Neo4j Live: GraphRAG for Smarter Medical AI
Chapters 8
- Play from Welcome and Introductions
- Play from The Risks of AI in Healthcare
- Play from Societal Impact and Trust in AI
- Play from Introducing Adiu Health
- Play from Reducing Doctor Workload with AI
- Play from Limitations of Traditional RAG
- Play from Transition to GraphRAG
- Play from Tripartite GraphRAG Explained
Clinical documentation consumes a significant portion of a doctor’s time, a time better spent on patient care or research. Adiu Health addresses this by combining large language models with a Neo4j-powered knowledge graph to automate consultation summarization and enrich it with contextual medical insights.
In this session, you’ll learn how Adiu Health enhances LLM outputs with graph-based retrieval (GraphRAG), enabling tasks like identifying drug interactions, suggesting alternative treatments, and structuring follow-up recommendations. We’ll walk through the architecture, data modeling choices, and how Neo4j integrates into the overall GenAI workflow.
Guests: Michael Banf & Johannes Kuhn
Resources mentioned
GenAI & GraphRAGKnowledge graphs
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