Evaluating large language model-generated brain MRI protocols: performance of GPT4o, o3-mini, DeepSeek-R1 and Qwen2.5-72B.

Objectives: To evaluate the potential of LLMs to generate sequence-level brain MRI protocols.

Materials And Methods: This retrospective study employed a dataset of 150 brain MRI cases derived from local imaging request forms. Reference protocols were established by two neuroradiologists.

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

Objectives: This study investigated the impact of human-large language model (LLM) collaboration on the accuracy and efficiency of brain MRI differential diagnosis.

Materials And Methods: In this retrospective study, forty brain MRI cases with a challenging but definitive diagnosis were randomized into two groups of twenty cases each. Six radiology residents with an average experience of 6.