Cargando…

From Data to Wisdom: Biomedical Knowledge Graphs for Real-World Data Insights

Graph data models are an emerging approach to structure clinical and biomedical information. These models offer intriguing opportunities for novel approaches in healthcare, such as disease phenotyping, risk prediction, and personalized precision care. The combination of data and information in a gra...

Descripción completa

Detalles Bibliográficos
Autores principales: Hänsel, Katrin, Dudgeon, Sarah N., Cheung, Kei-Hoi, Durant, Thomas J. S., Schulz, Wade L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10191934/
https://www.ncbi.nlm.nih.gov/pubmed/37195430
http://dx.doi.org/10.1007/s10916-023-01951-2
Descripción
Sumario:Graph data models are an emerging approach to structure clinical and biomedical information. These models offer intriguing opportunities for novel approaches in healthcare, such as disease phenotyping, risk prediction, and personalized precision care. The combination of data and information in a graph model to create knowledge graphs has rapidly expanded in biomedical research, but the integration of real-world data from the electronic health record has been limited. To broadly apply knowledge graphs to EHR and other real-world data, a deeper understanding of how to represent these data in a standardized graph model is needed. We provide an overview of the state-of-the-art research for clinical and biomedical data integration and summarize the potential to accelerate healthcare and precision medicine research through insight generation from integrated knowledge graphs.