Chrisolande/Medical-Research-Assistant
A comprehensive RAG pipeline combining knowledge graphs, vector search, and LLM generation for medical document analysis. Features semantic caching, advanced reranking, and modular architecture for scalable knowledge discovery from medical literature.
This tool helps medical researchers and clinicians quickly find answers to complex questions by analyzing medical literature. You input your research question or search topic, and it processes medical articles, abstracts, and MeSH terms. It then generates concise, evidence-based answers, saving significant time in literature review and knowledge discovery.
Use this if you need to rapidly extract and synthesize information from a large collection of medical documents or perform targeted searches on PubMed to get direct answers to your clinical or research inquiries.
Not ideal if you need to perform statistical analysis on structured datasets, visualize trends across many studies, or require human expert judgment for every step of your literature review.
Stars
12
Forks
2
Language
Python
License
MIT
Category
Last pushed
Jan 07, 2026
Commits (30d)
0
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