Synopsis
The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems.
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Blockchain-Enabled Federated Learning for Privacy and Security
Published by
LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security
Published by
LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
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PAP
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Blockchain-Enabled Federated Learning for Privacy and Security
Published by
LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security (Paperback)
Published by
LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
New
Paperback
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security
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Omniscriptum, LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book 'Blockchain-Enabled Federated Learning for Privacy and Security' explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. 72 pp. Englisch. Seller Inventory # 9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security
Published by
LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security
Published by
LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security (Paperback)
Published by
LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
New
Paperback
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security (Paperback)
Published by
LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
New
Paperback
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786209074318
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Blockchain-Enabled Federated Learning for Privacy and Security
Published by
LAP Lambert Academic Publishing, 2025
ISBN 10: 6209074316
ISBN 13: 9786209074318
New
Softcover
Seller: Biblios, Frankfurt am main, HESSE, Germany
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