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Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

  • Artificial Intelligence and Machine Learning for Safety-Critical Systems

    A Comprehensive Guide
    • 1st Edition
    • September 1, 2026
    • Rajiv Pandey + 3 more
    • English
    Artificial Intelligence and Machine Learning for Safety-Critical Systems: A Comprehensive Guide provides engineers and system designers who are exploring the application of AI/ML methods for safety-critical systems with a dedicated resource on the challenges and mitigation strategies involved in their design. The book's authors present ML techniques in safety-critical systems across multiple domains, including pattern recognition, image processing, edge computing, Internet of Things (IoT), encryption, hardware accelerators, and many others. These applications help readers understand the many challenges that need to be addressed in order to increase the deployment of ML models in critical systems. In addition, the book shows how to improve public trust in ML systems by providing explainable model outputs rather than treating the system as a black box for which the outputs are difficult to explain. Finally, the authors demonstrate how to meet legal certification and regulatory requirements for the appropriate ML models. In essence, the goal of this book is to help ensure that AI-based critical systems better utilize resources, avoid failures, and increase system safety and public safety.

  • 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.

  • 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.

  • Deep Learning Approaches for Healthcare Data Analysis and Decision Making

    • 1st Edition
    • September 1, 2026
    • Ashish Bagwari + 5 more
    • English
    Deep Learning Approaches for Healthcare Data Analysis and Decision Making demystifies complex data-driven technologies, providing a clear framework for integrating advanced analytics into healthcare practices. With a focus on practical applications, the authors present a comprehensive digital transformation methodology that empowers readers to tackle the multifaceted challenges of healthcare data management. By leveraging deep learning techniques, readers will learn to analyze vast datasets, identify critical patterns, and develop predictive models that enhance diagnosis and treatment strategies while ensuring compliance with stringent data regulations. The book also addresses the pressing need for ethical AI practices, emphasizing patient privacy and data security. Real-world case studies illustrate how to implement personalized healthcare solutions and foster interdisciplinary collaboration, breaking down silos in knowledge and practice. Moreover, it explores innovative business models for sustainable AI integration, offering actionable insights for healthcare providers. This resource equips professionals with the tools to drive innovation, improve patient outcomes, and navigate the complexities of digital transformation in healthcare, making it a must-read for anyone at the intersection of technology and healthcare.

  • Smart Healthcare 2.0

    Integrating Digital Twins with AI-Driven Predictive Analytics
    • 1st Edition
    • September 1, 2026
    • Ramesh Chandra Poonia + 1 more
    • English
    Smart Healthcare 2.0: Integrating Digital Twins with AI-Driven Predictive Analytics offers a ground-breaking exploration of how digital twin technology, combined with real-time sensing and predictive analytics, is transforming healthcare delivery. As the global healthcare landscape shifts toward proactive, personalized care, this book addresses the urgent need for comprehensive resources that unify artificial intelligence, Internet of Things (IoT), and biomedical engineering within the digital twin framework. It provides an essential guide for researchers, engineers, and clinicians aiming to harness virtual patient models and data-driven insights to improve health outcomes and system efficiency in the era of ubiquitous healthcare.This volume covers a wide spectrum of topics, starting with foundational concepts of digital twins in precision health and advancing through smart sensing technologies, scalable system architectures, and AI-powered predictive analytics. Readers will explore detailed discussions on edge-cloud computing, secure communication protocols including blockchain, and simulation platforms that enable virtual patient modeling. The book also addresses critical themes such as chronic disease management, emergency response optimization, ethical AI deployment, interoperability standards, and workforce readiness. Real-world case studies and future-focused chapters on cognitive twins and quantum simulation provide a rich, multidisciplinary perspective. Each chapter is complemented by pedagogical tools and supported by a companion website offering extended resources for teaching and applied research. Researchers and academics will find a consolidated, interdisciplinary framework linking theory with practical healthcare applications, ideal for advancing scholarship and innovation.Biomedica... and clinical engineers gain actionable insights into system design, sensor integration, and clinical validation for building reliable, patient-centered solutions. Healthcare AI engineers and data scientists will benefit from specialized guidance on deploying predictive models, managing multi-sensor data fusion, and ensuring privacy-compliant, real-time analytics. This book empowers stakeholders across the healthcare ecosystem to drive the next generation of intelligent, adaptive, and trustworthy digital health systems.

