Books in Artificial intelligence

Cybersecurity for Healthcare Systems in the Internet of Medical Things Era

1st Edition
January 1, 2026
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.

Medical Imaging Application in Health Assessment and Disease Management

1st Edition
January 1, 2026
Dilber Uzun Ozsahin + 4 more
English
Paperback
9 7 8 0 4 4 3 2 8 9 6 7 5
eBook
9 7 8 0 4 4 3 2 8 9 6 8 2

Medical Imaging Application in Health Assessment and Disease Management is an all-encompassing book that explores the transformative power of medical imaging in various fields of medicine. It showcases the latest advancements and applications of medical imaging modalities, ranging from neurology and oncology to audiology and osteoporosis. The book highlights the role of medical imaging in understanding and treating neurological conditions, assessing bone health, unraveling hearing disorders, and diagnosing and treating oncological conditions. It also delves into the potential of artificial intelligence and machine learning in improving cancer diagnosis and treatment. The book explores the use of medical imaging in observing mental health conditions such as autism spectrum disorder and stress-related behavioral changes. This comprehensive resource is essential for researchers and professional engineers in the fields of medical image computing/processing... computer science, artificial intelligence, radiology, neuroscience, and biomedical research.

Industry 4.0 and Sustainability

1st Edition
January 1, 2026
Muhammad Imran Khan + 2 more
English

The Fourth Industrial Revolution, commonly termed Industry 4.0, is transforming production and manufacturing through integration of advanced digital technologies like artificial intelligence (AI), industrial internet of things (IIoT), big data analytics, additive manufacturing, and advanced robotics. While much discussion has centered on potential economic impacts, Industry 4.0 also holds significant implications for sustainability across environmental, social, and economic dimensions. However, simply adopting technologies does not guarantee sustainability benefits, and improperly managed, they pose risks related to job losses, inequality, and rebound effects that must be addressed through integrative frameworks. ‘Industry 4.0 and Sustainability’ will provide the first comprehensive, evidence-based perspective unifying technological, organizational, policy, and social considerations to strategically direct Industry 4.0 innovations towards improved sustainability across economic, environmental, and social dimensions. With applied case studies and integrated roadmaps spanning engineering, management, and policy, it fills a crucial gap in guiding Industry 4.0 deployments to accelerate progress on sustainable development goals.

Multilevel Quantum Metaheuristics

1st Edition
January 1, 2026
Siddhartha Bhattacharyya + 4 more
English

Multilevel Quantum Metaheuristics: Applications in Data Exploration explores the most recent advances in hybrid quantum-inspired algorithms. Combining principles of quantum mechanics with metaheuristic techniques for efficient data optimization, this book examines multilevel quantum systems characterized by qudits and higher-level quantum states as more robust alternatives to conventional bilevel quantum approaches. It introduces novel multilevel applications of quantum metaheuristics for addressing optimization problems in areas including function optimization, data analysis, scheduling, and signal processing. The book also showcases real-world examples, case studies, and contributions that emphasize the effectiveness of proposed multilevel techniques over existing bilevel methods. Researchers, professionals, and engineers working on intelligent computing, quantum computing, data processing, clustering, and analysis, and those interested in the synergies between quantum computing, metaheuristics, and multilevel quantum systems for enhanced data exploration and analysis will find this book to be of great value.

Autonomous Vehicle Safety Solutions

1st Edition
January 1, 2026
Aparna Kumari
English

Autonomous Vehicle Safety Solutions: Foundations, Technologies, and Prospects for the Future addresses the dynamically evolving state of the art that traverses and brings together automotive engineering, electronics engineering, and computer science. Its technical overview of smart vehicles' capabilities, propelled by headway in artificial intelligence and sensor technologies, enables in-depth understanding of the safety-assurance complexities that guide their design and operation.The comprehensive volume distinguishes itself for its treatment of several exciting, emerging opportunities and trends, including machine learning algorithms, V2X connectivity, and cybersecurity. Up-to-date applications are featured through practical examples and expert insights, bringing additional value to a discourse which underscores the critical need for ongoing safety advancements and adaptability in the fast-moving context of autonomous driving systems, with their related implications on sustainability and society as a whole.The outcome is a cornerstone resource for academia and industry alike that encourages further transformative, interdisciplinary investigations to bring safety solutions to maturity and subsequent rigorous testing for validation standards to be defined, thus realizing, in a future not distant from now, a scenario where self-driving vehicles can co-exist seamlessly with traditional modes of transportation and also integrate reliably, efficiently, and without risks within the larger infrastructure.

