Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Federated Learning for Digital Healthcare Systems

Federated Learning for Digital Healthcare Systems

Obaidat, Mohammad S.
Imoize, Agbotiname Lucky
Song, Houbing Herbert

Paperback

Series: Intelligent Data-Centric Systems

General ComputersGeneral MathematicsProgramming

ISBN10: 0443138974
ISBN13: 9780443138973
Publisher: Academic Press
Published: Jun 6 2024
Pages: 458
Weight: 1.72
Height: 0.93 Width: 7.50 Depth: 9.25
Language: English

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.

Also in

General Computers

View All