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Elsevier

Libros en Inteligencia Artificial

  • Principles of Medical Biohybrid Microrobots

    • 1 Edición
    • Veronika Magdanz + 1 más
    • Inglés

  • Healthcare 5.0

    Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data
    • 1 Edición
    • Yugal Kumar + 2 más
    • Inglés
    Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data addresses the urgent need for innovation in today’s complex healthcare data landscape, characterized by pandemics, aging populations, and escalating chronic conditions. This book introduces the concept of ‘Healthcare 5.0’ as an interconnected, data-driven, and patient-centric framework, where advanced technologies—such as AI, ML, IoMT, Big Data, and Large Language Models (LLMs)—converge to optimize care, streamline operations, and deliver personalized, predictive solutions that meet real-world challenges. Comprising six comprehensive sections, the book moves from core AI applications in electronic health records, drug discovery, data management, and privacy, through cutting-edge big data analytics for precise disease forecasting and diagnosis. It explores new research advances in the Internet of Medical Things including connected device architectures and their fusion with AI for dynamic decision-making. The third section focuses on data analytics in telemedicine, remote care, system usability, and integration in Healthcare 5.0. The personalized healthcare section details analysis and applications in AI- and IoT-powered assistance, and real-time monitoring. The last section explores the development of LLMs and their applications in medical imaging, clinical decision support, predictive analytics, system architectures, as well as the ethical challenges of their deployment in healthcare. Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data serves as an essential resource for graduate students, researchers, and engineers in computer science, data science, and biomedical informatics. It bridges theory and practical application, offering interdisciplinary insights, foundational background, detailed case studies, and guidance on navigating the next generation of healthcare data systems. Whether for research or real-world innovation, readers gain the tools to design, analyze, and implement intelligent healthcare data solutions for a rapidly evolving digital era.

  • The Deterministic Universe

    Exploring Chaos, Free Will, Prediction, and Modeling
    • 1 Edición
    • Paul A. Gagniuc
    • Inglés
    The Deterministic Universe: Exploring Chaos, Free Will, Prediction, and Modeling equips readers with the tools to learn the foundational concepts of chaos, randomness, and determinism through examples and applied case studies. The book helps readers gain insight into how deterministic algorithms handle complex, chaotic data, providing an interdisciplinary exploration of chaos theory, determinism, and free will, grounded in scientific principles, computational models, and philosophical insights. The content builds on established theories in physics, bioinformatics, and systems biology, weaving them into broader existential questions. The material emphasizes the interplay between randomness, noise, and order, providing a fresh lens to view the universe and our place within it. The book connects these ideas to practical tools like random number generators and nonlinear equations, machine learning algorithms, computational and predictive models, extending their implications to biological systems, human thought, and decision-making. By addressing both scientific fundamentals and philosophical debates, the book bridges abstract ideas with real-world phenomena and demonstrates the role of randomness and noise in predictive models and simulations, helping readers understand the limits of computational systems in mimicking real-world processes.

  • Integrating AI in Psychological and Mental Health Care

    Techniques, Applications, and Ethical Considerations
    • 1 Edición
    • Sandeep Kautish + 4 más
    • Inglés
    Integrating AI in Psychological and Mental Health Care: Techniques, Applications, and Ethical Considerations introduces key concepts and the historical evolution of AI, providing a foundation for understanding its applications in mental health. The content delves into various aspects of AI, including diagnostic tools, machine learning algorithms, and natural language processing, highlighting their roles in enhancing therapeutic outcomes and improving patient care. The discussion encompasses significant mental health conditions such as anxiety, depression, and severe psychological disorders, showcasing how AI technologies can assist in diagnosis, treatment planning, and monitoring. Ethical considerations and privacy issues are critically examined, ensuring a balanced perspective on the benefits and challenges associated with AI-driven interventions. Practical applications, such as virtual psychotherapists and AI-enhanced cognitive behavioral therapy illustrate real-world implementations and their impact on patient care. Additionally, case studies provide insights into successful AI applications in mental health settings, thus enhancing our understanding of potential advantages and obstacles.

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

    • 1 Edición
    • Hanif Heidari + 1 más
    • Inglés
    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.

  • Robotics for Intervention in Healthcare

    From Technology to Clinical Practice
    • 1 Edición
    • Françoise J Siepel
    • Inglés
    Robotics for Intervention in Healthcare: From Technology to Clinical Practice bridges the gap between deep-core robotic intervention technology and clinical aspects, including content that is appropriate for physicians and clinicians. The book gives insights on the importance of connectivity in early stages, thoroughly addressing which aspects are important to improve the innovation chain.

