Abstract: Recent developments in wireless networking, big data technologies including 5G networks, healthcare big data analytics, the Internet of Things (IoT), sophisticated wearable technologies, and artificial intelligence (AI) have made it possible to design intelligent illness diagnostic models. In addition to its critical function in e-health applications, 5G-IoT is becoming a standard feature of intelligent software. Intelligent systems and architectures are necessary for e-health applications to counteract threats to the privacy of patients’ medical information. Using machine learning and IoMT, this research suggests a new approach to cloud data analysis using the 5G network in the context of a recommendation model. This application of the 5G cloud network to the monitoring and analysis of healthcare data makes use of variational adversarial transfer convolutional neural networks. The treatment plan for abnormalities in a tolerant body is derived from this clustered outcome. Experiment analysis was performed for a number of healthcare datasets with respect to training precision, network efficiency, F-1 score, root-mean-squared error, and mean average precision as the metrics of interest.
Keywords: 5G network, cloud data analysis, recommendation model, machine learning, internet of medical things (IoMT)
