Applications of Big Data in Healthcare

Applications of Big Data in Healthcare
Author: Ashish Khanna,Deepak Gupta,Nilanjan Dey
Publsiher: Academic Press
Total Pages: 310
Release: 2021-03-10
ISBN 10: 0128204516
ISBN 13: 9780128204511
Language: EN, FR, DE, ES & NL

Applications of Big Data in Healthcare Book Review:

Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data. This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians. The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in the healthcare sector is to come up with ways to provide personalized healthcare to patients by taking into account the enormous amounts of already existing data. Provides case studies that illustrate the business processes underlying the use of big data and deep learning health analytics to improve health care delivery Supplies readers with a foundation for further specialized study in clinical analysis and data management Includes links to websites, videos, articles and other online content to expand and support the primary learning objectives for each major section of the book

Big Data Analytics in Healthcare

Big Data Analytics in Healthcare
Author: Anand J. Kulkarni,Patrick Siarry,Pramod Kumar Singh,Ajith Abraham,Mengjie Zhang,Albert Zomaya,Fazle Baki
Publsiher: Springer Nature
Total Pages: 187
Release: 2019-10-01
ISBN 10: 3030316726
ISBN 13: 9783030316723
Language: EN, FR, DE, ES & NL

Big Data Analytics in Healthcare Book Review:

This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.

Big Data and Artificial Intelligence for Healthcare Applications

Big Data and Artificial Intelligence for Healthcare Applications
Author: Ankur Saxena,Nicolas Brault,Shazia Rashid
Publsiher: CRC Press
Total Pages: 286
Release: 2021-06-15
ISBN 10: 1000387313
ISBN 13: 9781000387315
Language: EN, FR, DE, ES & NL

Big Data and Artificial Intelligence for Healthcare Applications Book Review:

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

Knowledge Modelling and Big Data Analytics in Healthcare

Knowledge Modelling and Big Data Analytics in Healthcare
Author: Mayuri Mehta,Kalpdrum Passi,Indranath Chatterjee,Rajan Patel
Publsiher: CRC Press
Total Pages: 362
Release: 2021-12-09
ISBN 10: 1000477762
ISBN 13: 9781000477764
Language: EN, FR, DE, ES & NL

Knowledge Modelling and Big Data Analytics in Healthcare Book Review:

Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications focuses on automated analytical techniques for healthcare applications used to extract knowledge from a vast amount of data. It brings together a variety of different aspects of the healthcare system and aids in the decision-making processes for healthcare professionals. The editors connect four contemporary areas of research rarely brought together in one book: artificial intelligence, big data analytics, knowledge modelling, and healthcare. They present state-of-the-art research from the healthcare sector, including research on medical imaging, healthcare analysis, and the applications of artificial intelligence in drug discovery. This book is intended for data scientists, academicians, and industry professionals in the healthcare sector.

Artificial Intelligence and Big Data Analytics for Smart Healthcare

Artificial Intelligence and Big Data Analytics for Smart Healthcare
Author: Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui
Publsiher: Academic Press
Total Pages: 290
Release: 2021-10-22
ISBN 10: 0128220627
ISBN 13: 9780128220627
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Big Data Analytics for Smart Healthcare Book Review:

Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers

New Horizons for a Data Driven Economy

New Horizons for a Data Driven Economy
Author: José María Cavanillas,Edward Curry,Wolfgang Wahlster
Publsiher: Springer
Total Pages: 303
Release: 2016-04-04
ISBN 10: 3319215698
ISBN 13: 9783319215693
Language: EN, FR, DE, ES & NL

New Horizons for a Data Driven Economy Book Review:

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.

Big Data Analytics for Intelligent Healthcare Management

Big Data Analytics for Intelligent Healthcare Management
Author: Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera
Publsiher: Academic Press
Total Pages: 312
Release: 2019-04-15
ISBN 10: 0128181478
ISBN 13: 9780128181478
Language: EN, FR, DE, ES & NL

Big Data Analytics for Intelligent Healthcare Management Book Review:

Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data. Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc. Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more

Medical Big Data and Internet of Medical Things

Medical Big Data and Internet of Medical Things
Author: Aboul Ella Hassanien,Nilanjan Dey,Surekha Borra
Publsiher: CRC Press
Total Pages: 340
Release: 2018-10-25
ISBN 10: 1351030361
ISBN 13: 9781351030366
Language: EN, FR, DE, ES & NL

Medical Big Data and Internet of Medical Things Book Review:

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.

Transforming Healthcare with Big Data and AI

Transforming Healthcare with Big Data and AI
Author: Mingbo Gong,Anna Farzindar,Alex Liu
Publsiher: IAP
Total Pages: 185
Release: 2020-04-01
ISBN 10: 1641138998
ISBN 13: 9781641138994
Language: EN, FR, DE, ES & NL

Transforming Healthcare with Big Data and AI Book Review:

Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.

Building Big Data Applications

Building Big Data Applications
Author: Krish Krishnan
Publsiher: Academic Press
Total Pages: 242
Release: 2019-11-15
ISBN 10: 0128158042
ISBN 13: 9780128158043
Language: EN, FR, DE, ES & NL

Building Big Data Applications Book Review:

Building Big Data Applications helps data managers and their organizations make the most of unstructured data with an existing data warehouse. It provides readers with what they need to know to make sense of how Big Data fits into the world of Data Warehousing. Readers will learn about infrastructure options and integration and come away with a solid understanding on how to leverage various architectures for integration. The book includes a wide range of use cases that will help data managers visualize reference architectures in the context of specific industries (healthcare, big oil, transportation, software, etc.). Explores various ways to leverage Big Data by effectively integrating it into the data warehouse Includes real-world case studies which clearly demonstrate Big Data technologies Provides insights on how to optimize current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

Data Science for Healthcare

Data Science for Healthcare
Author: Sergio Consoli,Diego Reforgiato Recupero,Milan Petković
Publsiher: Springer
Total Pages: 367
Release: 2019-02-23
ISBN 10: 3030052494
ISBN 13: 9783030052492
Language: EN, FR, DE, ES & NL

Data Science for Healthcare Book Review:

This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.

