Applied ML / knowledge graphPublic case studyPublic case notes, private source
Medical KBQA Knowledge Graph
Built a Chinese medical KBQA system with NER models, Neo4j graph storage, Cypher query generation, and web interfaces.
Problem
Medical FAQ systems need structured domain knowledge and reliable entity extraction instead of simple keyword matching.
Role
Implemented a medical question answering pipeline from entity recognition to graph query and answer generation.
Public evidence
- Public project note on the site
- Technical pipeline summary around NER, graph query, and UI experiments
Verification boundary
- This is an applied ML project, not a clinical product.
- No public source repository is currently linked.
- Medical claims should remain limited to demo/learning context.
No medical advice, patient data, or production healthcare deployment is claimed.