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Retrieval Augmented Generation Using PubMed For Precision Health Recommendations by Parul Ramteke is a document available to read on EtoBox.

What is Retrieval Augmented Generation Using PubMed For Precision Health Recommendations about?

This capstone project report by Parul Ramteke presents a framework for Retrieval-Augmented Generation (RAG) using PubMed to enhance precision health recommendations. The proposed system integrates a Query Processing Engine, PubMed Retrieval Engine, LLM Generation Module, and a Validation Layer to minimize hallucinations and provide traceable health advice. Evaluation results indicate that the RAG model significantly outperforms standard LLMs in accuracy and reduces the generation of false information.

Author

Parul Ramteke

Language

EN