  • Advanced Concepts in Grey Wolf Optimizer

    Leading the Pack in Advanced Optimization
    • 1 Edición
    • Seyedali Mirjalili
    • Inglés
    Advanced Concepts in Grey Wolf Optimizer: Leading the Pack in Advanced Optimization provides in-depth coverage of recent theoretical advancements in GWO, as well as advanced methods to handle issues such as multiple objectives, constraints, binary variables, large search spaces, dynamic goals, and uncertain data. This book assumes familiarity with optimization fundamentals and therefore dives directly into multi-objective, constrained, binary, and dynamic-environment variants, as well as GWO-ML/LLM hybrids. Extensive real-world case studies in areas such as energy systems, supply-chain design, LLM fine-tuning, robotics, and finance ensure that both scholars and engineers can translate the material into deployable solutions. The authors present important new theories, hybrids with Machine Learning/Deep Learning, and hybrid methods that increase GWO’s performance. The use of generative AI to improve this algorithm and make it more generic is also explored, along with diverse applications across multiple fields to illustrate the practical utility and versatility of the methods presented. Written by some of the world’s most highly cited researchers in the field of artificial intelligence, algorithms, and machine learning, the book serves as an advanced resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer.

  • Computational Intelligence in Mechatronics

    Solving Real-World Problems in Electronic Systems Design
    • 1 Edición
    • Mohamed Arezki Mellal
    • Inglés
    Computational Intelligence in Mechatronics: Solving Real-World Problems in Electronic Systems Design provides a comprehensive exploration of the diverse applications of computational intelligence in the realm of applied electronics. By compiling cutting-edge research and practical case studies, the book bridges the gap between theory and practice, offering insights into how CI techniques can be effectively utilized to solve real-world problems in electronic systems design, analysis, and optimization. Through a combination of theoretical foundations, algorithmic implementations, and practical examples, readers will gain a deeper understanding of the potential benefits and limitations of CI in various applications within the field of applied electronics.From optimizing circuit designs to enhancing signal processing algorithms, CI has demonstrated its efficacy in addressing challenges across diverse domains such as telecommunications, consumer electronics, renewable energy systems, and medical devices. As the demand for intelligent electronic systems continues to grow, understanding and harnessing the potential of computational intelligence becomes imperative for researchers, engineers, and practitioners in the field of applied electronics.

  • Advances in Medical Imaging

    From Behavioral Analysis to Disease Prevention and Rehabilitation
    • 1 Edición
    • Dilber Uzun Ozsahin + 4 más
    • Inglés
    Advances in Medical Imaging: From Behavioral Analysis to Disease Prevention and Rehabilitation presents a comprehensive exploration of the rapidly evolving field of medical imaging at the crossroads of clinical science, behavioral research, and public health. This book addresses the growing need to understand how advanced imaging technologies—such as MRI, PET, and ultrasound—are transforming healthcare beyond traditional diagnosis. By capturing structural, functional, metabolic, and molecular processes, these innovations provide new insights into brain function, lifestyle impacts, chronic disease, and rehabilitation, supporting the shift toward personalized and preventive medicine.The book is organized into five thematic sections covering a wide range of topics. Early chapters focus on the integration of neuroimaging with behavioral science, highlighting brain–behavior relationships through cutting-edge imaging modalities and cognitive software. Subsequent sections examine the effects of sedentary lifestyles on brain health, vascular function assessed by ultrasound, and musculoskeletal aging through imaging biomarkers. Additional chapters explore chronic disease management, yoga and cognitive well-being, stroke recovery, traumatic brain injury rehabilitation, and the expanding role of imaging in oncology and systemic diseases. Throughout, the book emphasizes the use of artificial intelligence, radiomics, and multimodal imaging to enhance precision medicine and population health research.Advances in Medical Imaging: From Behavioral Analysis to Disease Prevention and Rehabilitation offers valuable insights for researchers, clinicians, and healthcare professionals interested in the applications of medical imaging across multiple disciplines. It highlights imaging’s critical role in advancing personalized care, supporting preventive strategies, and fostering innovation in modern healthcare.

  • Neuro-Symbolic AI

    Integrating Neural Networks and Symbolic Reasoning
    • 1 Edición
    • Sarika Jain + 3 más
    • Inglés
    Neuro-Symbolic AI: Integrating Neural Networks and Symbolic Reasoning explores the convergence of two historically distinct paradigms in artificial intelligence—data-dr... neural networks and logic-based symbolic reasoning. This book presents a comprehensive roadmap of this emerging hybrid discipline, offering deep theoretical insights, practical methodologies, and transformative applications across diverse research sectors, including healthcare, finance, engineering, and autonomous systems. It is structured into four parts—Foundational Principles, Hybrid Models and Techniques, Real-World Applications, and Emerging Challenges, bringing together cutting-edge research and expert perspectives to highlight how Neuro-Symbolic AI enhances interpretability, reasoning capabilities, and trust in intelligent systems.While neural networks have achieved remarkable success in perception and pattern recognition tasks, they often lack the reasoning, transparency, and generalizability that symbolic systems excel at. Conversely, symbolic AI lacks the flexibility and scalability of deep learning. This handbook directly addresses these challenges by providing a structured approach to Neuro-symbolic AI, presenting rigorous theoretical foundations, state-of-the-art hybrid techniques (e.g., knowledge graphs, compositionality, category theory), and diverse real-world applications. This book consolidates research insights, methodological innovations, and practical use cases into a single, accessible volume.