Abstract:
As more and more medical devices, including as mobile phones, sensors, and remote monitoring equipment, require Internet access, wireless networks have gained considerable traction in the healthcare sector. High-performance technologies, such as the forthcoming fifth generation/sixth generation (5G/6G), are needed for data transit to and from medical equipment in order to give patients with state-of-the-art medical treatments. Furthermore, much better optimization techniques must be used when creating its primary components. Intelligent system design affects how all medical equipment operates, which presents a challenging issue in medical applications. Using information from many sources, electronic health records are built and stored there. These data are compiled in several formats and techniques. There are various big data strategies that could be utilised to reconcile the conflicting data. Artificial intelligence, machine learning and deep learning methods can be used to forecast diseases or other problems using the knowledge gathered from big data analytics. With the advent of 5G, augmented reality, virtual reality and spatial computing are all enhanced, which has a profound effect on healthcare informatics by allowing for real-time remote monitoring. With the advent of 5G technologies, healthcare services can be provided over vast distances via a vast network of interconnected devices and high-performance computation. Disease detection and treatment using dynamic data can be accomplished with the help of deep learning techniques such as Deep Convolutional Neural Networks (DCNN). Deep convolutional neural networks that incorporate images of sick regions are frequently employed for classification tasks
Page(s):
99-109
DOI:
DOI not available
Published:
Journal: International Journal of Communication Networks and Information Security, Volume: 14, Issue: 3, Year: 2022