Deep Learning In Smart Ehealth Systems

Author : Asma Channa
Publisher : Springer Nature
ISBN 13 : 3031450035
Total Pages : 102 pages
Book Rating : 4.37/5 ( download)

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Download or read book Deep Learning in Smart eHealth Systems written by Asma Channa and published by Springer Nature. This book was released on 2023-12-07 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the main benefits of this book is that it presents a comprehensive and innovative eHealth framework that leverages deep learning and IoT wearable devices for the evaluation of Parkinson's disease patients. This framework offers a new way to assess and monitor patients' motor deficits in a personalized and automated way, improving the efficiency and accuracy of diagnosis and treatment. Compared to other books on eHealth and Parkinson's disease, this book offers a unique perspective and solution to the challenges facing patients and healthcare providers. It combines state-of-the-art technology, such as wearable devices and deep learning algorithms, with clinical expertise to develop a personalized and efficient evaluation framework for Parkinson's disease patients. This book provides a roadmap for the integration of cutting-edge technology into clinical practice, paving the way for more effective and patient-centered healthcare. To understand this book, readers should have a basic knowledge of eHealth, IoT, deep learning, and Parkinson's disease. However, the book provides clear explanations and examples to make the content accessible to a wider audience, including researchers, practitioners, and students interested in the intersection of technology and healthcare.

Author : Hanen Idoudi
Publisher : Springer Nature
ISBN 13 : 3030149390
Total Pages : 239 pages
Book Rating : 4.90/5 ( download)

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Download or read book Smart Systems for E-Health written by Hanen Idoudi and published by Springer Nature. This book was released on 2021-04-15 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to review the recent advances in E-health technologies and applications. In particular, the book investigates the recent advancements in physical design of medical devices, signal processing and emergent wireless technologies for E-health. In a second part, novel security and privacy solutions for IoT-based E-health applications are presented. The last part of the book is focused on applications, data mining and data analytics for E-health using artificial intelligence and cloud infrastructure. E-health has been an evolving concept since its inception, due to the numerous technologies that can be adapted to offer new innovative and efficient E-health applications. Recently, with the tremendous advancement of wireless technologies, sensors and wearable devices and software technologies, new opportunities have arisen and transformed the E-health field. Moreover, with the expansion of the Internet of Things, and the huge amount of data that connected E-health devices and applications are generating, it is also mandatory to address new challenges related to the data management, applications management and their security. Through this book, readers will be introduced to all these concepts. This book is intended for all practitioners (industrial and academic) interested in widening their knowledge in wireless communications and embedded technologies applied to E-health, cloud computing, artificial intelligence and big data for E-health applications and security issues in E-health.

Author : Surbhi Bhatia
Publisher : Springer Nature
ISBN 13 : 3030670511
Total Pages : 323 pages
Book Rating : 4.11/5 ( download)

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Download or read book Intelligent Healthcare written by Surbhi Bhatia and published by Springer Nature. This book was released on 2021-07-02 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

Author : K. Murugeswari
Publisher : CRC Press
ISBN 13 : 1040021379
Total Pages : 309 pages
Book Rating : 4.78/5 ( download)

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Download or read book Deep Learning for Smart Healthcare written by K. Murugeswari and published by CRC Press. This book was released on 2024-05-15 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data. Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient’s medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process. Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.

Author : Akansha Singh
Publisher : John Wiley & Sons
ISBN 13 : 111979174X
Total Pages : 484 pages
Book Rating : 4.44/5 ( download)

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Download or read book Blockchain and Deep Learning for Smart Healthcare written by Akansha Singh and published by John Wiley & Sons. This book was released on 2024-01-04 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: BLOCKCHAIN and DEEP LEARNING for SMART HEALTHCARE The book discusses the popular use cases and applications of blockchain technology and deep learning in building smart healthcare. The book covers the integration of blockchain technology and deep learning for making smart healthcare systems. Blockchain is used for health record-keeping, clinical trials, patient monitoring, improving safety, displaying information, and transparency. Deep learning is also showing vast potential in the healthcare domain. With the collection of large quantities of patient records and data, and a trend toward personalized treatments. there is a great need for automated and reliable processing and analysis of health information. This book covers the popular use cases and applications of both the above-mentioned technologies in making smart healthcare. Audience Comprises professionals and researchers working in the fields of deep learning, blockchain technology, healthcare & medical informatics. In addition, as the book provides insights into the convergence of deep learning and blockchain technology in healthcare systems and services, medical practitioners as well as healthcare professionals will find this essential reading.

