Knowledge Graphs in Health
The use of graph databases, semantic technologies, and knowledge graphs for health data integration, clinical decision support, and longitudinal patient records.
Neo4j's research shows healthcare leads in knowledge graph adoption, with CIOs unable "to scale AI without a knowledge graph foundation."[1] Towards Data Science notes healthcare leads other industries in this space.[2]
Major Projects edit
AIDAVA (EU Horizon Europe) edit
AIDAVA — €7.7M (2022–2026). Creates a virtual assistant for automated curation and publishing of personal health data using Personal Health Knowledge Graphs (PHKG) based on SNOMED, FHIR, and LOINC ontologies. 13 partners from 9 countries. Coordinator: Maastricht University. Knowledge graph technology by Ontotext.[3]
OHDSI / OMOP Common Data Model edit
The OHDSI (Observational Health Data Sciences and Informatics) community uses the OMOP Common Data Model for observational health research across 100+ data partners globally. Recent work includes graph visualization and validation of drug mappings using LLMs and the USAGI tool.[4] The Jackalope Plus tool enables post-coordination and ontology development for observational studies.[5]
TriNetX edit
TriNetX operates a global federated real-world data network connecting healthcare organizations. Recently acquired Zetta Genomics to enhance federated genomics data capabilities across its provider network.[6] Also launched NLP services for clinical trial protocol design.[7]
NIH All of Us Research Program edit
The All of Us research program (NIH) collects health data from 1M+ diverse US participants. Plans to add environmental exposures data, building toward a comprehensive longitudinal health knowledge graph.[8]
UK Biobank Knowledge Graph edit
UK Biobank — 500,000 participant biomedical database. AI-powered knowledge graphs link cardiac imaging to genomics and drug predictions.[9]
PubMed Knowledge Graph 2.0 edit
Connects papers, patents, and clinical trials in biomedical science using graph structures. Published in Nature.[10]
OpenEHR edit
OpenEHR is an open standard for clinical health data with archetype-based models. Research shows knowledge graph applications for COVID-19 diagnosis prediction and infection control systems.[11]
GA4GH edit
The Global Alliance for Genomics and Health (GA4GH) develops data standards for genomics. New platforms make genome analyses scalable and reproducible using graph-based approaches.[12]
Technology Platforms edit
Graph Databases edit
- Neo4j — leading graph database, extensive healthcare applications including MedQGraph (Temporal Medical Knowledge Graphs for AI-Driven Healthcare Insights). Snowflake now supports Neo4j graph analytics natively.[13]
- GraphDB (Ontotext) — enterprise knowledge graph database, powers AIDAVA. Now part of Graphwise after merger with Semantic Web Company.[14]
- AllegroGraph (Franz Inc.)' — semantic graph database widely used in life sciences. Supports RDF, SPARQL, and knowledge graph applications for clinical data integration.[15]
- Amazon Neptune — managed graph database, healthcare analytics use cases.[16]
- Stardog — enterprise knowledge graph platform used in life sciences and pharma for data virtualization and reasoning.[17]
- ArangoDB — multi-model database with graph capabilities used in healthcare analytics.[18]
- TigerGraph — scalable graph analytics for clinical data.[19]
Semantic Platforms edit
- PoolParty (Semantic Web Company / Graphwise) — semantic AI platform for health data classification and ontology management. Merged with Ontotext in 2024.[20]
- Elsevier Knowledge Graphs — life sciences knowledge graphs used for drug repurposing, linking literature, patents, and clinical data.[21]
LLM + Knowledge Graphs edit
Large language models are increasingly used to construct and query health knowledge graphs:
- Nature: "Large language model powered knowledge graph construction for mental health exploration"[22]
