5G, Edge Computing, and AI for Secure and Scalable Cyber-Healthcare Interoperability

Abstract

The integration of 5G, Edge Computing, and Artificial Intelligence (AI) in cyber-healthcare 
interoperability aims at making healthcare data exchange more efficient, secure, and scalable. This 
paper suggests a new paradigm using ultra-low latency of 5G for real-time data transmission, edge 
computing for local data processing, and AI-driven models for intelligent decision-making. The 
integration of these technologies optimizes the dependency of healthcare on services by allowing 
reduced latency with decreased bandwidth, ensuring secure and safe data access. Mathematical 
modeling for network latency, edge efficiency, and the AI-driven predictive decision-making 
analysis is discussed below to evaluate this proposed approach with respect to all performance 
metrics such as data communication speed, and edge efficiency at reduced latency times. A 
comparative analysis with existing methods will show the proposed approach's better performance, 
and it will prove to be a promising solution for next-generation healthcare systems.