Challenges and Applications of Generative Large Language Models

1st Edition
January 1, 2026
Anitha S. Pillai + 2 more
English

Large Language Models (LLMs) are a form of generative AI, based on Deep Learning, that rely on very large textual datasets, and are composed of hundreds of millions (or even billions) of parameters. LLMs can be trained and then refined to perform several NLP tasks like generation of text, summarization, translation, prediction, and more. Challenges and Applications of Generative Large Language Models assists readers in understanding LLMs, their applications in various sectors, challenges that need to be encountered while developing them, open issues, and ethical concerns. LLMs are just one approach in the huge set of methodologies provided by AI. The book, describing strengths and weaknesses of such models, enables researchers and software developers to decide whether an LLM is the right choice for the problem they are trying to solve. AI is the new buzzword, in particular Generative AI for human language (LLMs). As such, an overwhelming amount of hype is obfuscating and giving a distorted view about AI in general, and LLMs in particular. Thus, trying to provide an objective description of LLMs is useful to any person (researcher, professional, student) who is starting to work with human language. The risk, otherwise, is to forget the whole set of methodologies developed by AI in the last decades, sticking with only one model which, although very powerful, has known weaknesses and risks. Given the high level of hype around such models, Challenges and Applications of Generative Large Language Models (LLMs) enables readers to clarify and understand their scope and limitations.

Decision Systems

1st Edition
January 1, 2026
Pallavi Vijay Chavan + 3 more
English

Decision Systems: Integrating Machine Learning, Fuzzy Logic, and Artificial Neural Networks provides readers with a comprehensive understanding of the principal techniques used to build effective decision-making systems. This book covers the fundamental principles and concepts of machine learning, fuzzy logic, and artificial neural networks, and explains how these techniques can be used to build intelligent decision-making systems that can learn from data, reason, and make accurate predictions. The book also presents a wide range of applications of machine learning, fuzzy logic, and artificial neural networks in various domains, such as engineering, medicine, finance, and robotics. The book also provides practical guidance on how to design and implement effective decision-making systems using these techniques and discusses the potential challenges and limitations of machine learning, fuzzy logic, and artificial neural networks, and how to overcome them. The book provides a stepwise approach to provide readers with the knowledge and tools they need to build intelligent decision-making systems, including a robust introduction to the mathematical concepts and principles necessary to understand the concepts and applications of Decision Systems and Machine Learning algorithms. Next, the book provides readers with an in-depth explanation and demonstration of two of the major machine learning techniques – Fuzzy Logic/Fuzzy Set Theory and Artificial Neural Networks – followed by an in-depth look at more advanced topics that play essential roles in making machine learning algorithms more useful in practice, including creating full-fledged Recurrent Networks and their mathematical foundations, Associative Memories, and Deep Learning networks such as Convolutional Neural Networks, Generative Adversarial Networks, Radial Basis Function Networks, Multilayer Perceptrons, and Self-Organizing Maps. The lynchpin of the book provides readers with an understanding of how the various types of techniques can be integrated to create dynamic Decision Systems. The book wraps up with coverage of challenges and opportunities in Decision Systems along with real-world applications of Decision Systems with case studies in healthcare, finance, education, social media, and agriculture.

Edge Intelligence

1st Edition
January 1, 2026
Jawad Ahmad + 5 more
English

Edge Intelligence: Advanced Deep Transfer Learning for IoT Security presents a comprehensive exploration into the critical intersection of cybersecurity, edge computing, and deep learning, offering practitioners, researchers, and cybersecurity professionals a definitive guide to protect IoT/IIoT systems. This book delves into the synergistic potential of edge computing and advanced machine/deep learning algorithms, providing insights into lightweight and resource-efficient models with a special focus on resource-constrained edge devices. The rapidly evolving nature of cyberattacks underscores the need for updated and integrated resources that address the intersection of cybersecurity, edge computing, and deep learning. The authors address this issue by offering practical insights, lightweight models, and proactive defense mechanisms tailored to the unique challenges of securing edge devices and networks. This book is not only written to provide its audience effective strategies to detect and mitigate network intrusions by leveraging edge intelligence and advanced deep transfer learning techniques but also to provide practical insights and implementation guidelines tailored to resource-constrained edge devices.

Advanced Intelligence Methods for Data Science and Optimization

1st Edition
December 1, 2025
Amir Hossein Gandomi + 2 more
English
Paperback
9 7 8 0 4 4 3 2 8 9 4 0 8
eBook
9 7 8 0 4 4 3 2 8 9 4 1 5

Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains.It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.

Intelligent and Soft Computing

1st Edition
December 1, 2025
Ishaani Priyadarshini + 3 more
English
Paperback
9 7 8 0 4 4 3 3 0 0 9 0 5
eBook
9 7 8 0 4 4 3 3 0 0 9 1 2

Intelligent and Soft Computing: Techniques and Applications illustrates the synergistic effect of cutting-edge developments in all areas of both fields to build intelligent software systems to solve a multitude of problems. The book offers an introduction to artificial intelligence as well as fuzzy logic concepts, systems, and methods. Additional sections focus on AI tools and applications, search and data mining, reasoning and evolution, as well as nature-inspired computing techniques. Applications and case studies are included in all chapters, making this an ideal resource for researchers, graduate students, and professionals working in these domains.Readers will find this to be a timely reference on current and future developments in this emerging domain for decision support, management, information technology, and business applications.

Related subjects

Artificial intelligence expert systems and knowledge based systems

Artificial intelligence general

Cognitive science

Computer human interaction

Evolutionary computation genetic algorithms programming

Fuzzy logic

Machine learning

Natural language and computational linguistics

Neural networks

Planning and scheduling

Reasoning

Robotics and autonomous systems

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health