Neo4j Live: GraphRAG for Smarter Medical AI

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
https://www.linkedin.com/in/johannes-kuhn-ai/
https://www.linkedin.com/in/michaelbanf/

Adiu Health: https://www.adiu-health.de/

0:00 – Welcome and Introductions
4:30 – The Risks of AI in Healthcare
6:29 – Societal Impact and Trust in AI
10:07 – Introducing Adiu Health
12:19 – Reducing Doctor Workload with AI
17:24 – Limitations of Traditional RAG
23:06 – Transition to GraphRAG
32:11 – Tripartite GraphRAG Explained

#neo4j #graphdatabase #genai #graphrag #knowledgegraph #llm #lifescience #healthcare