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Computing Paradigms for Smart Healthcare (Hardcover)
Loot Price: R4,595
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Computing Paradigms for Smart Healthcare (Hardcover)
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Smart healthcare has gradually gained its popularity because of the
development of information technologies and computing paradigms
such as internet of things (loT), big data, Cloud computing and
artificial intelligence. These technologies transform the
conventional medical system in to smarter one by making healthcare
more convenient, efficient, accurate, and more customized. Smart
healthcare will lead to a revolutionized healthcare system that
enables the participation of all people for the early prediction
and prevention of diseases so that preemptive and pro-active
treatment can be delivered. The aim of this edited book is to
publish the latest research advancements in the convergence of
automation technology, artificial intelligence, biomedical
engineering and health informatics. This will help the readers to
grasp the extensive point of view and the essence of the recent
advances in this field. This book solicits contributions which
include theory, case studies and computing paradigms pertaining to
the healthcare applications. The prospective audience would be
researchers, professionals, practitioners, and students from
academia and industry who work in this field. We hope the chapters
presented will inspire future research both from theoretical and
practical viewpoints to spur further advances in the field. The
entire book is the contribution of interdisciplinary expertise
available in the esteemed Institution PSG College of Technology, an
ISO 9001:2015 certified Government aided Institution, belonging to
Department of Information Technology, Computer Science and
Engineering, Electronics and Communication Engineering, Biomedical
Engineering and Biotechnology. A brief introduction about each
chapter is as follows. Chapter 1 focuses on health informatics
which provides an overview of the various types of data originating
from the medical information, Chapter 2 objective is to provide a
asmart connected environment' which includes storing, processing
and exchange information seamlessly using technologies. Chapter 3
deals with an intelligent healthcare system for automatic diagnosis
of diseases based on IOT enabled cloud computing framework and deep
learning Chapter 4 discuss about basic concepts of digital twin
technology and implementation of digital twin in various health
care domains. Chapter 5 proposes a graph based framework for
classification, feature selection method which uses the existing
notion, histograms for extracting isotonic features from a data
set. Chapter 6 explains the significance of convolution neural
network in medical image analysis. Chapter 7 summarizes recent
advances in AI tools applied in cancer diagnosis and research for
disease prediction and biomarker discovery. Chapter 8 explores DNA
microarray data followed by the implementation of machine learning
algorithms to obtain the highly predictive genes for
classification. Chapter 9 uses various data structures such as hash
tables and prefix-based search trees to efficiently query the EHR
data present in the Blockchain. Chapter 10 focuses on agreeing upon
a common symmetric cryptographic key generated from the ECG signal
collected at different locations of a patient using linear
prediction and error control coding techniques. We are grateful to
the authors and reviewers for their excellent contributions for
making this book possible.
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