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Retrieval-augmented generation (RAG) integrates task-specific expert knowledge into large language model (LLM) queries, offering potential to improve diagnostic accuracy, transparency, and decision support. This approach enables LLMs to function as complementary tools for radiologists, helping optimize patient care and meet growing health care demands.
Fink et al. (Wed,) studied this question.