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Books in Artificial intelligence general

  • AI-Driven Cybersecurity for Intelligent Healthcare Systems

    • 1st Edition
    • September 1, 2026
    • Balamurugan Balusamy + 3 more
    • English
    AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. The book offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. It presents case studies and real-world applications to illustrate the effectiveness of these solutions and highlights the significance of data privacy in healthcare and methods to ensure secure data sharing and storage. Topics such as federated learning, homomorphic encryption, and blockchain technology are covered to demonstrate how AI can enhance data security without compromising patient privacy. This book will be an essential resource for anyone involved in the healthcare industry, offering practical solutions and fostering a more in-depth understanding of how AI can revolutionize cybersecurity in healthcare.

  • Artificial Intelligence in Brain Disorders

    Innovations in Diagnosis and Treatment
    • 1st Edition
    • September 1, 2026
    • Pranav Kumar Prabhakar + 3 more
    • English
    Artificial Intelligence in Brain Disorders: Innovations in Diagnosis and Treatment focuses on the utilization of AI and machine learning to enhance current practices in the diagnosis and treatment of neurological disorders. Each chapter provides in-depth exploration of specific areas where AI can improve existing methodologies, offering practical guidance, case studies, and research findings that can be directly applied in the field. It explains the application of AI in diagnosing and treating major neurological illnesses and showcases the potential of AI in predicting diseases such as epilepsy and neurodegenerative disorders.As such, this book offers a detailed overview of AI and machine learning techniques relevant to neurological research.

  • Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

    • 1st Edition
    • September 1, 2026
    • Hanif Heidari + 1 more
    • English
    Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders discusses the latest developed methods in IoT and its applications in neurological disorders that emphasize end-user requirements. Intelligent IoT is used to explore the intersection between medicine, data science, biomedical engineering, and healthcare systems. A comprehensive overview of modelling and analyzing the requirements of people with neurological disorders is presented in this book. Signals and images of biological activity are collected and analyzed based on patient specifications to facilitate more accurate diagnosis and treatment. The book also discusses cutting-edge AI methods for IoT devices designed to treat neurological conditions.

  • Federated Learning for the Metaverse

    Applications in Virtual Environments
    • 1st Edition
    • August 1, 2026
    • Noor Zaman Jhanjhi + 3 more
    • English
    Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.

  • AI-Powered Developments in Medical Robotics

    Data-Driven Techniques for Enhanced Surgical Efficiency
    • 1st Edition
    • August 1, 2026
    • Thomas Heinrich Musiolik + 3 more
    • English
    AI-Powered Developments in Medical Robotics: Data-Driven Techniques for Enhanced Surgical Efficiency offers a comprehensive exploration of AI-driven innovations, robotics, and data-driven techniques specifically tailored for medical applications. This book strikes a balance by addressing foundational principles, emerging technologies, and their practical implementation in real-world scenarios. It enhances its value through the inclusion of real-world case studies and interdisciplinary perspectives, making it relevant for professionals, researchers, and students alike. The book explores future developments, such as augmented and virtual reality in medical robotics, positioning itself as a forward-thinking resource. By addressing current gaps in the field, including regulatory challenges, training needs, and cost-effectiveness, it ensures a well-rounded approach that appeals to both advanced and emerging markets. This multifaceted perspective enriches the reader's understanding and equips them with actionable insights for navigating the complexities of AI-driven healthcare robotics. The book serves as a definitive reference for a global audience seeking innovation and practical solutions in the rapidly evolving landscape of medical technology, bridging the gap between theory and practice in a critical area of healthcare advancement.

  • Encyclopedia of Multi-Attribute Decision Making (MADM)

    • 1st Edition
    • August 1, 2026
    • Gholamreza Haseli + 2 more
    • English
    Encyclopedia of Multi-Attribute Decision Making (MADM) is a comprehensive guide that presents all of the current methods in MADM in one volume. In recent years, numerous MADM methods have been introduced, each of them having been rapidly developed by numerous researchers using fuzzy sets and fuzzy numbers. This book presents all the existing methods in a simple way, including Sections on Weighting Methods, Extensions for the MADM Methods, Ranking Methods, and Outranking Methods. All methods chapters have a consistent structure, enabling easier learning of the methods. Each of the methods chapters presents two numerical examples for each method, one simple example with less than six criteria and six alternatives, and one complex example with six or more criteria and six or more alternatives. In addition, most of the methods chapters are written by the original developers of the method, ensuring insight into and practical application of MADM. The book is also filled with over 200 full-color figures illustrating the methods and their applications. Encyclopedia of Multi-Attribute Decision Making (MADM) demystifies the complex world of MADM, blending theoretical concepts with hands-on practices and case studies. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of MADM.

