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Federated Bayesian Surveillance of Mechanical Thrombectomy Adverse Events
US & West ·
The work treats population-scale adverse-event surveillance as a distinct belief layer of a surgical digital twin, evaluated with a federated Bayesian protocol under formal privacy guarantees: sites exchange only differentially private natural-parameter updates. Benchmarking uses the full FDA MAUDE cohort for thrombus-retrieval catheters — 8,617 reports, 6,491 classified into five complication classes across eight manufacturer sites.
Why it matters
It demonstrates how to pool fragmented industry data for risk estimation without centralising sensitive information — a transferable pattern for sectoral digital twins.
arXiv:2610.31864v1 Announce Type: new Abstract: Existing stealthy attacks presuppose white- or grey-box access to the target system, unrealistic in practice. This paper develops a model-free stealthy attack framework that learns an attack policy directly from nominal measurement data, without…
Wireless digital twins (DTs) are increasingly integrated with artificial intelligence to support online modeling, prediction, and network optimization. However, most existing approaches perform adaptation within predefined learning or optimization structures, which may become unsuitable when…
