RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...

Retrieval augmented generation, or 'RAG' for short, creates a more customized and accurate generative AI model that can greatly reduce anomalies such as hallucinations. As more organizations turn to ...

Drug side effects are a major public health concern, yet off-the-shelf large language models (LLMs) struggle to reliably answer questions about drug side effects due to limited training data and ...

Extracting structured data from free-text medical records at scale is laborious, and traditional approaches struggle in complex clinical domains. We present a novel, end-to-end pipeline leveraging ...