Advancing Smart Health and Biomedical Research with Artificial Intelligence Algorithms

Dear Colleagues,

The medical field is experiencing notable progress by integrating advanced technologies designed to provide optimal solutions for supporting medical professionals in smart health and biomedical research. As an example, radiology has observed the most applications of patented and FDA-approved artificial intelligence (AI)-based devices. This Special Issue encourages researchers to extend the potential of AI to diverse medical disciplines. Whether for medical diagnosis or drug development, the recent advances in technologies such as artificial intelligence (AI), machine learning (ML), deep learning (DL), and data sciences can advance research across the spectrum of smart health and biomedical research. This Special Issue aims to inspire researchers to explore the development of new AI algorithms or enhance existing AI-based algorithms in smart health and biomedical research. The research articles contributed to this issue are anticipated to lay the groundwork for developing patented devices with promising applications in the medical field.

Recent breakthroughs in machine learning (ML), artificial intelligence (AI), deep learning, and high performance coupled with the availability of new datasets have made advancements in smart health and biomedical research possible. Documented in the Summary of the Big Data and High-End Computing Interagency Working Groups Joint Workshop on the Convergence of High-Performance Computing, Big Data, and Machine Learning, these developments pave the way for unprecedented progress in medical research. Development or enhancement of algorithms concurrently address various aspects of human biology, physiology, and behavior, thereby enabling the creation of personalized, predictive models.

Dr. Jaafar Alghazo
Dr. Ghazanfar Latif
Dr. Elena Tanfani
Guest Editors

Manuscript Submission Information

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• AI algorithms in healthcare
• AI algorithms in biomedical research
• medical diagnostics
• smart healthcare
• ML and big data
• sensor technologies
• privacy in healthcare
• AI-enabled medical imaging