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Enhancing Clinical Decision-Making and Operational Efficiency in Healthcare Using Edge Computing

R. N. RavikumarMarwadi University, Rajkot, IndiaS. AarthiMarwadi University, Rajkot, IndiaGularam MasharipovaAlfraganus University, Тashkent, UzbekistanNilufar NiyazovaNavbakhor SalaevaUrgench State University, Urgench, UzbekistanDilnoz BuriyevaTermez University of Economics and Service, Termez, Uzbekistan
2025en
ABI

Аннотация

Edge computing in healthcare offers significant benefits by improving medical outcomes, enhancing operational efficiency, and supporting real-time clinical decisions. This chapter explores how edge systems build resilient healthcare networks, enabling rapid patient support through data-driven protocols while meeting security and compliance requirements such as HIPAA and GDPR. The proliferation of wearable devices and remote monitoring generates vast medical data, posing challenges in centralized processing due to latency and reliability issues. Edge solutions address this by enabling real-time analysis closer to data sources with reduced network demands. The chapter discusses deployment strategies across hospitals, outpatient clinics, and home care, emphasizing the development of medical-grade edge nodes and fast data transfer mechanisms. Case studies highlight successful predictive analytics using edge-based AI diagnostics, improved cost-efficiency, and patient satisfaction.

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