Special Issue "Recent Trends in Machine Intelligence respected to Medical Field Applications"

Submission Deadline: 13 March 2021 (closed)
Guest Editors
Dr. Paulchamy Balaiyah, Hindusthan Institute of Technology, India.
Dr. Arun Kumar Sivaraman, Vellore Institute of Technology (VIT), India.
Prof. Vijayakumar Varadarajan, The University of New South Wales, Australia.
Dr. Muralidhar Appalaraju, Vellore Institute of Technology (VIT), India.


Artificial Intelligence plays the major role in the field of medical image processing which brings the enormous changes in the present technology. Advanced monitoring systems based on Machine learning approach and innovative technologies are rapidly evolving and their use in healthcare, activity monitoring, and performance assessment is promising. Virtual technology and Artificial Intelligence systems development have been fostered by a combination of advances in materials, Classification techniques, electronic and communication engineering, Internet of Things technologies, wireless Sensor networks. Such Machine learning approaches brings various changes in disparate scenarios and at different scopes.

• Innovative machine learning algorithm in medical imaging system
• Techniques in sensing systems, techniques and methods in Internet of Things
• Metrological characterization of Virtual devices and monitoring systems in Artificial Intelligence
• prototypes and applications in medicine and Real Time applications
• Signal processing and Machine learning with Data fusion techniques
• Study of Gene expression with innovative outcome in machine learning approaches
• Innovative applications and case studies

Published Papers
  • Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs
  • Abstract Graph colouring is the system of assigning a colour to each vertex of a graph. It is done in such a way that adjacent vertices do not have equal colour. It is fundamental in graph theory. It is often used to solve real-world problems like traffic light signalling, map colouring, scheduling, etc. Nowadays, social networks are prevalent systems in our life. Here, the users are considered as vertices, and their connections/interactions are taken as edges. Some users follow other popular users’ profiles in these networks, and some don’t, but those non-followers are connected directly to the popular profiles. That means,… More
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