Edge-Enhanced Collaborative Intelligence in 6G Healthcare Networks
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Updated time:2026-07-23 10:56:23
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Keynote speech
Abstract
Healthcare support turns into one of the persistent challenges for the country like India where diagnosis of diseases is often delayed due to acute shortage of specialist doctors, lack of alertness among the common people, healthcare accessibility in rural and semi-urban regions that are under-served by quality healthcare facilities at low cost and on timely basis. Evolution of 6G networks and edge computing is enabling transformative healthcare applications, including low-cost data acquisition, computer aided diagnosis (CAD) with real-time patient monitoring, and privacy-preserving computation, thereby offering improved latency, reliability, and security in sensitive healthcare environments. This lecture discusses challenges and end-to-end complete solution that includes low-cost non-invasive imaging, edge-IoT architecture coupled with integrated AI-based algorithms for early screening of epithelial cancers from the label-free pathology specimens to facilitate quality and timely healthcare support to the rural people through reliable broadband connectivity. Technologies to be touched upon include autoflurosence (AF) imaging, ML/DL techniques with edge-IoT for timely disease diagnosis while reconfigurable intelligent surface and integrated sensing and communication (ISAC) for wireless connectivity.
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