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FHIR R4 resource profiling -- constraining and extending base resources for your specific use case -- is where most of the design effort goes. US Core profiles provide a solid...
Insurance EOBs arrive in dozens of inconsistent formats — PDFs, 835 EDI files, scanned images — and payers routinely reorder line items, bundle codes differently, and apply rates...
Healthcare workflows span multiple bounded contexts — scheduling, insurance, clinical records, billing — that cannot be wrapped in a single database transaction. Event sourcing...
The hardest part of building a digital impression pipeline is not the 3D data processing — it is normalizing across scanner brands. Six different intraoral scanners export in STL...
For tabular clinical data with moderate dataset sizes (thousands, not millions, of records), XGBoost consistently outperformed neural networks in our experiments. The neural...