Federated Learning for Digital Healthcare Systems

Herausgeber: Imoize, Agbotiname Lucky; Xhafa, Fatos; Song, Houbing Herbert; Obaidat, Mohammad S

• Broschiertes Buch

Produktbeschreibung

Federated Learning for Digital Healthcare Systems critically examines the key factors that contribute to the problem of applying machine learning in healthcare systems and investigates how federated learning can be employed to address the problem. The book discusses, examines, and compares the applications of federated learning solutions in emerging digital healthcare systems, providing a critical look in terms of the required resources, computational complexity, and system performance. In the first section, chapters examine how to address critical security and privacy concerns and how to revamp existing machine learning models. In subsequent chapters, the book's authors review recent advances to tackle emerging efficient and lightweight algorithms and protocols to reduce computational overheads and communication costs in wireless healthcare systems. Consideration is also given to government and economic regulations as well as legal considerations when federated learning is applied to digital healthcare systems.

Produktdetails

• Verlag: Elsevier Science
• Seitenzahl: 458
• Erscheinungstermin: 6. Juni 2024
• Englisch
• Gewicht: 450g
• ISBN-13: 9780443138973
• ISBN-10: 0443138974
• Artikelnr.: 69722640

Inhaltsangabe

1. Digital Healthcare Systems in a Federated Learning Perspective 2.
Architecture and design choices for federated learning in modern digital
healthcare systems 3. Curation of Federated Patient Data: A Proposed
Landscape for the Africa Health Data Space 4. Recent advances in federated
learning for digital healthcare systems 5. Performance evaluation of
federated learning algorithms using a breast cancer dataset 6. Taxonomy for
federated learning applied to digital healthcare systems 7. Modeling an
Internet of Health Things Using Federated Learning to Support Remote
Therapies for Children with Psychomotor Deficit 8. Blockchain-Based
Federated Learning in Internet of Health Things (IoHT) 9. Integration of
Federated Learning Paradigms into Electronic Health Record Systems 10.
Technical considerations of federated learning in digital healthcare
systems 11. Federated Learning Challenges and Risks in Modern Digital
Healthcare Systems 12. Case studies and recommendations for designing
federated learning models for digital healthcare systems 13. Government and
economic regulations on federated learning in emerging digital healthcare
systems 14. Legal implications of federated learning in emerging digital
healthcare systems 15. Secure Federated Learning in the Internet of Health
Things (IoHT) for Improved Patient Privacy and Data Security