Leveraging Biomedical and Healthcare Data

Leveraging Biomedical and Healthcare Data
Author: Firas Kobeissy,Kevin Wang,Fadi A. Zaraket,Ali Alawieh
Publsiher: Academic Press
Total Pages: 225
Release: 2018-11-23
ISBN 10: 012809561X
ISBN 13: 9780128095614
Language: EN, FR, DE, ES & NL

Leveraging Biomedical and Healthcare Data Book Review:

Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic systems biology, introduces novel areas of its application, and describes step-wise protocols for transforming heterogeneous data into useful knowledge that can influence healthcare and biomedical research. Given the astronomical increase in the number of published reports, papers, and datasets over the last few decades, the ability to curate this data has become a new field of biomedical and healthcare research. This book discusses big data text-based mining to better understand the molecular architecture of diseases and to guide health care decision. It will be a valuable resource for bioinformaticians and members of several areas of the biomedical field who are interested in understanding more about how to process and apply great amounts of data to improve their research. Includes at each section resource pages containing a list of available curated raw and processed data that can be used by researchers in the field Provides demonstrative and relevant examples that serve as a general tutorial Presents a list of algorithm names and computational tools available for basic and clinical researchers

Big Data Big Challenges A Healthcare Perspective

Big Data  Big Challenges  A Healthcare Perspective
Author: Mowafa Househ,Andre W. Kushniruk,Elizabeth M. Borycki
Publsiher: Springer
Total Pages: 144
Release: 2019-02-26
ISBN 10: 3030061094
ISBN 13: 9783030061098
Language: EN, FR, DE, ES & NL

Big Data Big Challenges A Healthcare Perspective Book Review:

This is the first book to offer a comprehensive yet concise overview of the challenges and opportunities presented by the use of big data in healthcare. The respective chapters address a range of aspects: from health management to patient safety; from the human factor perspective to ethical and economic considerations, and many more. By providing a historical background on the use of big data, and critically analyzing current approaches together with issues and challenges related to their applications, the book not only sheds light on the problems entailed by big data, but also paves the way for possible solutions and future research directions. Accordingly, it offers an insightful reference guide for health information technology professionals, healthcare managers, healthcare practitioners, and patients alike, aiding them in their decision-making processes; and for students and researchers whose work involves data science-related research issues in healthcare.

Big Data Analytics and Intelligence

Big Data Analytics and Intelligence
Author: Poonam Tanwar,Vishal Jain,Chuan-Ming Liu,Vishal Goyal
Publsiher: Emerald Group Publishing
Total Pages: 392
Release: 2020-09-30
ISBN 10: 1839090995
ISBN 13: 9781839090998
Language: EN, FR, DE, ES & NL

Big Data Analytics and Intelligence Book Review:

Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.

Demystifying Big Data and Machine Learning for Healthcare

Demystifying Big Data and Machine Learning for Healthcare
Author: Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
Publsiher: CRC Press
Total Pages: 210
Release: 2017-02-15
ISBN 10: 1315389304
ISBN 13: 9781315389301
Language: EN, FR, DE, ES & NL

Demystifying Big Data and Machine Learning for Healthcare Book Review:

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Healthcare Data Analytics and Management

Healthcare Data Analytics and Management
Author: Nilanjan Dey,Amira S. Ashour,Simon James Fong,Chintan Bhatt
Publsiher: Academic Press
Total Pages: 340
Release: 2018-11-15
ISBN 10: 0128156368
ISBN 13: 9780128156360
Language: EN, FR, DE, ES & NL

Healthcare Data Analytics and Management Book Review:

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges

Big Data Analytics in Bioinformatics and Healthcare

Big Data Analytics in Bioinformatics and Healthcare
Author: Wang, Baoying
Publsiher: IGI Global
Total Pages: 528
Release: 2014-10-31
ISBN 10: 1466666129
ISBN 13: 9781466666122
Language: EN, FR, DE, ES & NL

Big Data Analytics in Bioinformatics and Healthcare Book Review:

As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.

Data Analytics in Medicine

Data Analytics in Medicine
Author: Information Resources Management Association
Publsiher: Medical Information Science Reference
Total Pages: 2250
Release: 2019-11-18
ISBN 10: 9781799812043
ISBN 13: 1799812049
Language: EN, FR, DE, ES & NL

Data Analytics in Medicine Book Review:

""This book examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations"--

Machine Learning for Healthcare Applications

Machine Learning for Healthcare Applications
Author: Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar
Publsiher: John Wiley & Sons
Total Pages: 416
Release: 2021-04-13
ISBN 10: 1119791812
ISBN 13: 9781119791812
Language: EN, FR, DE, ES & NL

Machine Learning for Healthcare Applications Book Review:

When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Internet of Things and Big Data Technologies for Next Generation Healthcare

Internet of Things and Big Data Technologies for Next Generation Healthcare
Author: Chintan Bhatt,Nilanjan Dey,Amira S. Ashour
Publsiher: Springer
Total Pages: 388
Release: 2017-01-01
ISBN 10: 3319497367
ISBN 13: 9783319497365
Language: EN, FR, DE, ES & NL

Internet of Things and Big Data Technologies for Next Generation Healthcare Book Review:

This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients’ records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics. Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data.