BiomedRAG: Elevating Biomedical Data Analysis with Retrieval-Augmented Generation in Large Language Models

The emergence of large language models (LLMs) has profoundly influenced the field of biomedicine, providing critical support for synthesizing vast data. These models are instrumental in distilling complex information into understandable and actionable insights. However, they face significant challenges, such as generating incorrect or misleading information. This phenomenon, known as hallucination, can negatively impact the […]

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