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Elsevier

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.

  • AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice

    • 1st Edition
    • Olfa Boubaker + 1 more
    • English
    AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice examines the transformative role of AI and data science in improving diagnosis, treatment, and healthcare delivery. It shows how machine learning, deep learning, and advanced signal and image analysis enable breakthroughs in genomics, multi-omics integration, biomedical imaging, EEG-based seizure prediction, and real-time physiological monitoring. The book highlights AI-driven stratification of complex syndromes such as sepsis, stroke, and acute respiratory distress syndrome, demonstrating how data-driven models support early detection, personalized interventions, and actionable clinical decisions.The volume also presents system-level innovations, including AI-based forecasting for dialysis, blood supply management, and telemedicine optimization. It addresses ethical and regulatory challenges, fairness, transparency, data governance, and clinical validation, providing a practical roadmap for healthcare professionals, engineers, researchers, and policymakers. By integrating responsible, human-centered AI into precision medicine, the book illustrates clear pathways to enhance patient care, improve outcomes, and promote equitable healthcare.

  • AI and Data Science in Medical Research

    • 1st Edition
    • Olfa Boubaker
    • English
    AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies.The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

  • Artificial Intelligence Applications in Emerging Healthcare Technologies

    • 1st Edition
    • Miguel Antonio Wister Ovando + 2 more
    • English
    Artificial Intelligence Applications in Emerging Healthcare Technologies presents the latest advances and state-of-the-art methods and applications of computer science and emerging AI technologies in health and medicine. The book explores the impact of artificial intelligence (AI) in healthcare for medical decision-making and data analysis, tackling topics such as cloud computing, cybersecurity, the internet of things, natural language processing, virtual health, data science applied to healthcare, personalized medicine, imaging, diagnosis, drug discovery, and diseases, among others.Chapters present adaptations or improvements on previous models and algorithms to process data from different sources. Other chapters investigate new formulations for the optimization of known procedures and algorithms. Finally, all chapters use experimental methods to study problems of interest in healthcare. This is a great resource for researchers and students who want to learn how machine learning algorithms and other data science techniques have been implemented to solve healthcare-related problems.

  • Digital Supply Chain Transformation

    Implementing Technology, Analytics, and Data-Driven Solutions
    • 1st Edition
    • Vinaytosh Mishra
    • English
    Digital Supply Chain Transformation: Implementing Technology, Analytics, and Data-Driven Solutions delves into the intricate world of supply chain management, emphasizing the role of digital transformation in modern supply chains. Through a blend of theoretical learning and practical applications, readers will gain a deep understanding of foundational supply chain principles while exploring emerging trends and technologies reshaping the industry. Topics such as system dynamics modelling, machine learning, artificial intelligence, and end-to-end visibility are explored in-depth, equipping readers with the tools and knowledge needed to excel in the rapidly evolving landscape of supply chain management. Readers will learn how comprehend core principles and elements of supply chain management and its pivotal role in businesses and industries, recognize the significance of digital transformation in supply chains, understand the tools, technologies, and strategies essential for a successful transformation, evaluate the importance of end-to-end supply chain visibility, employ methods and technologies to enhance this visibility in practical scenarios, and apply system dynamics modeling techniques to address complex supply chain problems to optimize supply chain processes, and much more.

  • Foundations of High-Performance Computing

    A Comprehensive Guide to Systems, Concepts, and Programming
    • 1st Edition
    • Oscar Diez
    • English
    Foundations of High Performance Computing: A Comprehensive Guide to Systems, Concepts, and Programming offers a comprehensive reference on high-performance computing (HPC). Laying the groundwork for the companion text, High-Performance Computing: Applications and Frontiers, this book serves as a comprehensive introduction to the fundamental concepts, systems, and introductory programming techniques. It focuses on infrastructure, programming basics, and practical access to HPC systems, covering the evolution of HPC and offering an architectural overview of HPC systems. In addition, it explores resource management and performance metrics in parallel systems, discussing practical access to HPC and considering the concepts behind distributed and shared memory. Other sections focuses on OpenMP for multithreading, MPI programming, GPU computing, OpenACC, and CUDA, and parallel I/O, data management, filesystems, cloud based HPC, and virtualization. The book concludes with a reference and glossary, equipping the reader with a thorough grounding in the basics of HPC and providing a comprehensive, multidisciplinary guide on the principles and concepts that underpin high performance computing. It is designed for graduate students, early-career professionals, and researchers seeking to build a solid foundation in HPC.

