Guest Editors
Dr. Fahad Ahmad, University of Portsmouth, United Kingdom
Dr. Kashaf Junaid, Queen Mary University of London, United Kingdom
Summary
This special issue is dedicated to showcasing cutting-edge advancements in cancer research through the collaborative use of Omics data analysis and the application of intelligent technologies. It focuses on the synergy between RNA expression profiles and machine learning methodologies to accurately classify various cancer types. As precision medicine gains prominence, the fusion of Omics data, sophisticated medical imaging techniques, and artificial intelligence (AI) heralds a new era in the early diagnosis, comprehensive understanding, and effective treatment of cancer.
We seek submissions that delve into the innovative application of deep learning, explainable AI, and data science to Omics data (including genomics, proteomics, and metabolomics) and medical imaging modalities (such as radiology, X-ray, MRI, CT scans, and molecular imaging) aimed at enhancing cancer diagnosis and therapy. Contributions should emphasize the development and implementation of AI algorithms to decipher complex biological datasets, refine medical imaging accuracy for tumor identification, and shed light on cancer biology.
Moreover, this issue will address the role of the Medical Internet of Things (IoT) and emerging health technologies in cancer care, highlighting how these advancements contribute to early cancer detection, continuous monitoring, improved patient management, and optimized therapeutic strategies. We welcome a broad spectrum of research topics, including but not limited to, the integration of AI and medical imaging, the exploration of Omics for cancer research, and the application of IoT in enhancing cancer treatment efficacy.
Submissions are encouraged from researchers and practitioners who are working at the intersection of biology, medicine, technology, and data science to advance cancer diagnostics and therapeutics. Through this special issue, we aim to showcase cutting-edge research that contributes to the personalized medicine landscape, offering hope and new solutions for patients affected by cancer.
Keywords
• Artificial Intelligence/Machine Learning/Deep Learning
• Explainable Artificial Intelligence/Data Science
• Image Processing
• Medical Internet of Things (MIoT)
• Health and Wellbeing Technologies
• Omics (Genomics, Proteomics, Metabolomics)
• Medical Imaging/Radiology/X-Ray/MRI/CT Scans/Molecular Imaging
• Cancer Expansion Behaviour and Diagnostics
• Patient Monitoring Systems
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