Research graph
References from A Knowledge Graph Framework for Longitudinal Congenital Heart Disease Modeling. Local targets link to admitted publications; unresolved targets remain external evidence.
Pediatric and congenital cardiovascular disease research challenges and opportunities: JACC review topic of the week
10.1016/j.jacc.2022.09.032 · 2022 · External reference
Congenital heart defects in the United States: estimating the magnitude of the affected population in 2010
10.1161/circulationaha.115.019307 · 2016 · External reference
A systematic review on deep learning in ventricular septal defect screening, diagnosis, and management
10.4103/apc.apc_163_25 · 2026 · External reference
Characteristics of in-hospital mortality of congenital heart disease after surgical treatment in children from 2005 to 2017: a single-center experience
10.1186/s12887-021-02935-2 · 2021 · External reference
Post-operative outcomes in children with and without congenital heart disease undergoing noncardiac surgery
10.1016/j.jacc.2015.11.057 · 2016 · External reference
Harnessing EHR data for health research
10.1038/s41591-024-03074-8 · 2024 · External reference
An open-source framework for end-to-end analysis of electronic health record data
10.1038/s41591-024-03214-0 · 2024 · External reference
Meeting the challenges of electronic health record (EHR) optimization
10.1038/s41746-025-02178-w · 2026 · External reference
Learning a health knowledge graph from electronic medical records
10.1038/s41598-017-05778-z · 2017 · External reference
Deep patient: an unsupervised representation to predict the future of patients from the electronic health records
10.1038/srep26094 · 2016 · External reference
Scalable and accurate deep learning with electronic health records
10.1038/s41746-018-0029-1 · 2018 · External reference
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction
10.1038/s41746-021-00455-y · 2021 · External reference
A multimodal vision knowledge graph of cardiovascular disease
10.1038/s44161-025-00757-4 · 2026 · External reference
A comprehensive large-scale biomedical knowledge graph for AI-powered data-driven biomedical research
10.1038/s42256-025-01014-w · 2025 · External reference
Building a knowledge graph to enable precision medicine
10.1038/s41597-023-01960-3 · 2023 · External reference
Graph neural networks
10.1038/s43586-024-00294-7 · 2024 · External reference
Unsupervised word embeddings capture latent knowledge from materials science literature
10.1038/s41586-019-1335-8 · 2019 · External reference
Representation learning to advance multi-institutional studies with electronic health record data from US and France
10.1038/s41467-026-71152-1 · 2026 · External reference
Graph representation learning in biomedicine and healthcare
10.1038/s41551-022-00942-x · 2022 · External reference
A phenotyping algorithm for classification of single ventricle physiology using electronic health records
10.1093/jamiaopen/ooaf035 · 2025 · External reference
Validating publicly available crosswalks for translating ICD-9 to ICD-10 diagnosis codes for cardiovascular outcomes research
10.1161/circoutcomes.118.004782 · 2018 · External reference
Integrated machine learning and multimodal data fusion for patho-phenotypic feature recognition in iPSC models of dilated cardiomyopathy
10.1515/hsz-2024-0023 · 2024 · External reference
Inductive representation learning on large graphs
2017 · External reference
Comparing natural language processing representations of coded disease sequences for prediction in electronic health records
10.1093/jamia/ocae091 · 2024 · External reference
An electronic health record multimodal data integration platform for comprehensive analysis of single ventricle physiology
2025 · External reference
Deepr: a convolutional net for medical records
10.1109/jbhi.2016.2633963 · 2017 · External reference
BEHRT: transformer for electronic health records
10.1038/s41598-020-62922-y · 2020 · External reference
