Guest Editors
Dr. Ashutosh Kumar Dubey, Chitkara University, India.
Dr. Vicente García-Díaz, University of Oviedo, Spain.
Dr. Abhishek Kumar, Chitkara University, India.
Summary
The advancement of machine learning and computational methods has become a driving force for global healthcare development and transformation. Machine learning allows a system to learn from the environment, through re-iterative processes. Along with the computational methods it also improves itself from experience. Recently, machine learning has gained massive attention across numerous fields, and is making it easy to model data extremely well, without the importance of using strong assumptions about the modeled system. The goal of this thematic issue is to explore how machine learning and Evolutionary Algorithms can help in the cancer detection and prediction. Specifically, innovative contributions that either solve or advance the understanding of issues related to new technologies and applications in the real world in the direction of cancer detection and prediction are very welcome.
Keywords
Potential topics include, but are not limited to the following:
• Computational methods for cancer prediction and detection
• Machine and deep learning approaches for cancer and health data
• Decision support systems for healthcare and wellbeing
• Optimization for cancer detection and prediction
• Medical expert systems
• Biomedical applications
• Applications of artificial intelligence for cancer detection and prediction
• Intelligent computing and platforms in healthcare
• Visualization and interactive interfaces related to healthcare systems.
Published Papers
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