Paperback. With contributions from leading researchers and industry experts, this book examines cutting-edge applications, integration models, and sustainable solutions across sectors including finance, agriculture, healthcare, IoT, and smart cities. Chapters cover blockchain-enabled fintech operations, fraud detection, deep learning-driven intrusion detection, AI-enhanced smart contracts, and data-driven healthcare innovations. Case studies, methodologies, and future-oriented insights demonstrate how these technologies can foster secure, efficient, and sustainable ecosystems. By bridging theoretical foundations with practical implementations, this book offers readers a roadmap to navigate the opportunities and challenges shaping the next generation of intelligent, blockchain-powered systems. Key Features: -Integrates blockchain with machine learning for real-world applications. -Applies advanced analytics, automation, and AI models to enhance blockchain ecosystems. -Develops secure solutions in fintech, agriculture, healthcare, IoT, and smart cities. -Evaluates case studies and frameworks addressing challenges and vulnerabilities. -Explores sustainable, future-ready trends shaping intelligent systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Bibliographic Details

Title: Machine Learning and Blockchain - Challenges, Future Trends and Sustainable Technologies (Paperback)
Publisher: Bentham Science Publishers Singapore Pte. Ltd.
Publication Date: 2026
Language: English
ISBN 10: 9815324233
ISBN 13: 9789815324235
Binding: Paperback
Condition: new

About this title

Synopsis

With contributions from leading researchers and industry experts, this book examines cutting-edge applications, integration models, and sustainable solutions across sectors including finance, agriculture, healthcare, IoT, and smart cities. Chapters cover blockchain-enabled fintech operations, fraud detection, deep learning–driven intrusion detection, AI-enhanced smart contracts, and data-driven healthcare innovations. Case studies, methodologies, and future-oriented insights demonstrate how these technologies can foster secure, efficient, and sustainable ecosystems. By bridging theoretical foundations with practical implementations, this book offers readers a roadmap to navigate the opportunities and challenges shaping the next generation of intelligent, blockchain-powered systems.

Key Features:

-Integrates blockchain with machine learning for real-world applications.
-Applies advanced analytics, automation, and AI models to enhance blockchain ecosystems.
-Develops secure solutions in fintech, agriculture, healthcare, IoT, and smart cities.
-Evaluates case studies and frameworks addressing challenges and vulnerabilities.
-Explores sustainable, future-ready trends shaping intelligent systems.

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