B5G and Explainable Deep Learning Assisted Healthcare Vertical at the Edge: COVID-I9 Perspective

• Published in: IEEE network Vol. 34; no. 4; pp. 98 - 105
• Main Authors: Rahman, Md. Abdur, Hossain, M. Shamim, Alrajeh, Nabil A., Guizani, Nadra
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Algorithms; Cloud computing; Coronaviruses; COVID-19; Datasets; Decision making; Deep learning; Edge computing; Health care; Hospitals; Image edge detection; Infectious diseases; Machine learning; Network latency; Semantics; Solid modeling; Training; Vaccines; Wireless networks

B5G-based tactile edge learning shows promise as a solution to handle infectious diseases such as COVID-19 at a global level. By leveraging edge computing with the 5G RAN, management of epidemic diseases such as COVID-19 can be conducted efficiently. Deploying a hierarchical edge computing architect...