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CRC Press Federated Deep Learning for Healthcare: A Practical Guide with Challenges and Opportunities (Advances in Smart Healthcare Technologies)

Amazon

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£138.44 £101.66 £109.68 £117.71 £125.73 £133.76 £141.78 25 July 2026 08 August 2026 23 August 2026 07 September 2026 22 September 2026
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Price range: £105 - £138

Price levels: 5 different prices over 60 days

Description

This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information. Features: Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications. Investigates privacy-preserving methods with emphasis on data security and privacy. Discusses healthcare scaling and resource efficiency considerations. Examines methods for sharing information among various healthcare organizations while retaining model performance. This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
02 October 2024
Listed Since
03 April 2024

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