Books in Artificial intelligence general

Multimodal Learning Using Heterogeneous Data

1st Edition
November 1, 2025
Saeid Eslamian + 3 more
English

Multimodal Learning Using Heterogeneous Data is a comprehensive guide to the emerging field of multimodal learning, which focuses on integrating diverse data types such as text, images, and audio within a unified framework. The book delves into the challenges and opportunities presented by multimodal data and offers insights into the foundations, techniques, and applications of this interdisciplinary approach. It is intended for researchers and practitioners interested in learning more about multimodal learning and is a valuable resource for those working on projects involving data analysis from multiple modalities.The book begins with a comprehensive introduction, focusing on multimodal learning's foundational principles and the intricacies of heterogeneous data. It then delves into feature extraction, fusion techniques, and deep learning architectures tailored for multimodal data. It also covers transfer learning, pre-processing challenges, and cross-modal information retrieval. The book highlights the application of multimodal learning in specialized contexts such as sentiment analysis, data generation, medical imaging, and ethical considerations. Real-world case studies are woven into the narrative, illuminating the applications of multimodal learning in diverse domains such as natural language processing, multimedia content analysis, autonomous systems, and cognitive computing. The book concludes with an insightful exploration of multimodal data analytics across social media, surveillance, user behavior, and a forward-looking examination of future trends and practical implementations. As a collective resource, Multimodal Learning Using Heterogeneous Data illuminates the powerful utility of multimodal learning to elevate machine learning tasks while also highlighting the need for innovative solutions and methodologies. The book acknowledges the challenges associated with deep learning and the growing importance of ethical considerations in the collection and analysis of multimodal data.Overall, Multimodal Learning Using Heterogeneous Data provides an expansive panorama of this rapidly evolving field, its potential for future research and application, and its vital role in shaping machine learning's evolution.

AI and Data Science in Medical Research

1st Edition
November 1, 2025
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. It 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.

Digital Transformation in Artificial Systems

1st Edition
November 1, 2025
Mirko Farina + 3 more
English

The last decade has seen exponential growth in the development of digital technologies. These have led to significant shifts in the political arena as well as in the economy, precipitating a series of revolutionary changes in the fabric of our societies, which have had far reaching consequences and effects on the way we relate and connect to each other. Digital Transformation in Artificial Systems: Engineering Requirements and Political, Economic, and Philosophical Challenges focuses on analyzing the engineering requirements as well as the political consequences and the overarching philosophical and ethical implications of this transformation, especially in relation to its application in Artificial Systems. In this context, the concept of digital transformation (understood as the practice of redefining models, functions, operations, processes, and activities by leveraging technological advancements to build efficient digital environments) has become increasingly important. While many researchers have studied and analyzed this concept from the perspective of their own disciplinary norms or boundaries, this book brings together key concepts, ideas, and frameworks related to this idea and previously developed in isolation (in disciplines such as computer science, engineering, philosophy, economy, and sociology).Digital Transformation in Artificial Systems: Engineering Requirements and Political, Economic, and Philosophical Challenges focuses on analyzing the engineering requirements as well as the political consequences and the overarching philosophical and ethical implications of this notion, especially in relation to its application in Artificial Systems. The authors encourage and promote an inclusive and responsible digital transformation (development) capable of addressing constraints on global digital divide; deepening cooperation in digitization, industrialization, and innovation, while furthering our understanding of the ethical and moral challenges associated with such a development. The distinctive and most original element of the book is its interdisciplinarity. The development of a collaborative, highly interdisciplinary, and synthetic framework for describing digital transformation in artificial systems as discussed by the authors will allow readers to gather crucial insights that will be instrumental to better understand the reach of the forthcoming AI revolution, its multidimensionality, as well as its potential impact on people and society. Such an original and multidisciplinary understanding is of paramount importance for the realization of practical objectives (such as the development of fairer policies) that will ultimately be directed at promoting human flourishing, social harmony, and moral good.

Artificial Intelligence for the Water-Energy-Food Nexus

1st Edition
November 1, 2025
Shahryar Jafarinejad + 1 more
English

Artificial Intelligence for the Water-Energy-Food Nexus explores the intricate connections between water, energy, and food—essentials for sustainable development—and the transformative potential of artificial intelligence (AI) within these domains. It begins by introducing the water-energy-food nexus, outlining the three dimensions: water-energy, water-food, and energy-food nexus. The book discusses assessment methods, challenges, opportunities, trends, and future perspectives. Subsequent chapters delve into AI techniques like machine learning, natural language processing, computer vision, and robotics. It studies AI applications in water treatment, wastewater management, renewable energy systems, smart grids, and food industry processes such as sorting, detection, safety, quality analysis, and packaging.The final chapter integrates AI applications across all these nexuses, making the book indispensable for researchers, students, engineers, industry professionals, and policymakers.

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

1st Edition
November 1, 2025
Olfa Boubaker
English

AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice explores the transformative role of AI and data science in enhancing precision medicine, predictive analytics, and medical practice. It covers diverse topics such as AI-driven personalized medicine, seizure prediction through EEG analysis, and the application of chaos theory in AI-driven healthcare. The volume also delves into medical practice and education, including ethical considerations, AI-driven supply chain management, and clinical documentation using natural language processing. Furthermore, it examines AI's role in telemedicine, patient engagement, and adherence, offering innovative solutions to improve healthcare delivery and outcomes.

