Congenital heart diseaseCohort study
A Knowledge Graph Framework for Longitudinal Congenital Heart Disease Modeling
- knowledge graph-based framework
- longitudinal knowledge graph
- Term frequency-inverse document frequency and Word2Vec approaches
Authors' conclusion
This knowledge graph framework provides a scalable approach for preserving temporal and relational clinical context and enable trajectory-aware modeling of longitudinal cardiovascular EHR data in patients with CHD.
Study context
- Population
- Patients with congenital heart disease (CHD) in a cardiovascular magnetic resonance cohort, longitudinal electronic health record (EHR) data
Main finding
As reported in the abstract
Retrospective identification of single ventricle physiology and capture of clinically meaningful patterns
- the framework captured clinically meaningful patterns and supported retrospective identification of single ventricle physiology as a representative use case
Observational data: associations, not effects.
Original publication
A Knowledge Graph Framework for Longitudinal Congenital Heart Disease Modeling. JACC Adv. Published 3 October 2026. doi:10.1016/j.jacadv.2026.103291
Summarised from the published abstract; every number is checked against it