Federated Learning for Digital Healthcare Systems

Agbotiname Lucky Imoize is currently a Marie Skłodowska‑Curie Fellow affiliated with the Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT) and Politecnico di Torino, Italy. Dr. Imoize has held international research appointments, including as a research scholar at Ruhr University Bochum, Germany, supported by the Nigerian Petroleum Technology Development Fund (PTDF) and the German Academic Exchange Service (DAAD), and as a Fulbright Visiting Researcher at the Wireless@VT Laboratory in the Bradley Department of Electrical and Computer Engineering, Virginia Tech, USA. His industry experience includes roles at ZTE and Globacom. He is Vice Chair of the IEEE Communications Society Nigeria Chapter and a registered engineer with the Council for the Regulation of Engineering in Nigeria. His research interests include AI, IoT, deep learning, and wireless communications for sustainable development applications. Mohammad S. Obaidat (Fellow IEEE, Fellow SCS, Fellow AAIA, and Fellow of FTRA) is a Full Professor in the Department of Computer Science at King Abdullah II School of Information Technology (KASIT), University of Jordan, Amman, Jordan. He is also a Distinguished Professor at SRM University, India. He has published around 1,200 technical articles, 100 books, and 70 book chapters. He is Editor-in-Chief of three scholarly journals and an editor of numerous international journals. He is the founding Editor-in-Chief of Wiley Security and Privacy Journal. Moreover, he is the founder or co-founder of five International Conferences. His areas of interest are in wireless networks, cyber security, security of e-Systems, computer networks, data analytics, and computer architecture, parallel computing: Architecture, and Algorithms, and performance evaluation of computer networks and systems. Houbing Song, Security and Optimization for Networked Globe Laboratory, University of Maryland, Baltimore County (UMBC), Baltimore, USA. His research interests include cyber-physical systems, cybersecurity and privacy, IoT, big data analytics, connected vehicles, smart health, wireless communications, and networking. Dr. Song has edited and authored several books in the field, including Cyber-Physical Systems: Foundations, Principles and Applications. Fatos Xhafa, PhD in Computer Science, is Full Professor at the Technical University of Catalonia (UPC), Barcelona, Spain. He has held various tenured and visiting professorship positions. He was a Visiting Professor at the University of Surrey, UK (2019/2020), Visiting Professor at the Birkbeck College, University of London, UK (2009/2010) and a Research Associate at Drexel University, Philadelphia, USA (2004/2005). He was a Distinguished Guest Professor at Hubei University of Technology, China, for the duration of three years (2016-2019). Prof. Xhafa has widely published in peer reviewed international journals, conferences/workshops, book chapters, edited books and proceedings in the field (H-index 55). He has been awarded teaching and research merits by the Spanish Ministry of Science and Education, by IEEE conferences and best paper awards. Prof. Xhafa has an extensive editorial service. He is founder and Editor-In-Chief of Internet of Things - Journal - Elsevier (Scopus and Clarivate WoS Science Citation Index) and of International Journal of Grid and Utility Computing, (Emerging Sources Citation Index), and AE/EB Member of several indexed Int'l Journals. Prof. Xhafa is a member of IEEE Communications Society, IEEE Systems, Man & Cybernetics Society and Founder Member of Emerging Technical Subcommittee of Internet of Things.His research interests include IoT and Cloud-to-thing continuum computing, massive data processing and collective intelligence, optimization, security and trustworthy computing and machine learning, among others. He can be reached at fatos@cs.upc.edu. Please visit also http://www.cs.upc.edu/~fatos/ and at http://dblp.uni-trier.de/pers/hd/x/Xhafa:Fatos

• 1. Digital Healthcare Systems in a Federated Learning Perspective2. Architecture and design choices for federated learning in modern digital healthcare systems3. Curation of Federated Patient Data: A Proposed Landscape for the Africa Health Data Space4. Recent advances in federated learning for digital healthcare systems5. Performance evaluation of federated learning algorithms using a breast cancer dataset6. Taxonomy for federated learning applied to digital healthcare systems7. Modeling an Internet of Health Things Using Federated Learning to Support Remote Therapies for Children with Psychomotor Deficit8. Blockchain-Based Federated Learning in Internet of Health Things (IoHT)9. Integration of Federated Learning Paradigms into Electronic Health Record Systems10. Technical considerations of federated learning in digital healthcare systems11. Federated Learning Challenges and Risks in Modern Digital Healthcare Systems12. Case studies and recommendations for designing federated learning models for digital healthcare systems13. Government and economic regulations on federated learning in emerging digital healthcare systems14. Legal implications of federated learning in emerging digital healthcare systems15. Secure Federated Learning in the Internet of Health Things (IoHT) for Improved Patient Privacy and Data Security