Digitization of Healthcare Data using Blockchain

Digitization of Healthcare Data using Blockchain PDF Author: T. Poongodi
Publisher: John Wiley & Sons
ISBN: 1119792711
Category : Computers
Languages : en
Pages : 324

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Book Description
DIGITIZATION OF HEALTHCARE DATA USING BLOCKCHAIN The book gives a detailed description of the integration of blockchain technology for Electronic Health Records and provides the research challenges to consider in various disciplines such as supply chain, drug discovery, and data management. The aim of the book is to investigate the concepts of blockchain technology and its association with the recent development and advancements in the medical field. Moreover, it focuses on the integration of workflow strategies like NLP, and AI which could be adopted for boosting the clinical documentation and electronic healthcare records (EHR) usage by bringing down the physician EHR data entry. Also, the book covers the usage of smart contracts for securing patient records. Digitization of Healthcare Data Using Blockchain presents the practical implementations that deal with developing a web framework for building highly usable healthcare applications, a simple blockchain-powered EHR system. Audience Researchers in information technology, artificial intelligence, electronics engineering, medical informatics, as well as policymakers and healthcare providers and management systems.

Blockchain and Health

Blockchain and Health PDF Author: Jan Veuger
Publisher: Nova Science Publishers
ISBN: 9781685072605
Category : Computers
Languages : en
Pages : 312

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Book Description
"The secure storage of medical records is vital to any healthcare system. Relying solely on centralized servers increases the likelihood of sensitive information going public. Transparency and increased security of Blockchain technology make it an ideal platform for storing medical records. Patients can safely store their privacy-sensitive information by securing their data on a Blockchain using cryptography. This enables them to share their medical information with any healthcare institution with their approval. The healthcare system is currently very fragmented, but if all users were to use a secure global database, the flow of information between them would be much faster. A great advantage of a global database is that clients do not have to tell their story every time. A medical specialist, for example, can see exactly what a patient has been through and what treatments and examinations have taken place. The information is also available in real time to the healthcare professional the client has indicated to have access to his file. A new revolution is taking place that is clearly different from the third industrial revolution (Internet, communication and globalization). This fourth industrial revolution involves a fusion of technologies such as biotechnology, nanotechnology, artificial intelligence, robotics, the Internet of Things, cloud computing and Blockchain. Our healthcare society is also changing fundamentally, also under the influence of COVID-19. With this book in three chapters, we present the impact of Blockchain and digitization in healthcare with (1) a systematic literature review om implementing blockchain solutions in health care and organizational consequences, (2) Blockchain in health care and (3) transformation of elderly care and impact of digitalization"--

Health 4.0: How Virtualization and Big Data are Revolutionizing Healthcare

Health 4.0: How Virtualization and Big Data are Revolutionizing Healthcare PDF Author: Christoph Thuemmler
Publisher: Springer
ISBN: 3319476173
Category : Technology & Engineering
Languages : en
Pages : 257

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Book Description
This book describes how the creation of new digital services—through vertical and horizontal integration of data coming from sensors on top of existing legacy systems—that has already had a major impact on industry is now extending to healthcare. The book describes the fourth industrial revolution (i.e. Health 4.0), which is based on virtualization and service aggregation. It shows how sensors, embedded systems, and cyber-physical systems are fundamentally changing the way industrial processes work, their business models, and how we consume, while also affecting the health and care domains. Chapters describe the technology behind the shift of point of care to point of need and away from hospitals and institutions; how care will be delivered virtually outside hospitals; that services will be tailored to individuals rather than being designed as statistical averages; that data analytics will be used to help patients to manage their chronic conditions with help of smart devices; and that pharmaceuticals will be interactive to help prevent adverse reactions. The topics presented will have an impact on a variety of healthcare stakeholders in a continuously global and hyper-connected world. · Presents explanations of emerging topics as they relate to e-health, such as Industry 4.0, Precision Medicine, Mobile Health, 5G, Big Data, and Cyber-physical systems; · Provides overviews of technologies in addition to possible application scenarios and market conditions; · Features comprehensive demographic and statistic coverage of Health 4.0 presented in a graphical manner.