AI and Data Science in Healthcare 5.0

1st Edition
November 1, 2025
Olfa Boubaker
English

AI and Data Science in Healthcare 5.0 delves into the innovative developments in Healthcare 5.0, focusing on smart medical robots, devices, and connected hospitals. It explores the role of robotics in modern healthcare, including advanced wearables enhanced by deep learning. The volume also addresses the integration of blockchain technology, IoT, and cloud computing in healthcare, emphasizing real-time applications in precision healthcare. The discussion extends to energy optimization in smart hospitals, federated learning for IoMT networks, and advanced patient monitoring systems. The volume concludes with an overview of the future opportunities and challenges in Healthcare 5.0.

Exploring Infant Cry

1st Edition
November 1, 2025
Carlos Alberto Reyes Garcia + 3 more
English

Exploring Infant Cry: Medical and Technological Analysis and Signal Processing Perspectives brings together the most advanced medical and technical knowledge in the study of infant crying. This book includes medical, technical, and computational approaches to cry processing for classification and diagnostic purposes. The book is written by medical and technical experts in Infant Cry processing and is an important step forward for research dealing with the process and interpretation of crying from both medical and technical perspectives. The number of research groups dedicated to this area has been growing, and with more research emerging it will be possible to use crying analysis as a powerful non-intrusive diagnostic tool for a large number of pathologies from the time they begin to appear, as well as for determining the cause of the crying in such a way as to tell parents the various reasons why a baby is crying. Exploring Infant Cry: Medical and Technological Analysis and Signal Processing Perspectives presents the advances of international groups of researchers where normal and pathological patterns of infant crying are studied, the possibilities of cry analysis for neonatal diagnosis, as well as perspectives on the development of this emerging field of research. The links of a baby’s first cries with the formation of language are addressed in the volume, as well as the communicative potential of the crying signal that makes this attribute a primary part of the vast and complex environment of human communication. Although the analysis of infant crying has received the attention of scientists and scholars of crying from diverse and varied approaches for more than 50 years, it continues to be an open topic with multiple unsolved or sufficiently investigated aspects, mainly in the area of routine applications to neonatal diagnosis.Exploring Infant Cry: Medical and Technological Analysis and Signal Processing Perspectives brings together for the first time the most advanced medical and technical knowledge on the study of crying babies. Considering on one hand the most important information as a diagnostic element, from the medical point of view, along with that provided by the technological field in order to automate acoustic processing, extraction of the most distinctive features, as well as recognition of outstanding patterns and their classification by type of pathology or cause of crying. These provide informative support tools for biomedical researchers, doctors, and clinicians. As a contribution to the technological support, a notable aspect of the book is the authors’ compilation of the most recent approaches to the classification of infant crying in correspondence with the important advances achieved in the field of signal processing, Artificial Intelligence, and soft computing. Readers of the book will find it to be an effective way to discover the foundations of the analysis of infant crying, as well as the various approaches and perspectives that have made it possible to advance the understanding of crying as an acoustic, neurophysiological, communicative, and linguistic phenomenon.

Intelligent Systems for Neurocognition and Human-Robot-Computer Interaction

1st Edition
October 20, 2025
Shubham Mahajan + 2 more
English

Intelligent Systems for Neurocognition and Human-Robot-Computer Interaction explores the transformative potential of intelligent systems in enhancing human well-being through advancements in neurocognitive technologies, robotics, and AI-driven healthcare. This book addresses the fragmented knowledge at the intersection of these fields, enabling readers to understand the latest advancements and discover practical strategies for implementation. It highlights the importance of ethical considerations and governance in deploying AI and robotics in healthcare settings. Each chapter covers various aspects, including personalized medicine, human-robot interaction, cognitive robotics, wearable technologies, and the role of AI in mental health. The book also discusses the implications of cloud computing, big data, and human-computer interaction in enhancing cognitive and emotional well-being.

Data-Driven Diagnostics and Disease Prediction with AI Optimization

1st Edition
October 1, 2025
Shailendra Pratap Singh + 3 more
English

Data-Driven Diagnostics and Disease Prediction with AI Optimization provides useful insights into model creation, data preparation, and ethical issues for healthcare applications. The book covers all the conventional and non-conventional methods related to this domain. It also discusses AI-based optimization techniques, Machine Learning models, and Advanced AI, offering practical insights, case studies, and optimization strategies to help data scientists and researchers efficiently employ AI in diagnostics and illness prediction in a world where precise diagnostics and early illness prediction may save lives and healthcare resources.

Artificial Intelligence Data and Model Safety

1st Edition
September 1, 2025
Yu-Gang Jiang + 2 more
English
Paperback
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eBook
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Artificial Intelligence Data and Model Safety: Risks, Attacks and Defenses begins with a brief review of the history of AI and AI security and then introduces the fundamental aspects of machine learning and AI security. Two key aspects are covered: data security and modelling. It provides detailed explanations of a wide range of attacks and defense algorithms related to data security, as well as adversarial attack/defense, backdoor attack/defense, and extraction attack/defense algorithms related to model security. By providing a systematic, comprehensive, and in-depth introduction to the topic, this book help readers understand the advanced attack and defense techniques in the field of AI security.

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