Books in Artificial intelligence general

1-10 of 103 results in All results

Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT)

• 1st Edition
• March 1, 2025
• Yacine Atif + 1 more
• Fatos Xhafa
• English
• Paperback 978-0-443-22217-7

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• eBook 978-0-443-22218-4

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Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT) is a reference for IT engineers and decision-makers who may engage in IoT platform pilot projects. The resources covered in this book help establish plans for sustainable operations and management and assist with the long-term procurement of relevant IoT technologies. The aim of the book is to be exhaustive and holistic by pointing out numerous issues and related solution options that guide with daily challenges when deploying and running IoT platforms.The book is divided into three parts where each part includes relevant theoretical chapters and applied case studies. Part One focuses on architectural and federation options for the design and implementation of IoT platforms that foster strategic collaboration opportunities. Part Two addresses vertical security challenges across IoT platform layers. Finally, Part Three shows how IoT is driving the digital transformation wheel through existing and forthcoming case studies.

Artificial Neural Networks and Type-2 Fuzzy Set

• 1st Edition
• March 1, 2025
• Snehashish Chakraverty
• English
• Paperback 978-0-443-32894-7

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• eBook 978-0-443-32895-4

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Soft computing is an emerging discipline which aims to exploit tolerance for imprecision, approximate reasoning, and uncertainty to achieve robustness, tractability, and cost effectiveness for building intelligent machines. Soft computing methodologies include neural networks, fuzzy sets, genetic algorithms, Bayesian networks, and rough sets, among others. In this regard, neural networks are widely used for modeling dynamic solvers, classification of data, and prediction of solutions, whereas fuzzy sets provide a natural framework for dealing with uncertainty. Artificial Neural Networks and Type-2 Fuzzy Set: Elements of Soft Computing and Its Applications covers the fundamental concepts and the latest research on variants of Artificial Neural Networks (ANN), including scientific machine learning and Type-2 Fuzzy Set (T2FS). In addition, the book also covers different applications for solving real-world problems along with various examples and case studies. It may be noted that quite a bit of research has been done on ANN and Fuzzy Set theory/ Fuzzy logic. However, Artificial Neural Networks and Type-2 Fuzzy Set is the first book to cover the use of ANN and fuzzy set theory with regards to Type-2 Fuzzy Set in static and dynamic problems in one place. Artificial Neural Networks and Type-2 Fuzzy Sets are two of the most widely used computational intelligence techniques for solving complex problems in various domains. Both ANN and T2FS have unique characteristics that make them suitable for different types of problems. This book provides the reader with in-depth understanding of how to apply these computational intelligence techniques in various fields of science and engineering in general and static and dynamic problems in particular. Further, for validation purposes of the ANN and fuzzy models, the obtained solutions of each model in the book is compared with already existing solutions that have been obtained with numerical or analytical methods.

The Digital Doctor

• 1st Edition
• January 10, 2025
• Chayakrit Krittanawong
• English
• Paperback 978-0-443-15728-8

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• eBook 978-0-443-34344-5

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The Digital Doctor: How Digital Health Can Transform Healthcare discusses digital health and demonstrates the appropriateness of each technology using an evidence-based approach. It serves as a comprehensive summary on current, evidence-based digital health applications, future novel digital health technologies (e.g., mobile health, blockchain, web3.0), as well as some of the current challenges and future directions for digital health within the various medical subspecialties. This book is a comprehensive review of digital health for clinicians, researchers, bioinformatic students, biomedical engineers interested in this topic.

Federated Learning for Medical Imaging

• 1st Edition
• December 1, 2024
• Xiaoxiao Li + 2 more
• English
• Paperback 978-0-443-23641-9

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• eBook 978-0-443-23642-6

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Federated Learning for Medical Imaging: Principles, Algorithms and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging.In addition, it provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc. This is a complete resource for computer scientists and engineers as well as clinicians and medical care policymakers wanting to learn about the application of federated learning to medical imaging.

Trustworthy AI in Medical Imaging

• 1st Edition
• December 1, 2024
• Marco Lorenzi + 1 more
• English
• Paperback 978-0-443-23761-4

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• eBook 978-0-443-23760-7

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Trustworthy AI in Medical Imaging brings together scientific researchers, medical experts, and industry partners working in the field of trustworthiness, bridging the gap between AI research and concrete medical applications and making it a learning resource for undergraduates, masters students, and researchers in AI for medical imaging applications.The book will help readers acquire the basic notions of AI trustworthiness and understand its concrete application in medical imaging, identify pain points and solutions to enhance trustworthiness in medical imaging applications, understand current limitations and perspectives of trustworthy AI in medical imaging, and identify novel research directions.Although the problem of trustworthiness in AI is actively researched in different disciplines, the adoption and implementation of trustworthy AI principles in real-world scenarios is still at its infancy. This is particularly true in medical imaging where guidelines and standards for trustworthiness are critical for the successful deployment in clinical practice. After setting out the technical and clinical challenges of AI trustworthiness, the book gives a concise overview of the basic concepts before presenting state-of-the-art methods for solving these challenges.