Capturing Social and Behavioral Domains and Measures in Electronic Health Records

Capturing Social and Behavioral Domains and Measures in Electronic Health Records PDF Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309312450
Category : Medical
Languages : en
Pages : 287

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Book Description
Determinants of health - like physical activity levels and living conditions - have traditionally been the concern of public health and have not been linked closely to clinical practice. However, if standardized social and behavioral data can be incorporated into patient electronic health records (EHRs), those data can provide crucial information about factors that influence health and the effectiveness of treatment. Such information is useful for diagnosis, treatment choices, policy, health care system design, and innovations to improve health outcomes and reduce health care costs. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2 identifies domains and measures that capture the social determinants of health to inform the development of recommendations for the meaningful use of EHRs. This report is the second part of a two-part study. The Phase 1 report identified 17 domains for inclusion in EHRs. This report pinpoints 12 measures related to 11 of the initial domains and considers the implications of incorporating them into all EHRs. This book includes three chapters from the Phase 1 report in addition to the new Phase 2 material. Standardized use of EHRs that include social and behavioral domains could provide better patient care, improve population health, and enable more informative research. The recommendations of Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2 will provide valuable information on which to base problem identification, clinical diagnoses, patient treatment, outcomes assessment, and population health measurement.

Metaheuristics for Machine Learning

Metaheuristics for Machine Learning PDF Author: Kanak Kalita
Publisher: John Wiley & Sons
ISBN: 1394233930
Category : Computers
Languages : en
Pages : 272

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Book Description
METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-inspired optimization in machine learning and presents a comprehensive guide to cutting-edge algorithms, interdisciplinary insights, and real-world applications. The field of metaheuristic optimization algorithms is experiencing rapid growth, both in academic research and industrial applications. These nature-inspired algorithms, which draw on phenomena like evolution, swarm behavior, and neural systems, have shown remarkable efficiency in solving complex optimization problems. With advancements in machine learning and artificial intelligence, the application of metaheuristic optimization techniques has expanded, demonstrating significant potential in optimizing machine learning models, hyperparameter tuning, and feature selection, among other use-cases. In the industrial landscape, these techniques are becoming indispensable for solving real-world problems in sectors ranging from healthcare to cybersecurity and sustainability. Businesses are incorporating metaheuristic optimization into machine learning workflows to improve decision-making, automate processes, and enhance system performance. As the boundaries of what is computationally possible continue to expand, the integration of metaheuristic optimization and machine learning represents a pioneering frontier in computational intelligence, making this book a timely resource for anyone involved in this interdisciplinary field. Metaheuristics for Machine Learning: Algorithms and Applications serves as a comprehensive guide to the intersection of nature-inspired optimization and machine learning. Authored by leading experts, this book seamlessly integrates insights from computer science, biology, and mathematics to offer a panoramic view of the latest advancements in metaheuristic algorithms. You’ll find detailed yet accessible discussions of algorithmic theory alongside real-world case studies that demonstrate their practical applications in machine learning optimization. Perfect for researchers, practitioners, and students, this book provides cutting-edge content with a focus on applicability and interdisciplinary knowledge. Whether you aim to optimize complex systems, delve into neural networks, or enhance predictive modeling, this book arms you with the tools and understanding you need to tackle challenges efficiently. Equip yourself with this essential resource and navigate the ever-evolving landscape of machine learning and optimization with confidence. Audience The book is aimed at a broad audience encompassing researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics. The detailed but accessible content makes it a must-have for both academia and industry professionals interested in the optimization aspects of machine learning algorithms.

Integration of AI, Quantum Computing, and Semiconductor Technology

Integration of AI, Quantum Computing, and Semiconductor Technology PDF Author: Mishra, Brojo Kishore
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 534

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Book Description
The integration of artificial intelligence (AI), quantum computing, and semiconductor technology offers improved innovation to redefine computational power and capabilities. As AI drives advances in machine learning and data processing, quantum computing revolutionizes problem-solving with its ability to handle complex calculations at improved speeds. Advancements in semiconductor technology push the limits of processing efficiency and miniaturization. Continued exploration on this convergence may accelerate breakthroughs in various fields such as cryptography, material science, and healthcare. Integration of AI, Quantum Computing, and Semiconductor Technology explores the intersection of artificial intelligence (AI) and semiconductor technology within the context of quantum computing. It offers a comprehensive analysis of the current advancements, challenges, and potential applications resulting from this convergence. This book covers topics such as cyber security, healthcare monitoring, and machine learning, and is a useful resource for computer engineers, energy scientists, business owners, healthcare administrators, environmental scientists, academicians, and researchers.

