Federated Learning Techniques and Its Application in the Healthcare Industry - Couverture rigide

Couverture rigide

ISBN 10 : 9811287937 ISBN 13 : 9789811287930

Editeur : World Scientific Publishing Co Pte Ltd, 2024

Synopsis

Federated Learning is currently an emerging technology in the field of machine learning. Federated Learning is a structure which trains a centralized model for a given assignment, where the data is de-centralized across different edge devices or servers. This enables preservation of the confidentiality of data on various edge devices, as only the updated outcomes of the models are shared with the centralized model. This means the data can remain on each edge device, while we can still train a model using that data.Federated Learning has greatly increased the potential to transmute data in the healthcare industry, enabling healthcare professionals to improve treatment of patients.This book comprises chapters on applying Federated models in the field of healthcare industry.Federated Learning mainly concentrates on securing the privacy of data by training local data in a shared global model without putting the training data in a centralized location. The importance of federated learning lies in its innumerable uses in health care that ranges from maintaining the privacy of raw data of the patients, discover clinically alike patients, forecasting hospitalization due to cardiac events impermanence and probable solutions to the same. The goal of this edited book is to provide a reference guide to the theme.

Détails de l'édition

• Éditeur: World Scientific Publishing Co Pte Ltd
• Date d'édition: 2024
• Langue: anglais
• ISBN 10: 9811287937
• ISBN 13: 9789811287930
• Reliure: Relié
• Nombre de pages: 240
• Éditeur: Gururaj H L, Kayarga Tanuja, Flammini Francesco, Dobrilovic Dalibor
• Coordonnées du fabricant: non disponible
• Personne responsable: gpsr@libri.de; gpsr@libri.de; ; Friedensallee 273; Hamburg; 22763; Allemagne