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Author: Vyasa Sai
Publisher: Springer Nature
ISBN: 3031738497
Category :
Languages : en
Pages : 150
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Book Description
Author: Vyasa Sai
Publisher: Springer Nature
ISBN: 3031738497
Category :
Languages : en
Pages : 150
Get Book Here
Book Description
Author: Ashish Kumar
Publisher: CRC Press
ISBN: 100089584X
Category : Technology & Engineering
Languages : en
Pages : 331
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Book Description
In today’s era, there is a need for a system that can automate the process of treatment for the patient if medical facilities are out of reach. Smart healthcare can step in to make the patient more self-dependent. 6G with its features can be seen as the future of smart healthcare with IoT and AI. 6G-Enabled IoT and AI for Smart Healthcare: Challenges, Impact, and Analysis offers the fundamentals, history, reality, and challenges faced in the smart healthcare industry today. It discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used. The book details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems. The book goes on to presents applications of smart healthcare through various real-world examples and includes chapters on security and privacy in the 6G-enabled and IoT environment, as well as research on the future prospects of the smart healthcare industry. This book: Offers the fundamentals, history, reality, and the challenges faced in the smart healthcare industry Discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used Details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems Presents applications of smart healthcare through various real-world examples Includes topics on security and privacy in 6G-enabled IoT, as well as research and future prospectus of the smart healthcare industry Interested readers of this book will include anyone working in or involved in smart healthcare research which includes, but is not limited to healthcare specialists, computer science engineers, electronics engineers, systems engineers, and pharmaceutical practitioners.
Author: Mohit Kumar
Publisher: Springer Nature
ISBN: 3031301013
Category : Computers
Languages : en
Pages : 416
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Book Description
Over the past few years, the demand for data traffic has experienced explosive growth thanks to the increasing need to stay online. New applications of communications, such as wearable devices, autonomous systems, drones, and the Internet of Things (IoT), continue to emerge and generate even more data traffic with vastly different performance requirements. With the COVID-19 pandemic, the need to stay online has become even more crucial, as most of the fields, would they be industrial, educational, economic, or service-oriented, had to go online as best as they can. As the data traffic is expected to continuously strain the capacity of future communication networks, these networks need to evolve consistently in order to keep up with the growth of data traffic. Thus, more intelligent processing, operation, and optimization will be needed for tomorrow’s communication networks. The Sixth Generation (6G) technology is latest approach for mobile systems or edge devices in terms of reduce traffic congestions, energy consumption blending with IoT devices applications. The 6G network works beyond the 5G (B5G), where we can use various platforms as an application e.g. fog computing enabled IoT networks, Intelligent techniques for SDN network, 6G enabled healthcare industry, energy aware location management. Still this technology must resolve few challenges like security, IoT enabled trust network. This book will focus on the use of AI/ML-based techniques to solve issues related to 6G enabled networks, their layers, as well as their applications. It will be a collection of original contributions regarding state-of-the-art AI/ML-based solutions for signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction 6G enabled software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The proposed edited book emphasis on the 6G network blended with Fog-IoT networks to introduce its applications and future perspectives that helps the researcher to apply this technique in their domain and it may also helpful to resolve the challenges and future opportunities with 6G networks.
Author: Agbotiname Lucky Imoize
Publisher: CRC Press
ISBN: 1000963268
Category : Technology & Engineering
Languages : en
Pages : 536
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Book Description
The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions. This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others. .
Author: Pandey, Binay Kumar
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 391
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Book Description
The advent of 6G technology introduces significant security challenges that must be addressed to ensure its safe and effective implementation. The increased complexity of 6G infrastructure, encompassing a vast array of devices and networks, expands the potential attack surface, making it more vulnerable to cyber threats. Privacy concerns are heightened with the massive data flow, necessitating stringent protection measures. These rapid developments are outpacing current educational frameworks, highlighting the need for updated programs to equip cybersecurity professionals with the skills to address these challenges. 6G Security Education and Multidisciplinary Implementation explores the critical intersection of technology, security, and education. It provides insights into the implementation of 6G technologies as well as frameworks for security education. Covering topics such as 6G education, learning experience, and privacy concerns, this book is a valuable resource for educators, academicians, scholars, security experts, post-graduate students, pre-service teachers, industry professionals, and researchers.
Author: Adwitiya Sinha
Publisher: CRC Press
ISBN: 0429671776
Category : Computers
Languages : en
Pages : 249
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Book Description
About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.
Author: Samiya Khan
Publisher: Academic Press
ISBN: 0323985394
Category : Technology & Engineering
Languages : en
Pages : 304
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Book Description
Extended Reality for Healthcare Systems: Recent Advances in Contemporary Research focuses on real world applications in medicine, also providing an overview of emerging technologies. The book includes case studies that break down the ways in which this technology has and can be used, while also taking readers through evidence, best practices and obstacles. Sections emphasize evidence, research-based practices and work. Content coverage includes Enhancing Medical Education with AR/VR, and XR: The Future of Surgery and Building Systems for Enhanced Health, and more. Readers will learn how to use this technology to improve existing systems by enhancing precision and reducing costs. Other sections cover extended reality in elderly care and remote monitoring of patients, building systems for enhanced health, including telehealth and telepsychiatry, using AR and VR in medical education, and designing technology for use in telesurgery. - Offers advice on the development of state-of-the-art tech-driven healthcare systems and technologies for improving the quality of healthcare - Focuses on healthcare solutions that are inclusive and cost-effective - Discusses the future, limitations and challenges associated with the use and adoption of XR for healthcare
Author: Mariella Särestöniemi
Publisher: Springer Nature
ISBN: 3031590805
Category :
Languages : en
Pages : 451
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Book Description
Author: Vania V. Estrela
Publisher: CRC Press
ISBN: 1000954323
Category : Computers
Languages : en
Pages : 399
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Book Description
The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems’ design practices and computational intelligence tactics for medical usage. The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.
Author: Agbotiname Lucky Imoize
Publisher: Elsevier
ISBN: 0443138966
Category : Computers
Languages : en
Pages : 459
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Book Description
Federated Learning for Digital Healthcare Systems critically examines the key factors that contribute to the problem of applying machine learning in healthcare systems and investigates how federated learning can be employed to address the problem. The book discusses, examines, and compares the applications of federated learning solutions in emerging digital healthcare systems, providing a critical look in terms of the required resources, computational complexity, and system performance. In the first section, chapters examine how to address critical security and privacy concerns and how to revamp existing machine learning models. In subsequent chapters, the book's authors review recent advances to tackle emerging efficient and lightweight algorithms and protocols to reduce computational overheads and communication costs in wireless healthcare systems. Consideration is also given to government and economic regulations as well as legal considerations when federated learning is applied to digital healthcare systems. - Provides insights into real-world scenarios of the design, development, deployment, application, management, and benefits of federated learning in emerging digital healthcare systems - Highlights the need to design efficient federated learning-based algorithms to tackle the proliferating security and patient privacy issues in digital healthcare systems - Reviews the latest research, along with practical solutions and applications developed by global experts from academia and industry
