. Clinical relevance Our results highlight the potential of an LLM-assisted workflow to increase diagnostic accuracy but underline the necessity to study collaborative efforts between humans and LLMs over LLMs in isolation.