- Frontiers: "Unlocking electronic health records: a hybrid graph RAG approach to safe clinical AI for patient QA"[23]
- Anthropic: "Advancing Claude in healthcare and the life sciences"[24]
- WHO: "An epidemiological knowledge graph extracted from Disease Outbreak News"[25]
FHIR + Graph Integration edit
- SMART on FHIR — open standards platform enabling third-party apps to access clinical data via FHIR APIs. Knowledge graph integration enables semantic queries across patient records.[26]
- HL7 FHIR Bulk Data — enabling population-level data export for research. "What Bulk FHIR can do for quality measurement and more."[27]
- MedCity News: "Beyond the Buzzword: Why Semantic Interoperability is the Holy Grail for Digital Health"[28]
Technology Stack edit
Common technologies used in health knowledge graphs:
- Graph Databases: Neo4j, GraphDB (Ontotext), AllegroGraph (Franz Inc.), Amazon Neptune, Stardog, TigerGraph, ArangoDB
- Standards: RDF, OWL, SPARQL, SHACL, Property Graph
- Health Ontologies: SNOMED CT, LOINC, HL7 FHIR, ICD-10/11, OMOP CDM, OpenEHR archetypes
- Integration: ETL pipelines, FHIR APIs, SMART on FHIR, Bulk FHIR, NLP extractors
- AI/ML: Graph neural networks, LLMs for KG construction, embedding models, RAG over graphs
See Also edit
- ↑ Neo4j (2025): "Why Healthcare CIOs Can't Afford to Scale AI Without a Knowledge Graph Foundation" — https://neo4j.com/blog/healthcare-knowledge-graph-ai/
- ↑ Towards Data Science: "Why Healthcare Leads in Knowledge Graphs" — https://towardsdatascience.com
- ↑ European Commission CORDIS, Grant 101057062 — https://cordis.europa.eu/project/id/101057062
- ↑ medRxiv (2025): "Rx Norm for Europe — Toward the representation of medicinal products in the OMOP CDM" — https://www.medrxiv.org
- ↑ Nature (2025): "Jackalope Plus tool for post-coordination, ontology development" — https://www.nature.com
- ↑ BeBeez International (2025): "TriNetX Enhances its Ability to Federate Genomics Data" — https://www.bebeez.it
- ↑ Tech Networks (2025): "TriNetX Unveils Natural Language Processing Service" — https://www.technetworks.com
- ↑ NIH/NIEHS (2025): "'All of Us' study plans to add environmental exposures" — https://www.niehs.nih.gov
- ↑ Medical Xpress (2025): "AI-powered knowledge graph links heart images to genes and drug predictions" — https://medicalxpress.com
- ↑ Nature (2025): "PubMed knowledge graph 2.0" — https://www.nature.com
- ↑ Nature (2023): "Prediction of COVID-19 diagnosis based on openEHR artefacts" — https://www.nature.com
- ↑ Berlin Institute of Health (2025): "New platform makes genome analyses scalable and reproducible" — https://bih-charite.de
- ↑ Neo4j (2025): "MedQGraph: TMKGs for AI-Driven Healthcare Insights" — https://neo4j.com
- ↑ PR Newswire (2024): "Semantic Web Company and Ontotext Merge to Create Graphwise" — https://www.prnewswire.com
- ↑ Franz Inc.: "AllegroGraph" — https://franz.com/agraph
- ↑ AWS (2025): "Building health care agents using Amazon Bedrock AgentCore" — https://aws.amazon.com
- ↑ Databricks (2025): "Democratize insight with generative AI and knowledge graphs" — https://www.databricks.com
- ↑ MarketsandMarkets (2025): "Knowledge Graph Market Report 2025-2030" — https://www.marketsandmarkets.com
- ↑ Frontiers (2025): "A solution for combining multi-source heterogeneous data to construct enterprise knowledge graph" — https://www.frontiersin.org
- ↑ TheRecursive (2024): "Graphwise — A Content Management Platform and a Graph Database Come Together" — https://therecursive.com
- ↑ Elsevier (2025): "How knowledge graphs can supercharge drug repurposing" — https://www.elsevier.com
- ↑ Nature (2025) — https://www.nature.com
- ↑ Frontiers (2025) — https://www.frontiersin.org
- ↑ Anthropic (2025) — https://www.anthropic.com
- ↑ Nature (2025) — https://www.nature.com
- ↑ OCNJ Daily (2026): "10 Best FHIR Software Development Companies" — https://ocnjdaily.com
- ↑ Healthcare IT News (2025) — https://www.healthcareitnews.com
- ↑ MedCity News (2025) — https://medcitynews.com