Primer to Neuromorphic Computing

• 1st Edition
• November 25, 2024
• Harish Garg + 3 more
• English
• Paperback 978-0-443-21480-6

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• eBook 978-0-443-21482-0

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Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning, and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture.Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains.

IoMT Applications in Healthcare 5.0

• 1st Edition
• November 22, 2024
• English
• Paperback 978-0-443-30157-5

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• eBook 978-0-443-30158-2

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IoMT Applications in Healthcare 5.0 introduces the concept of Healthcare 5.0, emphasizing the transformative potential of intelligent diagnosis, remote treatment, and smart health management. Sections define IoMT and its multi-tiered architecture, discussing its pivotal role in improving electronic device productivity in healthcare, explore IoMT applications in Healthcare 5.0, discuss remote physical therapy using IoMT in Healthcare 5.0, delve into the security and privacy considerations of IoMT in healthcare, and address how to overcome challenges and future directions in IoMT. The book concludes by summarizing key findings, providing a comprehensive overview of the discussed topics.Written by experts in the field, this is a key text for Biomedical Engineers, Data Scientists, and IoT Developers and specialists who work in the Internet of Medical Things. Graduate students of IoT engineering, biology, biostatistics, biomedical sciences, bioinformatics, health-informatics, and Interdisciplinary sciences will also find this an invaluable resource.

Empowering IoT with Big Data Analytics

• 1st Edition
• November 20, 2024
• Mohamed Adel Serhani + 2 more
• English
• Paperback 978-0-443-21640-4

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• eBook 978-0-443-21641-1

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Empowering IoT with Big Data Analytics provides comprehensive coverage of major topics, tools, and techniques related to empowering IoT with big data technologies and big data analytics solutions, thus allowing for better processing, analysis, protection, distribution, and visualization of data for the benefit of IoT applications and second, a better deployment of IoT applications on the ground. This book covers big data in the IoT era, its application domains, current state-of-the-art in big data and IoT technologies, standards, platforms, and solutions. This book provides a holistic view of the big data value-chain for IoT, including storage, processing, protection, distribution, analytics, and visualization.Big data is a multi-disciplinary topic involving handling intensive, continuous, and heterogeneous data retrieved from different sources including sensors, social media, and embedded systems. The emergence of Internet of Things (IoT) and its application to many domains has led to the generation of huge amounts of both structured and unstructured data often referred to as big data.

Intelligent Biomedical Technologies and Applications for Healthcare 5.0

• 1st Edition
• Volume 16
• November 1, 2024
• Lalit Garg + 3 more
• English
• Paperback 978-0-443-22038-8

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• eBook 978-0-443-22039-5

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Intelligent Biomedical Technologies and Applications for Healthcare 5.0, Volume Sixteen covers artificial health intelligence, biomedical image analysis, 5G, the Internet of Medical Things, intelligent healthcare systems, and extended health intelligence (EHI). This volume contains four sections. The focus of the first section is health data analytics and applications. The second section covers research on information exchange and knowledge sharing. The third section is on the Internet of Things (IoT) and the Internet of Everything (IoE)-based solutions. The final section focuses on the implementation, assessment, adoption, and management of healthcare informatics solutions.This new volume in the Advances in Ubiquitous Sensing Applications for Healthcare series focuses on innovative methods in the healthcare industry and will be useful for biomedical engineers, researchers, and students working in interdisciplinary fields of research. This volume bridges these newly developing technologies and the medical community in the rapidly developing healthcare world, introducing them to modern healthcare advances such as EHI and Smart Healthcare Systems.

Fuzzy Methods for Assessment and Decision Making

• 1st Edition
• October 18, 2024
• Michael Gr. Voskoglou
• English
• Paperback 978-0-443-23732-4

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• eBook 978-0-443-23733-1

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Fuzzy Methods for Assessment and Decision Making presents the assessment of learning and problem-solving skills with qualitative grades. These methods are outcomes of the author’s research work on the subject for more than 20 years. In particular, a hybrid assessment model uses the Center of Gravity (COG) defuzzification technique, closed real intervals (grey numbers), neutrosophic sets, and soft sets as tools. The book starts with the basic mathematical background that is needed for an understanding of its contents. The Rectangular Fuzzy Assessment Model (RFAM) of Subbotin and Voskoglou is presented next, the outcomes of which are compared to those of the GPA index.The book presents innovative fuzzy assessment methods, enabling readers to assess the mean and quality performance of learning or problem-solving skills of a group of students when qualitative (linguistic) grades are used for this purpose. In the case of using linguistic grades for the assessment of a group’s skills, the classical method of calculating the mean value of the (numerical) grades cannot be applied. Also, no safe conclusions can be obtained on comparing the quality performance of two groups when the values of their GPA index are equal.