Federated Learning And Ai For Healthcare 5 0
DOWNLOAD eBooks
Download Federated Learning And Ai For Healthcare 5 0 PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Federated Learning And Ai For Healthcare 5 0 book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Federated Learning And Ai For Healthcare 5 0
DOWNLOAD eBooks
Author : Hassan, Ahdi
language : en
Publisher: IGI Global
Release Date : 2023-12-18
Federated Learning And Ai For Healthcare 5 0 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 2023-12-18 with Medical categories.
The Healthcare sector is evolving with Healthcare 5.0, promising better patient care and efficiency. However, challenges like data security and analysis arise due to increased digitization. Federated Learning and AI for Healthcare 5.0 offers solutions, explaining cloud computing's role in managing data and advocating for security measures. It explores federated learning's use in maintaining data privacy during analysis, presenting practical cases for implementation. The book also addresses emerging tech like quantum computing and blockchain-based services, envisioning an innovative Healthcare 5.0. It empowers healthcare professionals, IT experts, and data scientists to leverage these technologies for improved patient care and system efficiency, making Healthcare 5.0 secure and patient centric.
Federated Learning For Internet Of Medical Things
DOWNLOAD eBooks
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 And Privacy Preserving In Healthcare Ai
DOWNLOAD eBooks
Author : Umesh Kumar Lilhore
language : en
Publisher:
Release Date : 2024
Federated Learning And Privacy Preserving In Healthcare Ai written by Umesh Kumar Lilhore and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
Pioneering Smart Healthcare 5 0 With Iot Federated Learning And Cloud Security
DOWNLOAD eBooks
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.
Federated Learning For Digital Healthcare Systems
DOWNLOAD eBooks
Author : Agbotiname Lucky Imoize
language : en
Publisher: Academic Press
Release Date : 2024-06-01
Federated Learning For Digital Healthcare Systems written by Agbotiname Lucky Imoize and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-01 with Computers categories.
Modern healthcare systems facilitate the collection of critical medical data for statistical evaluation and inference using machine learning, however, the application of ML in healthcare data analytics has not been fully exploited due to the proliferation of security and privacy concerns. The potential of machine learning is also limited by insufficient data, posing a significant impediment to the transition from research to clinical practice. Over the past five years, Federated Learning has been introduced to strengthen the performance of machine learning. In federated learning, artificial intelligence models are trained with data from multiple sources. In this case, data anonymity, security, privacy and integrity are maintained, thus removing potential barriers to data sharing. Additionally, models trained by federated learning have shown favorable progress in the agreement with models obtained from centrally hosted data sets. A successfully implemented federated learning model can produce unbiased decisions which facilitate better-informed decision making in precision medicine. 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, 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.
Federated Learning Systems
DOWNLOAD eBooks
Author : Muhammad Habib ur Rehman
language : en
Publisher: Springer Nature
Release Date : 2021-06-11
Federated Learning Systems written by Muhammad Habib ur Rehman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Technology & Engineering categories.
This book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.
Handbook On Federated Learning
DOWNLOAD eBooks
Author : Saravanan Krishnan
language : en
Publisher: CRC Press
Release Date : 2024-01-09
Handbook On Federated Learning written by Saravanan Krishnan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-09 with Computers categories.
Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects.
Explainable Ai In Healthcare
DOWNLOAD eBooks
Author : Mehul S Raval
language : en
Publisher: CRC Press
Release Date : 2023-07-17
Explainable Ai In Healthcare written by Mehul S Raval and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-17 with Medical categories.
This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care
Trends Of Artificial Intelligence And Big Data For E Health
DOWNLOAD eBooks
Author : Houneida Sakly
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Trends Of Artificial Intelligence And Big Data For E Health written by Houneida Sakly and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Medical categories.
This book aims to present the impact of Artificial Intelligence (AI) and Big Data in healthcare for medical decision making and data analysis in myriad fields including Radiology, Radiomics, Radiogenomics, Oncology, Pharmacology, COVID-19 prognosis, Cardiac imaging, Neuroradiology, Psychiatry and others. This will include topics such as Artificial Intelligence of Thing (AIOT), Explainable Artificial Intelligence (XAI), Distributed learning, Blockchain of Internet of Things (BIOT), Cybersecurity, and Internet of (Medical) Things (IoTs). Healthcare providers will learn how to leverage Big Data analytics and AI as methodology for accurate analysis based on their clinical data repositories and clinical decision support. The capacity to recognize patterns and transform large amounts of data into usable information for precision medicine assists healthcare professionals in achieving these objectives. Intelligent Health has the potential to monitor patients at risk with underlying conditions and track their progress during therapy. Some of the greatest challenges in using these technologies are based on legal and ethical concerns of using medical data and adequately representing and servicing disparate patient populations. One major potential benefit of this technology is to make health systems more sustainable and standardized. Privacy and data security, establishing protocols, appropriate governance, and improving technologies will be among the crucial priorities for Digital Transformation in Healthcare.
Trustworthy Machine Learning For Healthcare
DOWNLOAD eBooks
Author : Hao Chen
language : en
Publisher: Springer Nature
Release Date : 2023-07-30
Trustworthy Machine Learning For Healthcare written by Hao Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-30 with Computers categories.
This book constitutes the proceedings of First International Workshop, TML4H 2023, held virtually, in May 2023. The 16 full papers included in this volume were carefully reviewed and selected from 30 submissions. The goal of this workshop is to bring together experts from academia, clinic, and industry with an insightful vision of promoting trustworthy machine learning in healthcare in terms of scalability, accountability, and explainability.