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The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data pr...
The book aims to showcase the basics of both IoT and Blockchain for beginners as well as their integration and challenge discussions for existing practitioner. It aims to develop understanding of the role of blockchain in fostering security. The objective of this book is to initiate conversations among technologists, engineers, scientists, and clinicians to synergize their efforts in producing low-cost, high-performance, highly efficient, deployable IoT systems. It presents a stepwise discussion, exhaustive literature survey, rigorous experimental analysis and discussions to demonstrate the usage of blockchain technology for securing communications. The book evaluates, investigate, analyze and outline a set of security challenges that needs to be addressed in the near future. The book is designed to be the first reference choice at research and development centers, academic institutions, university libraries and any institutions interested in exploring blockchain. UG/PG students, PhD Scholars of this fields, industry technologists, young entrepreneurs and researchers working in the field of blockchain technology are the primary audience of this book.
The book focuses on developments in artificial intelligence (AI) and internet of things (IoT) integration for smart healthcare, with an emphasis on current methodologies and frameworks for the design, growth, implementation, and creative use of such convergence technologies to provide insight into smart healthcare service demands. Concepts like signal recognition, computation, internet of health stuff, and so forth and their applications are covered. Development in connectivity and intelligent networks allowing for social adoption of ambient intelligence is also included. Features: •Introduces Intelligent IoT as applicable to the key areas of smart healthcare. •Discusses computational in...
Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of ma...
This book discusses smart technologies and their influence in the field of manufacturing and industrial systems engineering, in the context of performability enhancement, and explores the development of the workforce for the execution of such smart and advanced technologies. Smart Technologies for Improved Performance of Manufacturing Systems and Services discusses the integration of smart technology into the production process and supply chain to enhance the overall performance of manufacturing industries. As well as emphasizing the fundamentals of smart technologies, such as artificial intelligence, big data, and cyber-physical systems, it highlights the role that machine learning plays along with other smart technologies. Real-time case studies highlight the applications of smart digital technologies, and research insights into the area of performability and overall sustainable development round out the great range of discussions this reference book has to offer. Managers and stakeholders seeking coverage on techniques and methods for integration into their organizations, as well as students and researchers in the field will find this book very useful.
Digital technologies is a major emerging area to invest and research in new models of health management. Future health scenarios are constituted by technologies in health and clinical decision-making systems. This book provides a unique multidisciplinary approach for exploring the potential contribution of AI and digital technologies in enabling global healthcare systems to respond to urgent twenty-first-century challenges. Deep analysis has been made regarding telemedicine using big data, deep learning, robotics, mobile and remote applications. Features: Focuses on prospective scenarios in health to predict possible futures. Addresses the urgent needs of the key population, socio-technical ...
Constant improvements in technological applications have allowed for more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but also ensures that technological progression will continue. Ubiquitous Machine Learning and its Applications is a pivotal reference source for the latest research on the issues and challenges machines face in the new millennium. Featuring extensive coverage on relevant areas such as computational advertising, software engineering, and bioinformatics, this publication is an ideal resource for academicians, graduate students, engineering professionals, and researchers interested in discovering how they can apply these advancements to various disciplines.
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information. Features: Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications. Investigates privacy-preserving methods with emphasis on data security and privacy. Discusses healthcare scaling and resource efficiency considerations. Examines methods for sharing information among various healthcare organizations while retaining model performance. This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.
This book covers the fundamentals, applications, algorithms, protocols, emerging trends, problems, and research findings in the field of AI and IoT in smart healthcare. It includes case studies, implementation and management of smart healthcare systems using AI. Chapters focus on AI applications in Internet of Healthcare Things, provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and AI, with the real-world examples. This book is aimed at Researchers and graduate students in Computer Engineering, Artificial Intelligence and Machine Learning, Biomedical Engineering, and Bioinformatics. Features: Focus on ...
Internet of Healthcare Things (IoHT) is an Internet of Things (IoT)-based solution that includes a network architecture which allows the connection between a patient and healthcare facilities. This book covers various research issues of smart and secure IoHT, aimed at providing solutions for remote healthcare monitoring using pertinent techniques. Applications of machine learning techniques and data analytics in IoHT, along with the latest communication and networking technologies and cloud computing, are also discussed. Features: Provides a detailed introduction to IoHT and its applications Reviews underlying sensor and hardware technologies Includes recent advances in the IoHT, such as remote healthcare monitoring and wearable devices Explores applications of data analytics/data mining in IoHT, including data management and data governance Focuses on regulatory and compliance issues in IoHT This book is intended for graduate students and researchers in Bioinformatics, Biomedical Engineering, Big Data and Analytics, Data Mining, and Information Management, IoT and Computer and Electrical Engineering.