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Wireless Body Area Networks (WBANs) are vulnerable to cyberattacks and security breaches that could unlock the door for cybercriminals to penetrate hospital networks. This book covers the fundamental concepts of security and privacy in WBANs including security requirements, issues, and challenges. Security, Privacy, and Trust in WBANs and E-Healthcare highlights the taxonomy of threats and attacks in WBANs and Internet of Medical Things (IoMT) and presents all technical aspects related to the security and privacy of WBANs. In addition to outlining viable solutions that take into account constrained resources at WBAN end-devices, hybrid network architecture, application characteristics, and c...
The book is a collection of best selected research papers presented at the Third World Conference on Internet of Things: Applications & Future (ITAF 2023) organized by Global Knowledge Research Foundation in Cairo during February 4–5, 2023. It includes innovative works from researchers, leading innovators, business executives, and industry professionals to examine the latest advances and applications for commercial and industrial end users across sectors within the emerging Internet of things ecosphere. It shares state-of-the-art as well as emerging topics related to Internet of things such as big data research, emerging services and analytics, Internet of things (IoT) fundamentals, electronic computation and analysis, big data for multi-discipline services, security, privacy and trust, IoT technologies, and open and cloud technologies.
The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018. The 373 revised full papers presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the following topical sections: Part I: Image Quality and Artefacts; Image Reconstruction Methods; Machine Learning in Medical Imaging; Statistical Analysis for Medical Imaging; Image Registration Methods. Part II: Optical and Histology Applications: Optical Imaging Applications; Histo...
Healthcare Solutions Using Machine Learning and Informatics covers novel and innovative solutions for healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, and intelligent IoT-based solutions for medical image analysis, medical big-data processing, and disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence. The wide variety of topics covered include: Artificial Intelligen...
In the face of an evolving global landscape characterized by climate change and a pressing need for sustainable development, the finance sector remains at a critical juncture. Traditional financial models struggle to address the challenges posed by the transition to a low-carbon economy, and unlocking private investments for sustainable initiatives remains an uphill battle. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into financial systems presents both promise and peril, with the potential to reshape the industry while posing unprecedented challenges. Issues of Sustainability in AI and New-Age Thematic Investing is a beacon of insight and solutions in the realm of green finance and AI/ML integration. Geared toward academic scholars, policymakers, and industry experts, this book serves as a comprehensive guide to navigating the intricacies of sustainable development and energy transition. By highlighting the pivotal role of AI/ML in green finance, the publication bridges the gap between theoretical understanding and practical implementation, offering actionable solutions for unlocking private investments.
The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learnin...
Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression. The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.
The construction sector plays an essential role in the global economy, using many exhaustible natural resources, most of which are renewable in low percentages. Moving towards a circular economy is essential because optimizing the consumption of materials and energy contributes to the development of an economic system that is independent, more competitive, and more resilient in the face of economic and social crises and various environmental factors. The current “take, make, and dispose” model of the economy is unsustainable, so a shift in thinking towards a circular economy is necessary. This circular economy is an economic model that minimizes the use of natural resources by selecting ...
This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.
This volume comprises of 21 selected chapters, including two overview chapters devoted to abdominal imaging in clinical applications supported computer aided diagnosis approaches as well as different techniques for solving the pectoral muscle extraction problem in the preprocessing part of the CAD systems for detecting breast cancer in its early stage using digital mammograms. The aim of this book is to stimulate further research in medical imaging applications based algorithmic and computer based approaches and utilize them in real-world clinical applications. The book is divided into four parts, Part-I: Clinical Applications of Medical Imaging, Part-II: Classification and clustering, Part-III: Computer Aided Diagnosis (CAD) Tools and Case Studies and Part-IV: Bio-inspiring based Computer Aided diagnosis techniques.