  • AI-Driven Human-Machine Interaction for Biomedical Engineering

    Concepts, Applications, and Methodologies
    • 1st Edition
    • Kapil Gupta + 4 more
    • English
    AI-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies offers a comprehensive examination of the intricate relationship between humans and machines, particularly through the transformative lens of artificial intelligence (AI). As AI technologies rapidly evolve, understanding their implications for human-machine interaction (HMI) has become essential across various domains, especially healthcare. Structured into well-defined chapters, the book begins with an introduction to AI-driven HMI, laying the groundwork for understanding its significance in sustainable healthcare and beyond. Subsequent chapters explore critical topics such as machine learning principles, advanced biomedical data classification methods, and the role of AI in telemedicine.Readers will delve into cutting-edge techniques, from deep learning to non-invasive computer vision, while also examining the implications of these technologies across industries. Each chapter equips readers with actionable insights and highlights emerging trends, ethical considerations, and the future of AI in HMI, ensuring a well-rounded perspective on this dynamic field. This is an invaluable resource for researchers, academics, and students in the fields of Biomedical Engineering, Computer Science, Data Science, Artificial Intelligence, and Healthcare Technology.

  • Cybersecurity for Healthcare Systems in the Internet of Medical Things Era

    • 1st Edition
    • Janmenjoy Nayak + 2 more
    • English
    Cybersecurity for Healthcare Systems in the Internet of Medical Things Era is driven by the imperative to address the intricate convergence of healthcare, technology, and security. In response to the burgeoning challenges presented by the Internet of Medical Things (IoMT), this book is designed to be an indispensable resource for computer systems experts, healthcare staff, and executives. It goes beyond the surface, offering strategic insights and actionable strategies that encompass not only the IoMT landscape but also the intersection of artificial intelligence, signal processing, and cyber security. Cybersecurity for Healthcare Systems in the IoMT Era serves as a problem-solving compass for a diverse readership in the healthcare landscape. For healthcare professionals and IT leaders, the book untangles the complexities of integrating and securing Internet of Medical Things (IoMT) devices, offering a roadmap for understanding and navigating this rapidly evolving terrain. Biomedical engineers, burdened with strategic and everyday decisions, find in this book strategic insights and actionable strategies, empowering them to make informed choices amidst the ever-changing challenges posed by technology and cybersecurity threats. The authors present a comprehensive guide that not only elucidates the challenges and opportunities presented by IoMT but also explores how the synergy of AI and signal processing can elevate healthcare systems. This integration is crucial in deciphering the intricate nuances of medical data, enhancing diagnostics, and fortifying the security of interconnected healthcare networks.

  • AI Platforms as Global Governance for the Health Ecosystem

    The Future's Global Hospital
    • 1st Edition
    • Dominique J. Monlezun
    • English
    AI Platforms as Global Governance for the Health Ecosystem: The Future’s Global Hospital provides comprehensive and actionable approaches for readers to understand and optimize responsible AI to create global governance for the healthcare ecosystem. The book explores how AI platforms can transform hospitals and clinical practice by digitally unifying patients, providers, and payors, advancing healthcare for all. Users will find content that defines and explains the main hurdles and technical innovations in responsibly governing AI platforms for efficient, equitable, and sustainable global healthcare.Additiona... sections delve into the history, science, politics, economics, ethics, policy, and future of these AI platforms, and how governance efforts can work toward the common good. Written from the first-hand perspective of a practicing physician-data scientist and AI ethicist, the book maps out how to develop successful governance for AI platforms.

  • Metaverse and AI in Healthcare

    A Federated Learning Approach
    • 1st Edition
    • Jyotir Moy Chatterjee + 1 more
    • English
    Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. The book fills a critical gap by exploring how federated learning enables secure, decentralized data sharing and personalized medicine in virtual health platforms, meeting urgent demands for privacy, interoperability, and innovation. The book is structured into four parts covering foundational AI and federated learning concepts, augmented reality and metaverse applications, legal and cybersecurity challenges, and emerging strategic trends.Contributors from academia and industry present chapters on predictive modeling, cybersecurity frameworks, AR fitness, legal perspectives, and AI-driven medical tourism which are supported by case studies and technical explanations. This reference equips graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare with practical knowledge and forward-looking analysis.

  • Deep Learning Assessment of Neurological Imaging

    • 1st Edition
    • Tripti Goel + 3 more
    • English
    Deep Learning Assessment of Neurological Imaging provides an introduction to deep learning structures and pre-processing methods for detecting MRI anomalies. The book also provides a comprehensive accounting of deep learning research on MRI images for Alzheimer's disease, Parkinson's disease, and schizophrenia, and includes a discussion on current research issues and future objectives. This book is a valuable resource to guide new entrants in the field, helping them make a meaningful impact in their development efforts. The book concludes with a brief overview of problems and potential future advancements in the field.

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