- Home
- Computers
- Computer Engineering
- Federated Deep Learning for Healthcare (A Practical Guide with Challenges and Opportunities)
Federated Deep Learning for Healthcare (A Practical Guide with Challenges and Opportunities)
List Price:
$73.99
- Availability: Confirm prior to ordering
- Branding: minimum 50 pieces (add’l costs below)
- Check Freight Rates (branded products only)
Branding Options (v), Availability & Lead Times
- 1-Color Imprint: $2.00 ea.
- Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
- Belly-Band Wrap: $2.50 ea. (full-color printed)
- Set-Up Charge: $45 per decoration
- Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
- Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
- Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
- RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
Product Details
Author:
Amandeep Kaur, Chetna Kaushal, Md. Mehedi Hassan, Si Thu Aung
Format:
Paperback
Pages:
266
Publisher:
CRC Press (July 19, 2026)
Imprint:
CRC Press
Language:
English
Audience:
College/higher education
ISBN-13:
9781032694863
Weight:
17.375oz
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_260911042558718-20260911.xml
Folder:
TAYLORFRANCIS
List Price:
$73.99
Country of Origin:
United States
Pub Discount:
30
Series:
Advances in Smart Healthcare Technologies
As low as:
$70.29
Publisher Identifier:
P-CRC
Discount Code:
H
Overview
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising of domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas.
