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Tremendous growth in healthcare treatment techniques and methods
has led to the emergence of numerous storage and communication
problems and need for security among vendors and patients. This
book brings together latest applications and state-of-the-art
developments in healthcare sector using Blockchain technology. It
explains how blockchain can enhance security, privacy,
interoperability, and data accessibility including AI with
blockchains, blockchains for medical imaging to supply chain
management, and centralized management/clearing houses alongside
DLT. Features: Includes theoretical concepts, empirical studies and
detailed overview of various aspects related to development of
healthcare applications from a reliable, trusted, and secure data
transmission perspective. Provide insights on business applications
of Blockchain, particularly in the healthcare sector. Explores how
Blockchain can solve the transparency issues in the clinical
research. Discusses AI with Blockchains, ranging from medical
imaging to supply chain management. Reviews benchmark testing of AI
with Blockchains and its impacts upon medical uses. This book aims
at researchers and graduate students in healthcare information
systems, computer and electrical engineering.
1) The book will discuss most relevant real-world applications and
case studies of IoT. 2) The book will provide deeper knowledge
regarding emerging research trends and future research directions
in IoT. 3) The book will provide theoretical, algorithmic,
simulation, and implementation-based research developments in IoT.
4) The book will follow theoretical approach to describe
applications of IoT for the beginners as well as practical approach
to depict simulation and implementation of real-world applications
for intermediate and advanced readers.
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
test-beds, and empirical characterization of security and privacy
interoperability issues in healthcare applications Explores and
illustrates the current and future impacts of pandemics and
mitigatse risk in healthcare with advanced analytics
This book reviews the state of the art of big data analysis and
smart city. It includes issues which pertain to signal processing,
probability models, machine learning, data mining, database, data
engineering, pattern recognition, visualisation, predictive
analytics, data warehousing, data compression, computer
programming, smart city, etc. Data is becoming an increasingly
decisive resource in modern societies, economies, and governmental
organizations. Data science inspires novel techniques and theories
drawn from mathematics, statistics, information theory, computer
science, and social science. Papers in this book were the outcome
of research conducted in this field of study. The latter makes use
of applications and techniques related to data analysis in general
and big data and smart city in particular. The book appeals to
advanced undergraduate and graduate students, postdoctoral
researchers, lecturers and industrial researchers, as well as
anyone interested in big data analysis and smart city.
This book reviews the state of the art of big data analysis,
artificial intelligence, and smart environments. Data is becoming
an increasingly decisive resource in modern societies, economies,
and governmental organizations. Data science, artificial
intelligence, and smart environments inspire novel techniques and
theories drawn from mathematics, statistics, information theory,
computer science, and social science. This book reviews the state
of the art of big data analysis, artificial intelligence, and smart
environments. It includes issues that pertain to signal processing,
probability models, machine learning, data mining, database, data
engineering, pattern recognition, visualization, predictive
analytics, data warehousing, data compression, computer
programming, smart city, etc. The papers in this book were the
outcome of research conducted in this field of study. The latter
makes use of applications and techniques related to data analysis
in general and big data and smart city in particular. The book
appeals to advanced undergraduate and graduate students,
post-doctoral researchers, lecturers, and industrial researchers,
as well as anyone interested in big data analysis and artificial
intelligence.
This book reviews the state of the art in big data analysis and
networks technologies. It addresses a range of issues that pertain
to: signal processing, probability models, machine learning, data
mining, databases, data engineering, pattern recognition,
visualization, predictive analytics, data warehousing, data
compression, computer programming, smart cities, networks
technologies, etc. Data is becoming an increasingly decisive
resource in modern societies, economies, and governmental
organizations. In turn, data science inspires novel techniques and
theories drawn from mathematics, statistics, information theory,
computer science, and the social sciences. All papers presented
here are the product of extensive field research involving
applications and techniques related to data analysis in general,
and to big data and networks technologies in particular. Given its
scope, the book will appeal to advanced undergraduate and graduate
students, postdoctoral researchers, lecturers and industrial
researchers, as well general readers interested in big data
analysis and networks technologies.
This book reviews the state of the art of big data analysis and
smart city. It includes issues which pertain to signal processing,
probability models, machine learning, data mining, database, data
engineering, pattern recognition, visualisation, predictive
analytics, data warehousing, data compression, computer
programming, smart city, etc. Data is becoming an increasingly
decisive resource in modern societies, economies, and governmental
organizations. Data science inspires novel techniques and theories
drawn from mathematics, statistics, information theory, computer
science, and social science. Papers in this book were the outcome
of research conducted in this field of study. The latter makes use
of applications and techniques related to data analysis in general
and big data and smart city in particular. The book appeals to
advanced undergraduate and graduate students, postdoctoral
researchers, lecturers and industrial researchers, as well as
anyone interested in big data analysis and smart city.
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