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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
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Book Description
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: 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: Vania V. Estrela
Publisher: CRC Press
ISBN: 1000954390
Category : Computers
Languages : en
Pages : 492
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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: Amit Kumar Tyagi
Publisher: John Wiley & Sons
ISBN: 139425833X
Category : Technology & Engineering
Languages : en
Pages : 470
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Book Description
A comprehensive reference on 6G wireless technologies, covering applications, hardware, security and privacy concerns, existing challenges, analytics methods, and much more 6G-Enabled Technologies for Next Generation delivers a thorough overview of the emerging sixth generation of wireless technology, presenting critical challenges of implementing 6G technologies including spectrum allocation, energy efficiency, security, interoperability, and more. Explaining ways we can use technologies to ensure a sustainable environment through renewable energy and a resilient industry, this book covers the applications and use cases such as smart grid, IoT, smart manufacturing, addressing security and privacy issues with privacy-preserving techniques and authentication control mechanisms. This book discusses the analytical methods used to study the performance of 6G technologies, covering simulation techniques, performance metrics, and predictive modeling. Introducing the core principles of 6G technology, including the advantages and disadvantages of the technology and how wireless communications have evolved, energy-efficient hardware and the different types of green communication technologies is explained. Many case studies are included in this book with a detailed explanation. Written by a team of experienced researchers, this book discusses: Terahertz (ThZ) communication, massive MIMO and beamforming, quantum communication, bandwidth management, and ultra-dense networks and small cell deployments Smart cities, telemedicine, and autonomous vehicles and schemes for waveform design, modulation, error correction, and advanced coding and modulation Sensor networks, edge computing and mobile cloud computing, and spatial, quantum, and dew computing Quantum-safe encryption, privacy-preserving technologies and techniques, threats and vulnerabilities, and authentication and access control mechanisms Network slicing and service differentiation, multi-connectivity and heterogeneous networks, and wireless power transfer 6G-Enabled Technologies for Next Generation is a comprehensive, up-to-date reference for students, academics, and researchers, along with professionals in the telecommunications field.
Author: Amit Kumar Tyagi
Publisher: John Wiley & Sons
ISBN: 139430353X
Category : Computers
Languages : en
Pages : 692
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Book Description
The book uniquely explores the fundamentals of blockchain and digital twin technologies and their uses in smart cities. In the previous decade, many governments explored artificial intelligence, digital twin, and blockchain, and their roles in smart cities. This book discusses the convergence of two transformative technologies, digital twin and blockchain, to address urban challenges and propel the development of smarter, more sustainable cities. This convergence empowers cities to create real-time replicas of urban environments (digital twins) and secure, transparent data management (blockchain) to improve city planning, management, and civic services. In this application, the concept of a digital twin involves creating a virtual, data-driven replica of a city or specific urban systems, such as transportation, energy, or infrastructure. This digital twin mirrors the real world, gathering data from various sensors, IoT devices, and other sources to provide a holistic view of the city’s operations. Furthermore, blockchain technology offers a decentralized and tamper-resistant ledger for securely storing and managing data. In the context of smart cities, blockchain can ensure data integrity, privacy, and transparency, enabling trust and collaboration among various stakeholders. This book covers many important topics, including real-time city modeling; data security and the trustworthy storage of sensitive urban data; transparent governance to facilitate accountable governance and decision-making processes in smart cities; improved city services; disaster resilience (by providing insights into vulnerabilities and efficient resource allocation during crises); sustainable urban planning that optimizes resource allocation, reduces energy consumption, and minimizes environmental impact, which fosters sustainable development; citizen engagement; and much more. This book will not only provide information about more efficient, resilient, and sustainable urban environments, but it also empowers citizens to be active participants in shaping the future of their cities. By converging these technologies, cities can overcome existing challenges, encourage innovation, and create more livable, connected, and responsive urban spaces. Audience This book has a wide audience in computer science, artificial intelligence, and information technology as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and government/city policymakers working on smart cities, the circular economy, clean tech investors, urban decision-makers, and environmental professionals.
Author: Mariella Särestöniemi
Publisher: Springer Nature
ISBN: 3031590805
Category :
Languages : en
Pages : 451
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Book Description
Author: Agbotiname Lucky Imoize
Publisher: CRC Press
ISBN: 1000963187
Category : Computers
Languages : en
Pages : 508
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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: Athina Bourdena
Publisher: Springer Nature
ISBN: 3031585275
Category :
Languages : en
Pages : 245
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Book Description
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
