An arXiv preprint, Towards End-to-End Privacy-Preserving AI for Real-Time ECG Monitoring, describes a shift in healthcare AI away from centralized archives and toward distributed pipelines. These pipelines combine wearables, edge processing, cloud analytics, and multi-institutional learning.
The abstract frames real-time electrocardiogram monitoring as a central case for this transition. In this setting, the paper argues, privacy protection cannot be an afterthought; it must be built end-to-end into the AI pipeline.
Because this digest is based on a single source, there are no independent findings to compare. The available abstract is truncated, so details beyond the overall framing are not covered here.