Federated Learning For Internet Of Medical Things
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Federated Learning For Internet Of Medical Things
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Author : Pronaya Bhattacharya
language : en
Publisher: CRC Press
Release Date : 2023-06-16
Federated Learning For Internet Of Medical Things written by Pronaya Bhattacharya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-16 with Computers categories.
This book intends to present emerging Federated Learning (FL)-based architectures, frameworks, and models in Internet of Medical Things (IoMT) applications. It intends to build on the basics of the healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing. Once IoMT is presented, the book shifts towards the proposal of privacy-preservation in IoMT, and explains how FL presents a viable solution to these challenges. The claims are supported through lucid illustrations, tables, and examples that present effective and secured FL schemes, simulations, and practical discussion on use-case scenarios in a simple manner. The book intends to create opportunities for healthcare communities to build effective FL solutions around the presented themes, and to support work in related areas that will benefit from reading the book. It also intends to present breakthroughs and foster innovation in FL-based research, specifically in the IoMT domain. The emphasis of this book is on understanding the contributions of IoMT to healthcare analytics, and its aim is to provide insights including evolution, research directions, challenges, and the way to empower healthcare services through federated learning. The book also intends to cover the ethical and social issues around the recent advancements in the field of decentralized Artificial Intelligence. The book is mainly intended for undergraduates, post-graduates, researchers, and healthcare professionals who wish to learn FL-based solutions right from scratch, and build practical FL solutions in different IoMT verticals.
Federated Learning For Internet Of Medical Things
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Author : Pronaya Bhattacharya
language : en
Publisher: CRC Press
Release Date : 2023-06-16
Federated Learning For Internet Of Medical Things written by Pronaya Bhattacharya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-16 with Computers categories.
This book intends to present emerging Federated Learning (FL)-based architectures, frameworks, and models in Internet of Medical Things (IoMT) applications. It intends to build on the basics of the healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing. Once IoMT is presented, the book shifts towards the proposal of privacy-preservation in IoMT, and explains how FL presents a viable solution to these challenges. The claims are supported through lucid illustrations, tables, and examples that present effective and secured FL schemes, simulations, and practical discussion on use-case scenarios in a simple manner. The book intends to create opportunities for healthcare communities to build effective FL solutions around the presented themes, and to support work in related areas that will benefit from reading the book. It also intends to present breakthroughs and foster innovation in FL-based research, specifically in the IoMT domain. The emphasis of this book is on understanding the contributions of IoMT to healthcare analytics, and its aim is to provide insights including evolution, research directions, challenges, and the way to empower healthcare services through federated learning. The book also intends to cover the ethical and social issues around the recent advancements in the field of decentralized Artificial Intelligence. The book is mainly intended for undergraduates, post-graduates, researchers, and healthcare professionals who wish to learn FL-based solutions right from scratch, and build practical FL solutions in different IoMT verticals.
Federated Learning For Digital Healthcare Systems
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Author : Agbotiname Lucky Imoize
language : en
Publisher: Elsevier
Release Date : 2024-06-10
Federated Learning For Digital Healthcare Systems written by Agbotiname Lucky Imoize and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-10 with Computers categories.
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
Internet Of Medical Things
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Author : D. Jude Hemanth
language : en
Publisher: Springer Nature
Release Date : 2021-04-13
Internet Of Medical Things written by D. Jude Hemanth and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-13 with Technology & Engineering categories.
This book looks at the growing segment of Internet of Things technology (IoT) known as Internet of Medical Things (IoMT), an automated system that aids in bridging the gap between isolated and rural communities and the critical healthcare services that are available in more populated and urban areas. Many technological aspects of IoMT are still being researched and developed, with the objective of minimizing the cost and improving the performance of the overall healthcare system. This book focuses on innovative IoMT methods and solutions being developed for use in the application of healthcare services, including post-surgery care, virtual home assistance, smart real-time patient monitoring, implantable sensors and cameras, and diagnosis and treatment planning. It also examines critical issues around the technology, such as security vulnerabilities, IoMT machine learning approaches, and medical data compression for lossless data transmission and archiving. Internet of Medical Things is a valuable reference for researchers, students, and postgraduates working in biomedical, electronics, and communications engineering, as well as practicing healthcare professionals.
Federated Learning
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Author : Jayakrushna Sahoo
language : en
Publisher: CRC Press
Release Date : 2024-09-20
Federated Learning written by Jayakrushna Sahoo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-20 with Computers categories.
This new book provides an in-depth understanding of federated learning, a new and increasingly popular learning paradigm that decouples data collection and model training via multi-party computation and model aggregation. The volume explores how federated learning integrates AI technologies, such as blockchain, machine learning, IoT, edge computing, and fog computing systems, allowing multiple collaborators to build a robust machine-learning model using a large dataset. It highlights the capabilities and benefits of federated learning, addressing critical issues such as data privacy, data security, data access rights, and access to heterogeneous data. The volume first introduces the general concepts of machine learning and then summarizes the federated learning system setup and its associated terminologies. It also presents a basic classification of FL, the application of FL for various distributed computing scenarios, an integrated view of applications of software-defined networks, etc. The book also explores the role of federated learning in the Internet of Medical Things systems as well. The book provides a pragmatic analysis of strategies for developing a communication-efficient federated learning system. It also details the applicability of blockchain with federated learning on IoT-based systems. It provides an in-depth study of FL-based intrusion detection systems, discussing their taxonomy and functioning and showcasing their superiority over existing systems. The book is unique in that it evaluates the privacy and security aspects in federated learning. The volume presents a comprehensive analysis of some of the common challenges, proven threats, and attack strategies affecting FL systems. Special coverage on protected shot-based federated learning for facial expression recognition is also included. This comprehensive book, Federated Learning: Principles, Paradigms, and Applications, will enable research scholars, information technology professionals, and distributed computing engineers to understand various aspects of federated learning concepts and computational techniques for real-life implementation.
