Edge-Med: Optimizing ethical HCI for real-time healthcare via edge-AI Integration

Run Zhong; Lei Yang

doi:10.33545/26649845.2025.v7.i2b.336

Edge-Med: Optimizing ethical HCI for real-time healthcare via edge-AI Integration

Author(s):

Run Zhong and Lei Yang

Abstract:

This study addresses critical gaps in decentralized healthcare systems by proposing Edge-Med an integrated framework combining edge computing with human-centered AI. Targeting time-sensitive medical interventions (e.g., fall detection, stroke prediction), we resolve the fundamental conflict between operational efficiency and ethical compliance through three innovations.

DOI: 10.33545/26649845.2025.v7.i2b.336

Pages: 149-151 | 507 Views 167 Downloads

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International Journal of Social Science and Education Research

How to cite this article:

Run Zhong and Lei Yang. Edge-Med: Optimizing ethical HCI for real-time healthcare via edge-AI Integration. Int. J. Social Sci. Educ. Res. 2025;7(2):149-151. DOI: 10.33545/26649845.2025.v7.i2b.336

Vol. 7, Issue 2, Part B (2025)

Edge-Med: Optimizing ethical HCI for real-time healthcare via edge-AI Integration

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