Digital Twin Models Simulate Diabetes Progression
This study develops ontology-guided, simulation-capable DTs that model diabetes risk and progression using public health data. It applies standardized ontological structures to organize patient and population-level inputs and creates simulation-ready digital twins for longitudinal trajectory modeling. The approach enables risk stratification and scenario testing to support diabetes research and public-health planning.
Scoring Rationale
Notable research that advances simulation-capable digital twin methodology for chronic disease modeling, offering practical utility for researchers and public-health modelers.
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