Federated Learning Techniques And Its Application In The Healthcare Industry
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Author : H L Gururaj
language : en
Publisher: World Scientific
Release Date : 2024-05-28
Federated Learning Techniques And Its Application In The Healthcare Industry written by H L Gururaj and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-28 with Computers categories.
Federated Learning is currently an emerging technology in the field of machine learning. Federated Learning is a structure which trains a centralized model for a given assignment, where the data is de-centralized across different edge devices or servers. This enables preservation of the confidentiality of data on various edge devices, as only the updated outcomes of the models are shared with the centralized model. This means the data can remain on each edge device, while we can still train a model using that data.Federated Learning has greatly increased the potential to transmute data in the healthcare industry, enabling healthcare professionals to improve treatment of patients.This book comprises chapters on applying Federated models in the field of healthcare industry.Federated Learning mainly concentrates on securing the privacy of data by training local data in a shared global model without putting the training data in a centralized location. The importance of federated learning lies in its innumerable uses in health care that ranges from maintaining the privacy of raw data of the patients, discover clinically alike patients, forecasting hospitalization due to cardiac events impermanence and probable solutions to the same. The goal of this edited book is to provide a reference guide to the theme.
Federated Learning And Privacy Preserving In Healthcare Ai
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Author : Lilhore, Umesh Kumar
language : en
Publisher: IGI Global
Release Date : 2024-05-02
Federated Learning And Privacy Preserving In Healthcare Ai written by Lilhore, Umesh Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-02 with Medical categories.
The use of artificial intelligence (AI) in data-driven medicine has revolutionized healthcare, presenting practitioners with unprecedented tools for diagnosis and personalized therapy. However, this progress comes with a critical concern: the security and privacy of sensitive patient data. As healthcare increasingly leans on AI, the need for robust solutions to safeguard patient information has become more pressing than ever. Federated Learning and Privacy-Preserving in Healthcare AI emerges as the definitive solution to balancing medical progress with patient data security. This carefully curated volume not only outlines the challenges of federated learning but also provides a roadmap for implementing privacy-preserving AI systems in healthcare. By decentralizing the training of AI models, federated learning mitigates the risks associated with centralizing patient data, ensuring that critical information never leaves its original location. Aimed at healthcare professionals, AI experts, policymakers, and academics, this book not only delves into the technical aspects of federated learning but also fosters a collaborative approach to address the multifaceted challenges at the intersection of healthcare and AI.
Pioneering Smart Healthcare 5 0 With Iot Federated Learning And Cloud Security
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Author : Hassan, Ahdi
language : en
Publisher: IGI Global
Release Date : 2024-02-14
Pioneering Smart Healthcare 5 0 With Iot Federated Learning And Cloud Security written by Hassan, Ahdi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-14 with Medical categories.
The Healthcare sector is experiencing a mindset change with the advent of Healthcare 5.0, bringing forth improved patient care and system efficiency. However, this transformation poses significant challenges. The growing digitization of healthcare systems raises concerns about the security and privacy of patient data, making seamless data sharing and collaboration increasingly complex tasks. Additionally, as the volume of healthcare data expands exponentially, efficient handling and analysis become vital for optimizing healthcare delivery and patient outcomes. Addressing these multifaceted issues is crucial for healthcare professionals, IT experts, data scientists, and researchers seeking to fully harness the potential of Healthcare 5.0. Pioneering Smart Healthcare 5.0 with IoT, Federated Learning, and Cloud Security presents a comprehensive solution to the pressing challenges in the digitalized healthcare industry. This research book dives into the principles of Healthcare 5.0 and explores practical implementation through cloud computing, data analytics, and federated learning. Readers will gain profound insights into the role of cloud computing in managing vast amounts of healthcare data, such as electronic health records and real-time analytics. Cloud-based frameworks, architectures, and relevant use cases are explored to optimize healthcare delivery and improve patient outcomes.
Interpretable Cognitive Internet Of Things For Healthcare
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Author : Utku Kose
language : en
Publisher: Springer Nature
Release Date : 2023-06-26
Interpretable Cognitive Internet Of Things For Healthcare written by Utku Kose and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-26 with Technology & Engineering categories.
This book presents research on how interpretable cognitive IoT can work to help with the massive amount of data in the healthcare industry. The authors give importance to IoT systems with intense machine learning features; this ensures the scope corresponds to use of cognitive IoT for understanding, reasoning, and learning from medical data. The authors discuss the interpretability of an intelligent system and its trustworthiness as a smart tool in the context of massive healthcare applications. As a whole, book combines three important topics: massive data, cognitive IoT, and interpretability. Topics include health data analytics for cognitive IoT, usability evaluation of cognitive IoT for healthcare, interpretable cognitive IoT for health robotics, and wearables in the context of IoT for healthcare. The book acts as a useful reference work for a wide audience including academicians, scientists, students, and professionals.
Intelligent Healthcare
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Author : Chinmay Chakraborty
language : en
Publisher: Springer Nature
Release Date : 2022-06-02
Intelligent Healthcare written by Chinmay Chakraborty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-02 with Medical categories.
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 provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors. Main Features: Ø Immersive technologies in healthcare Ø Internet of medical things Ø Federated learning algorithms Ø Explainable AI in Pervasive Healthcare Ø New management principles using biomedical data Ø Secured healthcare management systems This book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue.
