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Found 2 papers, 2 papers with code
Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation
We introduce a novel graph-based Retrieval-Augmented Generation (RAG) framework specifically designed for the medical domain, called \textbf{MedGraphRAG}, aimed at enhancing Large Language Model (LLM) capabilities for generating evidence-based medical responses, thereby improving safety and reliability when handling private medical data.
Medical SAM 2: Segment medical images as video via Segment Anything Model 2
Medical image segmentation plays a pivotal role in clinical diagnostics and treatment planning, yet existing models often face challenges in generalization and in handling both 2D and 3D data uniformly.
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