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AI-Driven Zero-Touch Network Orchestration for Tele-Radiology in Resource-Constrained Environments
2026-02-16
medical education
Title + abstract only
View on medRxiv
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BackgroundThe deployment of high-fidelity diagnostic Artificial Intelligence (AI) in resource-constrained environments is hindered by the stochastic nature of network latency and bandwidth limitations. Traditional tele-radiology relies on static cloud offloading, which introduces unacceptable latency for critical care scenarios. Zero-Touch Network and Service Management (ZSM) offers a paradigm for automated network orchestration, yet current frameworks lack application-layer awareness regarding ...
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