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NODES 26 — November 12, 2026

Building an Explainable GraphRAG System: From Clinical Notes to Knowledge Graphs with Neo4j

Session track: AI Engineering

Session time:

Session description:

Show how to build a complete GraphRAG pipeline that converts unstructured clinical notes into an explainable Neo4j knowledge graph using LLMs. Cover entity extraction, graph modelling, temporal relationships, Cypher queries, GraphRAG retrieval, and lessons learned. Demonstrate how graph-based reasoning provides transparent, evidence-backed answers and discuss how the same architecture can be applied beyond healthcare.

Speaker

photo of Julia Tran

Julia Tran

Data & AI Consultant, Capgemini

Julia Tran is a Data & AI Consultant at Capgemini with experience delivering Neo4j and knowledge graph solutions in healthcare. Her work focuses on transforming complex, connected data into meaningful insights and practical applications.