› › Blockchain And Machine Learning For E Healthcare Systems

Blockchain and Machine Learning for e-Healthcare Systems

Author : Balusamy Balamurugan

Publisher : Institution of Engineering and Technology

Page : 480 pages

File Size : 13,52 MB

Release : 2020-11-13

Category : Computers

ISBN : 1839531142

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Book Description

Blockchain and machine learning technologies can mitigate healthcare issues such as slow access to medical data, poor system interoperability, lack of patient agency, and data quality and quantity for medical research. Blockchain technology facilitates and secures the storage of information in such a way that doctors can see a patient's entire medical history, but researchers see only statistical data instead of any personal information. Machine learning can make use of this data to notice patterns and give accurate predictions, providing more support for the patients and also in research related fields where there is a need for accurate data to predict credible results.



Digital Health Transformation with Blockchain and Artificial Intelligence

Author : Chinmay Chakraborty

Publisher : CRC Press

Page : 370 pages

File Size : 46,19 MB

Release : 2022-05-10

Category : Computers

ISBN : 1000580946

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Book Description

The book Digital Health Transformation with Blockchain and Artificial Intelligence covers the global digital revolution in the field of healthcare sector. The population has been overcoming the COVID-19 period; therefore, we need to establish intelligent digital healthcare systems using various emerging technologies like Blockchain and Artificial Intelligence. Internet of Medical Things is the technological revolution that has included the element of "smartness" in the healthcare industry and also identifying, monitoring, and informing service providers about the patient’s clinical information with faster delivery of care services. This book highlights the important issues i.e. (a) How Internet of things can be integrated with the healthcare ecosystem for better diagnostics, monitoring, and treatment of the patients, (b) Artificial Intelligence for predictive and preventive healthcare systems, (c) Blockchain for managing healthcare data to provide transparency, security, and distributed storage, and (d) Effective remote diagnostics and telemedicine approach for developing smart care. The book encompasses chapters belong to the blockchain, Artificial Intelligence, and Big health data technologies. Features: Blockchain and internet of things in healthcare systems Secure Digital Health Data Management in Internet of Things Public Perception towards AI-Driven Healthcare Security, privacy issues and challenges in adoption of smart digital healthcare Big data analytics and Internet of things in the pandemic era Clinical challenges for digital health revolution Artificial intelligence for advanced healthcare Future Trajectory of Healthcare with Artificial Intelligence 9 Parkinson disease pre-diagnosis using smart technologies Emerging technologies to combat the COVID-19 Machine Learning and Internet of Things in Digital Health Transformation Effective Remote Healthcare and Telemedicine Approaches Legal implication of blockchain technology in public health This Book on "Digital Health Transformation with Blockchain and Artificial Intelligence" aims at promoting and facilitating exchanges of research knowledge and findings across different disciplines on the design and investigation of secured healthcare data analytics. It can also be used as a textbook for a Masters course in security and biomedical engineering. This book will also present new methods for the medical data analytics, blockchain technology, and diagnosis of different diseases to improve the quality of life in general, and better integration into digital healthcare.



Blockchain for Healthcare Systems

Author : Sheikh Mohammad Idrees

Publisher : CRC Press

Page : 238 pages

File Size : 14,19 MB

Release : 2021-09-21

Category : Medical

ISBN : 100045438X

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Book Description

Blockchain for Healthcare Systems: Challenges, Privacy, and Securing of Data provides a detailed insight on how to reap the benefits of blockchain technology in healthcare, as the healthcare sector faces several challenges associated with privacy and security issues. It also provides in-depth knowledge regarding blockchain in healthcare and the underlying components. This book explores securing healthcare data using blockchain technology. It discusses challenges and solutions for blockchain technology in the healthcare sector and presents the digital transformation of the healthcare sector using different technologies. It covers the handling of healthcare data/medical records and managing the medical supply chain all using blockchain technology. The contents of this book are highly beneficial to educators, researchers, and others working in a similar domain.



Blockchain, Big Data and Machine Learning

Author : Neeraj Kumar

Publisher : CRC Press

Page : 346 pages

File Size : 21,36 MB

Release : 2020-09-25

Category : Computers

ISBN : 1000163490

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Book Description

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.



Machine Learning Approaches for Convergence of IoT and Blockchain

Author : Krishna Kant Singh

Publisher : John Wiley & Sons

Page : 258 pages

File Size : 13,4 MB

Release : 2021-07-16

Category : Computers

ISBN : 1119761875

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Book Description

MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication. Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning. Highlights of the book include: Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT Security of the Internet of Things using blockchain and AI Developing smart cities and transportation systems using machine learning and IoT Audience The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.



Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty

Publisher : John Wiley & Sons

Page : 528 pages

File Size : 41,79 MB

Release : 2021-07-14

Category : Computers

ISBN : 1119785855

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Book Description

Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.



Smart Healthcare Systems

Author : Adwitiya Sinha

Publisher : CRC Press

Page : 329 pages

File Size : 31,60 MB

Release : 2019-07-24

Category : Computers

ISBN : 0429670281

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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.



Recommender System with Machine Learning and Artificial Intelligence

Author : Sachi Nandan Mohanty

Publisher : John Wiley & Sons

Page : 448 pages

File Size : 36,41 MB

Release : 2020-07-08

Category : Computers

ISBN : 1119711576

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Book Description

This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. It comprehensively covers the topic of recommender systems, which provide personalized recommendations of items or services to the new users based on their past behavior. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations in agricultural or healthcare domains and contexts, the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. This book illustrates how this technology can support the user in decision-making, planning and purchasing processes in agricultural & healthcare sectors.



Multidisciplinary Functions of Blockchain Technology in AI and IoT Applications

Author : Niaz Chowdhury

Publisher : Engineering Science Reference

Page : pages

File Size : 34,18 MB

Release : 2020-10

Category :

ISBN : 9781799872306

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Book Description

"This edited book deliberates upon prospects of blockchain technology for facilitating the analysis and acquisition of big data using AI and IoT devices in various application domains"--



Integrating AI in IoT Analytics on the Cloud for Healthcare Applications

Author : Jeya Mala, D.

Publisher : IGI Global

Page : 312 pages

File Size : 48,40 MB

Release : 2022-01-07

Category : Computers

ISBN : 1799891348

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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.