<ul><li>Automated radiology report generation (RRG) using large language models (LLMs) has the potential to reduce radiologists' workload.</li><li>A retrieval-augmented generation approach is proposed, leveraging multimodal retrieval and LLMs for radiology report generation.</li><li>The method extracts key phrases from radiology reports using LLMs, focusing on essential diagnostic information.</li><li>The approach achieves state-of-the-art results on evaluation metrics and demonstrates robust generalization for multi-view report generation.</li></ul>

Leveraging LLMs for Multimodal Retrieval-Augmented Radiology Report Generation via Key Phrase Extraction

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