Big data and the Internet of Things (IoT) play a vital role in
prediction systems used in biological and medical applications,
particularly for resolving issues related to disease biology at
different scales. Modelling and integrating medical big data with
the IoT helps in building effective prediction systems for
automatic recommendations of diagnosis and treatment. The ability
to mine, process, analyse, characterize, classify and cluster a
variety and wide volume of medical data is a challenging task.
There is a great demand for the design and development of methods
dealing with capturing and automatically analysing medical data
from imaging systems and IoT sensors. Addressing analytical and
legal issues, and research on integration of big data analytics
with respect to clinical practice and clinical utility,
architectures and clustering techniques for IoT data processing,
effective frameworks for removal of misclassified instances,
practicality of big data analytics, methodological and technical
issues, potential of Hadoop in managing healthcare data is the need
of the hour. This book integrates different aspects used in the
field of healthcare such as big data, IoT, soft computing, machine
learning, augmented reality, organs on chip, personalized drugs,
implantable electronics, integration of bio-interfaces, and
wearable sensors, devices, practical body area network (BAN) and
architectures of web systems. Key Features: Addresses various
applications of Medical Big Data and Internet of Medical Things in
real time environment Highlights recent innovations, designs,
developments and topics of interest in machine learning techniques
for classification of medical data Provides background and
solutions to existing challenges in Medical Big Data and Internet
of Medical Things Provides optimization techniques and programming
models to parallelize the computationally intensive tasks in data
mining of medical data Discusses interactions, advantages,
limitations, challenges and future perspectives of IoT based remote
healthcare monitoring systems. Includes data privacy and security
analysis of cryptography methods for the Web of Medical Things
(WoMT) Presents case studies on the next generation medical chair,
electronic nose and pill cam are also presented.
General
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