Artificial Intelligence for Sustainable Applications

Artificial Intelligence for Sustainable Applications PDF Author: K. Umamaheswari
Publisher: John Wiley & Sons
ISBN: 139417523X
Category : Computers
Languages : en
Pages : 306

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Book Description
ARTIFICAL INTELLIGENCE for SUSTAINABLE APPLICATIONS The objective of this book is to leverage the significance of artificial intelligence in achieving sustainable solutions using interdisciplinary research through innovative ideas. With the advent of recent technologies, the demand for Information and Communication Technology (ICT)-based applications such as artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), health care, data analytics, augmented reality/virtual reality, cyber-physical systems, and future generation networks, has increased drastically. In recent years, artificial intelligence has played a more significant role in everyday activities. While AI creates opportunities, it also presents greater challenges in the sustainable development of engineering applications. Therefore, the association between AI and sustainable applications is an essential field of research. Moreover, the applications of sustainable products have come a long way in the past few decades, driven by social and environmental awareness, and abundant modernization in the pertinent field. New research efforts are inevitable in the ongoing design of sustainable applications, which makes the study of communication between them a promising field to explore. This book highlights the recent advances in AI and its allied technologies with a special focus on sustainable applications. It covers theoretical background, a hands-on approach, and real-time use cases with experimental and analytical results. Audience AI researchers as well as engineers in information technology and computer science.

AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management

AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management PDF Author: Kautish, Sandeep
Publisher: IGI Global
ISBN: 1668444070
Category : Computers
Languages : en
Pages : 294

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Book Description
Multiple-criteria decision making, including multiple rule-based decision making, multiple-objective decision making, and multiple-attribute decision making, is used by clinical decision makers to analyze healthcare issues from various perspectives. In practical healthcare cases, semi-structured and unstructured decision-making issues involve multiple criteria that may conflict with each other. Thus, the use of multiple-criteria decision making is a promising source of practical solutions for such problems. AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management investigates the contributions of practical multiple-criteria decision analysis applications and cases for healthcare management. The book also considers the best practices and tactics for utilizing multiple-criteria decision making to ensure the technology is utilized appropriately. Covering key topics such as fuzzy data, augmented reality, blockchain, and data transmission, this reference work is ideal for computer scientists, healthcare professionals, nurses, policymakers, researchers, scholars, academicians, practitioners, educators, and students.

Integrating AI in IoT Analytics on the Cloud for Healthcare Applications

Integrating AI in IoT Analytics on the Cloud for Healthcare Applications PDF Author: Jeya Mala, D.
Publisher: IGI Global
ISBN: 1799891348
Category : Computers
Languages : en
Pages : 312

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Book Description
Internet of things (IoT) applications employed for healthcare generate a huge amount of data that needs to be analyzed to produce the expected reports. To accomplish this task, a cloud-based analytical solution is ideal in order to generate faster reports in comparison to the traditional way. Given the current state of the world in which every day IoT devices are developed to provide healthcare solutions, it is essential to consider the mechanisms used to collect and analyze the data to provide thorough reports. Integrating AI in IoT Analytics on the Cloud for Healthcare Applications applies artificial intelligence (AI) in edge analytics for healthcare applications, analyzes the impact of tools and techniques in edge analytics for healthcare, and discusses security solutions for edge analytics in healthcare IoT. Covering topics such as data analytics and next generation healthcare systems, it is ideal for researchers, academicians, technologists, IT specialists, data scientists, healthcare industries, IoT developers, data security analysts, educators, and students.

Convergence of Deep Learning in Cyber-IoT Systems and Security

Convergence of Deep Learning in Cyber-IoT Systems and Security PDF Author: Rajdeep Chakraborty
Publisher: John Wiley & Sons
ISBN: 111985766X
Category : Computers
Languages : en
Pages : 485

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Book Description
CONVERGENCE OF DEEP LEARNING IN CYBER-IOT SYSTEMS AND SECURITY In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. The main goal of this book is to bring to the fore unconventional cryptographic methods to provide cyber security, including cyber-physical system security and IoT security through deep learning techniques and analytics with the study of all these systems. This book provides innovative solutions and implementation of deep learning-based models in cyber-IoT systems, as well as the exposed security issues in these systems. The 20 chapters are organized into four parts. Part I gives the various approaches that have evolved from machine learning to deep learning. Part II presents many innovative solutions, algorithms, models, and implementations based on deep learning. Part III covers security and safety aspects with deep learning. Part IV details cyber-physical systems as well as a discussion on the security and threats in cyber-physical systems with probable solutions. Audience Researchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity and cryptography.