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Current vision-language models can generate fluent medical explanations, but struggle to ground them in relevant visual evidence, especially in emotionally charged scenarios.
Ditch the slow external knowledge base: this new method bakes clinical knowledge directly into LLMs for lightning-fast, state-of-the-art healthcare predictions.