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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.
Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple te...
The book Digital Health Transformation with Blockchain and Artificial Intelligence covers the global digital revolution in the field of healthcare sector. The population has been overcoming the COVID-19 period; therefore, we need to establish intelligent digital healthcare systems using various emerging technologies like Blockchain and Artificial Intelligence. Internet of Medical Things is the technological revolution that has included the element of "smartness" in the healthcare industry and also identifying, monitoring, and informing service providers about the patient’s clinical information with faster delivery of care services. This book highlights the important issues i.e. (a) How Int...
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 ...
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...
The book Intelligent Healthcare: Infrastructure, Algorithms, and Management® cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning. This book will prov...
One of the central engines of the current shift towards decentralization and reorientation of healthcare services is mobile healthcare (mHealth). mHealth offers unique opportunities to reduce cost, increase efficiencies, and improve quality and access to healthcare. However, the full impact of mHealth is just beginning to be felt by the medical community and requires further examination to understand the full range of benefits it contributes to medical staff and patients. Mobile Health Applications for Quality Healthcare Delivery explores the emergence of mHealth in the healthcare setting and examines its impact on patient-centered care, including how it has reshaped access, quality, and treatment. Highlighting topics such as patient management, emergency medicine, and health monitoring, this publication supports e-health systems designers in understanding how mobile technologies can best be used for the benefit of both doctors and their patients. It is designed for healthcare professionals, administrators, students, health services managers, and academicians.
The key parameter that needs to be considered when planning the management of resources in futuristic wireless networks is a balanced approach to resource distribution. A balanced approach is necessary to provide an unbiased working environment for the distribution, sharing, allocation, and supply of resources among the devices of the wireless network. Equal resource distribution also maintains balance and stability between the operations of communication systems and thus improves the performance of wireless networks. Managing Resources for Futuristic Wireless Networks is a pivotal reference source that presents research related to the control and management of key parameters of bandwidth, s...
Energy Harvesting: Enabling IoT Transformations gives insight into the emergence of energy harvesting technology and its integration with IoT-based applications. The book educates the reader on how energy is harvested from different sources, increasing the effectiveness, efficiency and lifetime of IoT devices. • Discusses the technology and practices involved in energy harvesting for biomedical, agriculture and automobile industries • Compares the performance of IoT-based devices with and without energy harvesting for different applications • Studies the challenges and issues in the implementation of EH-IoT • Includes case studies on energy-harvesting approach for solar, thermal and RF sources • Analyzes the market and business opportunities for entrepreneurs in the field of EH-IoT. This book is primarily aimed at graduates and research scholars in wireless sensor networks. Scientists and R&D workers in industry will also find this book useful.
Advances in medical technology increase both the efficacy and efficiency of medical practice, and mobile technologies enable modern doctors and nurses to treat patients remotely from anywhere in the world. This technology raises issues of quality of care and medical ethics, which must be addressed. E-Health and Telemedicine: Concepts, Methodologies, Tools, and Applications explores recent advances in mobile medicine and how this technology impacts modern medical care. Three volumes of comprehensive coverage on crucial topics in wireless technologies for enhanced medical care make this multi-volume publication a critical reference source for doctors, nurse practitioners, hospital administrators, and researchers and academics in all areas of the medical field. This seminal publication features comprehensive chapters on all aspects of e-health and telemedicine, including implementation strategies; use cases in cardiology, infectious diseases, and cytology, among others; care of individuals with autism spectrum disorders; and medical image analysis.