  • Clinical Cancer Genomic Medicine

    • 1st Edition
    • August 1, 2026
    • Eamonn Maher + 3 more
    • English
    Clinical Cancer Genomic Medicine covers all major aspects of genetics and genomics in cancer development, diagnosis, and management, and their use in the clinical setting. The book explores not only the genetic basis of cancer, but also the role genomics plays in understanding the molecular basis of disease and how it can aid in diagnosis and treatment. Sections discuss the basics of oncogenomic and emerging technologies and specific cancer types, such as breast, gastrointestinal, ocular, skin, and pediatric. The book also includes knowledge on diagnostic cancer genomic techniques, surgical approaches, and ethical, legal, and social implications.This is a valuable resource for oncologists, clinicians, researchers, healthcare workers, and members of the biomedical field who need to understand more about the benefits of genetics and genomics for cancer and their applications in the clinical setting.

  • Quantum Communication and Cryptography

    • 1st Edition
    • August 1, 2026
    • Walter O. Krawec
    • English
    Quantum Communication and Cryptography introduces readers to the theory of quantum cryptography, with a focus will on quantum key distribution (QKD) and more advanced quantum cryptographic protocols beyond QKD. It contains a brief introduction to the field of modern cryptography that is needed to fully appreciate and understand how quantum cryptographic systems are proven secure, and how they can be safely used in combination with current day classical systems. Readers are then introduced to quantum key distribution (QKD) - perhaps the most celebrated, and currently the most practical, of quantum cryptographic techniques.Basic protocols are described, and security proofs are given, providing readers with the knowledge needed to understand how QKD protocols are proven secure using modern, state- of-the-art definitions of security. Following this, more advanced QKD protocols are discussed, along with alternative quantum and classical methods to improve QKD performance. Finally, alternative quantum cryptographic protocols are covered, along with a discussion on some of the practical considerations of quantum secure communication technology. Throughout, protocols are described in a clear and consistent manner that still provides comprehensive, theoretical proofs and methods.

  • 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.

  • Advanced Computational and Mathematical Approaches in Applied Differential Equations

    • 1st Edition
    • August 1, 2026
    • Snehashish Chakraverty + 2 more
    • English
    Advanced Computational and Mathematical Approaches in Applied Differential Equations explores cutting-edge techniques and methodologies in solving complex differential equations, a cornerstone of mathematical modeling across science and engineering. The book bridges theory and application, offering advanced computational strategies and innovative mathematical insights to address real-world problems. Beginning with an overview that presents a unified framework that defines the types of differential equations covered (e.g. ordinary, partial, fractional, fuzzy), the book then progresses to foundations and methods such as Lie symmetries, homotropy, Adomian, FEM, FDM, spectral, machine learning, fuzzy, and fractional derivatives, addressing both computational and mathematical dimensions.Different... equations are fundamental to modeling complex systems, yet solving them often involves significant challenges due to their complexity and nonlinearity. The book equips readers with advanced tools and methodologies to overcome these challenges, providing innovative solutions that improve accuracy, efficiency, and applicability in real-world scenarios. Ideal for researchers, practitioners, and advanced students, it provides a comprehensive resource for tackling challenging applied differential equations with better precision and efficiency.

  • Artificial Intelligence, Machine Learning and Blockchain in Digital Twin Computing

    • 1st Edition
    • August 1, 2026
    • Parikshit Narendra Mahalle + 1 more
    • English
    Artificial Intelligence, Machine Learning and Blockchain in Digital Twin Computing explores the synergy between artificial intelligence, machine learning, blockchain technology, and digital twin computing. The book overviews each technology, establishing a clear understanding of their individual roles and potential when combined. The second section delves into the integration of these technologies, focusing on key themes such as enhancing system simulations, ensuring data integrity, and enabling secure, real-time decision-making. Practical applications and case studies are used to illustrate how this convergence can drive innovation in industries like manufacturing, healthcare, and smart cities. Final sections look ahead, discussing emerging trends, challenges, and future opportunities.Digita... twin computing is the bridge between the real and virtual worlds. Digital twin computing also is the mirror that reflects the real world into the virtual world. Blockchain technology can refine the digital twins (DTs) by ensuring transparency, decentralized data storage, data immutability, and peer-to-peer communication in various applications. DT provides a powerful tool able to generate a huge amount of training data for machine learning algorithms (MLAs).

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