A Secure Architecture for Deploying Machine Learning Models in Distributed Healthcare Settings
German Medical Science (German Research Foundation)
Abstract
Introduction: This work presents a proposed architecture that enables the secure deployment of machine learning (ML) models in distributed healthcare environments. ML models are typically developed in centralized environments, but their deployment in healthcare occurs in decentralized, highly protected [for full text, please go to the a.m. URL]
Authors 0
- Author list not loaded yet.
Cited by 0 stored of 0
No patents citing this paper on Lens.org (checked 2026-10-06).