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Federated Learning and Privacy-Preserving in Healthcare AI (Advances in Healthcare Information Systems and Administration)

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£282.00 £267.90 £273.54 £279.18 £284.82 £290.46 £296.10 08 August 2026 22 August 2026 05 September 2026 19 September 2026 03 October 2026
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Description

The use of artificial intelligence (AI) in data-driven medicine has revolutionized healthcare, presenting practitioners with unprecedented tools for diagnosis and personalized therapy. However, this progress comes with a critical concern: the security and privacy of sensitive patient data. As healthcare increasingly leans on AI, the need for robust solutions to safeguard patient information has become more pressing than ever. Federated Learning and Privacy-Preserving in Healthcare AI emerges as the definitive solution to balancing medical progress with patient data security. This carefully curated volume not only outlines the challenges of federated learning but also provides a roadmap for implementing privacy-preserving AI systems in healthcare. By decentralizing the training of AI models, federated learning mitigates the risks associated with centralizing patient data, ensuring that critical information never leaves its original location. Aimed at healthcare professionals, AI experts, policymakers, and academics, this book not only delves into the technical aspects of federated learning but also fosters a collaborative approach to address the multifaceted challenges at the intersection of healthcare and AI.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
02 May 2024
Listed Since
03 May 2024

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