  • Symbiotic Planning for Urban Futures

    Empowering Collaborative Human-AI Planning
    • 1st Edition
    • August 1, 2026
    • Zhong-Ren Peng
    • English
    AI-Driven Urban Planning: Shaping the Future of Cities presents a comprehensive guide to the transformative potential of artificial intelligence in urban planning. This book equips readers with the knowledge to harness data, analytics, and AI for creating sustainable, equitable, and livable urban environments. Exploring diverse applications—from understanding human mobility patterns to enhancing disaster response strategies and optimizing design processes—the book offers practical projects and illustrates how AI is shaping contemporary urban landscapes. By addressing both theoretical and practical dimensions, this resource aims to empower students, professionals, and policymakers with a holistic understanding of Urban Planning AI.It is organized into five parts, each tackling crucial aspects of Urban Planning AI. It first introduces core concepts, types, mechanisms, and ethical considerations surrounding AI. Part II then discusses the history of computer applications in urban and regional planning. Part III focuses on AI Applications in Urban Planning, addressing critical domains such as transportation, environmental, housing, economic, participatory, and health and safety planning. Part IV tackles challenges and ethical considerations, emphasizing equity, transparency, and data-related issues. Lastly, Part V explores future pathways of urban planning AI, discussing current trends, future visions, and interdisciplinary approaches essential for effective governance and policymaking.

  • GeoAI for Earth Observation Imagery

    Fundamentals and Practical Applications
    • 1st Edition
    • July 1, 2026
    • Dalton Lunga + 1 more
    • English
    GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications comprehensively covers methodologies of AI and Machine Learning applications of image processing for Earth Observation (EO) Imagery. As traditional image processing methods face challenges with handling vast volumes of EO imagery, leading to efficiencies and limitations when extracting meaningful insights, AI-driven approaches can enhance the efficiency, accuracy, and scalability of image processing. Chapters cover essential methodologies including atmospheric compensation, image enhancement techniques like deblurring and superresolution, and advanced analysis methods such as semantic segmentation and object detection.Cutting-ed... approaches to computing, automating, and optimizing image processing tasks are also covered. Additionally, emerging trends in GeoAi and their implication on future research are reviewed. The book serves as an essential guide for navigating the complexities of spatial data and equips readers with knowledge to enhance their analytical capabilities.

  • Federated Learning

    Foundations and Applications
    • 1st Edition
    • June 1, 2026
    • Rajkumar Buyya + 2 more
    • English
    Federated Learning: Foundations and Applications provides a comprehensive guide to the foundations, architectures, systems, security, privacy, and applications of federated learning. Sections cover fundamental concepts, including machine learning, deep learning, centralized learning, and distributed learning processes. The book then progresses to coverage of the architectures, algorithms, and system models of Federated Learning, as well as security, privacy, and energy-efficiency techniques. Finally, the book presents various applications of Federated Learning through real-world case studies, illustrating both centralized and decentralized Federated Learning.Federated Learning has become an increasingly important machine learning technique because it introduces local data analysis within clients and requires exchange of only model parameters between clients and servers, hence the addition of this new release is ideal for those interested in the topics presented.

  • Intelligent Cyber-Physical Systems for Sustainable Healthcare

    • 1st Edition
    • June 1, 2026
    • Vandana Bajaj + 5 more
    • English
    Intelligent Cyber-Physical Systems for Sustainable Healthcare addresses the integration of emerging technologies like Virtual Reality, Smart Robotics, and Human-Computer Interaction, which are crucial for maximizing digital health's potential. The book includes case studies that highlight challenges faced by medical practitioners and industry professionals, providing valuable insights for designing sustainable iCPS solutions. Aimed at biomedical engineers, researchers, and industry professionals, it offers guidance for developing practical applications in sustainable healthcare. Additionally, shared, cross-disciplinary experiences assist engineers with less clinical expertise in enhancing healthcare applications in the intelligent digital health sector. Overall, case studies illustrate past challenges in the healthcare industry and present effective solutions to overcome them, making the book a comprehensive resource for advancing sustainable healthcare practices.