Author : Suneeta Satpathy
Publisher : CRC Press
ISBN 13 : 1000894932
Total Pages : 292 pages
Book Rating : 4.36/5 ( download)

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Download or read book Reconnoitering the Landscape of Edge Intelligence in Healthcare written by Suneeta Satpathy and published by CRC Press. This book was released on 2024-04-23 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revolution in healthcare as well as demand for efficient real-time healthcare services are driving the progression of edge computing, AI-mediated techniques, deep learning, and IoT applications for healthcare industries and cloud computing. Edge computing helps to meet the demand for newer and more sophisticated healthcare systems that are more personalized and that match the speed of modern life. With applications of edge computing, automated intelligence and intuitions are incorporated into existing healthcare analysis tools for identifying, forecasting, and preventing high-risk diseases. Reconnoitering the Landscape of Edge Intelligence in Healthcare provides comprehensive research on edge intelligence technology with the emphasis on application in the healthcare industry. It covers all the various areas of edge intelligence for data analysis in healthcare, looking at the emerging technologies such as AI-based techniques, machine learning, IoT, cloud computing, and deep learning with illustrations of the design, implementation, and management of smart and intelligent healthcare systems. Chapters showcase the advantages and highlights of the adoption of the intelligent edge models toward smart healthcare infrastructure. The book also addresses the increased need for a high level of medical data security while transferring real-time data to cloud-based architecture, a matter of prime concern for both patient and doctor. Topics include edge intelligence for wearable sensor technologies and their applications for health monitoring, the various edge computing techniques for disease prediction, e-health services and e-security solutions through IoT devices that aim to improve the quality of care for transgender patients, smart technology in ambient assisted living, the role of edge intelligence in limiting virus spread during pandemics, neuroscience in decoding and analysis of visual perception from the neural patterns and visual image reconstruction, and more. The technology addressed include energy aware cross-layer routing protocol (ECRP), OMKELM-IDS technique, graphical user interface (GUI), IOST (an ultra-fast, decentralized blockchain platform), etc. This volume will be helpful to engineering students, research scholars, and manufacturing industry professionals in the fields of engineering applications initiatives on AI, machine learning, and deep learning techniques for edge computing.

Author : Wason, Ritika
Publisher : IGI Global
ISBN 13 : 1799821021
Total Pages : 248 pages
Book Rating : 4.21/5 ( download)

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Download or read book Applications of Deep Learning and Big IoT on Personalized Healthcare Services written by Wason, Ritika and published by IGI Global. This book was released on 2020-02-07 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes. Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.

Author : Hassan, Ahdi
Publisher : IGI Global
ISBN 13 :
Total Pages : 372 pages
Book Rating : 4.04/5 ( download)

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Download or read book Pioneering Smart Healthcare 5.0 with IoT, Federated Learning, and Cloud Security written by Hassan, Ahdi and published by IGI Global. This book was released on 2024-02-14 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Om Prakash Jena
Publisher : CRC Press
ISBN 13 : 1000486796
Total Pages : 397 pages
Book Rating : 4.97/5 ( download)

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Download or read book Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems written by Om Prakash Jena and published by CRC Press. This book was released on 2022-05-18 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications. FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analytics This book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.

Author : Abdulmotaleb El Saddik
Publisher : Springer Nature
ISBN 13 : 3030278441
Total Pages : 254 pages
Book Rating : 4.41/5 ( download)

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Download or read book Connected Health in Smart Cities written by Abdulmotaleb El Saddik and published by Springer Nature. This book was released on 2019-12-03 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the theoretical foundations, fundamental applications and latest advances in various aspects of connected services for health information systems. The twelve chapters highlight state-of-the-art approaches, methodologies and systems for the design, development, deployment and innovative use of multisensory systems and tools for health management in smart city ecosystems. They exploit technologies like deep learning, artificial intelligence, augmented and virtual reality, cyber physical systems and sensor networks. Presenting the latest developments, identifying remaining challenges, and outlining future research directions for sensing, computing, communications and security aspects of connected health systems, the book will mainly appeal to academic and industrial researchers in the areas of health information systems, smart cities, and augmented reality.