Granular Segmentation Benchmark on Synthetic FHIR Cohort
Benchmarking consent thresholds on a ~10k Synthea cohort for throughput, precision, and cost.
Why I Built This
Privacy-preserving architectures are easy to pitch, but hard to operationalize without hard numbers. I built this benchmark to measure what happens when consent-aware segmentation runs at cohort scale, including latency, throughput, and cost behavior. This gave us concrete evidence for design tradeoffs instead of assumptions.
What I Evaluated
- Consent-threshold behavior on large synthetic cohorts.
- Throughput, precision tradeoffs, and operational cost behavior under realistic load.
- Sensitivity-labeling effects across segmentation scenarios.
Outcome
A benchmark baseline that helped prioritize engineering decisions for scalable consent-aware clinical pipelines.