Edited book to be published in Springer series "Computational Intelligence Methods and Applications"

Series Editor: Patrick Siarry (siarry@u-pec.fr)

Book Editors: Salim El khediri, Mansour Eddaly, Tarek Moulahi and Salah Zidi
Description


Exploring the Nexus of Blockchain, Federated Learning, and IoMT in Healthcare: Unveiling Convergence and Future Trajectories” delves into the intersection of three cutting-edge technologies – blockchain, federated learning, and the Internet of Medical Things (IoMT) – and their transformative potential within the healthcare sector. This comprehensive volume serves as a roadmap for navigating the intricate landscape of these technologies, offering insights into their applications, challenges, and opportunities within healthcare. The book’s primary aim is to provide a thorough exploration of how blockchain, federated learning, and IoMT are reshaping healthcare delivery, data management, and diagnostic processes. Each chapter delves deeply into a specific aspect of these technologies, from their underlying principles to their practical implementations and implications. By offering a comprehensive review of each technology’s role in healthcare, the book equips healthcare professionals, researchers, policymakers, and technology enthusiasts with the knowledge needed to navigate the rapidly evolving healthcare landscape. The chapters are meticulously crafted to provide a blend of theoretical foundations, practical insights, and real-world case studies, ensuring that readers gain both a deep understanding of the subject matter and actionable insights for implementation. Moreover, the book adopts a forward-thinking approach, exploring not only current applications but also future trajectories and emerging trends in the field. With its interdisciplinary approach and forward-looking perspective,” Exploring the Nexus of Blockchain, Federated Learning, and IoMT in Healthcare” stands as an indispensable resource for anyone seeking to understand the convergence of these transformative technologies and their implications for the future of healthcare delivery and management.
Potential topics are (but are not limited to):
* Federated Learning for Healthcare
* Internet of Medical Things (IoMT) Networks for Healthcare
* Internet of Things architecture for healthcare
* E-Health Data collection using the Internet of Medical Things
* Privacy preservation issues in e-Health
* Blockchain paradigm for e-Health
* Platforms and architectures for Blockchain and IoMT
* Machine learning and Deep learning for healthcare diagnostic
* Explainable Artificial Intelligence (XAI) for healthcare diagnostic
* Testbeds and validation of IoMT solutions
* Future of privacy preserved IoMT data analytics

Information for authors
Authors may submit new contributions of around 20 pages. All chapters suitable for publication in this book will be blindly reviewed.


Contact Information
To submit your proposal and for more detailed information, please contact: Salim El Khediri, Associate professor in College of Computer, Qassim University, KSA (s.elkhediri@qu.edu.sa)