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Intelligent Ubiquitous Computing and Advanced Learning Systems for Biomedical Engineering
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  • Chinmay Chakraborty,
  • Mohammad Khosravi (GE),
  • Lalit Garg,
  • M Shamim Kaiser,
  • Xingwang Li (GE),
  • Houbing Song
Chinmay Chakraborty
Birla Institute of Technology

Corresponding Author:[email protected]

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Mohammad Khosravi (GE)
Persian Gulf University
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Lalit Garg
University of Malta
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M Shamim Kaiser
Institute of Information Technology, Jahangirnagar University
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Xingwang Li (GE)
Henan Polytechnic University
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Houbing Song
Embry-Riddle Aeronautical University
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The health monitoring for disease diagnosis and prognosis in a desired smart medical structure is realized by interpreting the health data. The advances in sensor technologies and biomedical data acquisition tools have led to the new era of big data, where different sensors collect massive medical data every day. This special issue explores the latest development in emerging technologies of biomedical engineering, including big medical data, artificial intelligence, cloud/fog computing, federated learning, ubiquitous computing and communication, internet of things, wireless technologies, and, security and privacy. The biological wearable sensors can enhance the decision-making and early disease diagnosis processes by intelligently investigating and collecting large amounts of biomedical data (i.e., big health data). Hence, there is a need for scalable advanced learning, and intelligent algorithms that lead to reliable and interoperable solutions to make effective decisions in emergency medicine technologies. The optimization algorithms can be used in order to acquire the sensor data from multiple sources for fast and accurate health monitoring.
30 Sep 2022Submitted to The Journal of Engineering
02 Oct 2022Assigned to Editor
02 Oct 2022Submission Checks Completed
05 Oct 2022Editorial Decision: Accept