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: 0128204516
Category: Science
Language: EN, FR, DE, ES & NL

Applications of Big Data in Healthcare Book Excerpt:

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: 3030316726
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Big Data Analytics in Healthcare Book Excerpt:

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 Analytics for Healthcare

Big Data Analytics for Healthcare
Author: Pantea Keikhosrokiani
Publsiher: Academic Press
Total Pages: 354
Release: 2022-05-19
ISBN: 0323985165
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Big Data Analytics for Healthcare Book Excerpt:

Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. Presents theories, methods and approaches in which data analytic techniques are used for medical data Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases Discusses social, behavioral, and medical fake news analytics for medical information systems

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: 1315389304
Category: Medical
Language: EN, FR, DE, ES & NL

Demystifying Big Data and Machine Learning for Healthcare Book Excerpt:

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.

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: 1000477762
Category: Computers
Language: EN, FR, DE, ES & NL

Knowledge Modelling and Big Data Analytics in Healthcare Book Excerpt:

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.

Big Data in Medical Science and Healthcare Management

Big Data in Medical Science and Healthcare Management
Author: Peter Langkafel
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 290
Release: 2015-11-27
ISBN: 3110445743
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data in Medical Science and Healthcare Management Book Excerpt:

Big Data in medical science – what exactly is that? What are the potentials for healthcare management? Where is Big Data at the moment? Which risk factors need to be kept in mind? What is hype and what is real potential? This book provides an impression of the new possibilities of networked data analysis and "Big Data" – for and within medical science and healthcare management. Big Data is about the collection, storage, search, distribution, statistical analysis and visualization of large amounts of data. This is especially relevant in healthcare management, as the amount of digital information is growing exponentially. An amount of data corresponding to 12 million novels emerges during the time of a single hospital stay. These are dimensions that cannot be dealt with without IT technologies. What can we do with the data that are available today? What will be possible in the next few years? Do we want everything that is possible? Who protects the data from wrong usage? More importantly, who protects the data from NOT being used? Big Data is the "resource of the 21st century" and might change the world of medical science more than we understand, realize and want at the moment. The core competence of Big Data will be the complete and correct collection, evaluation and interpretation of data. This also makes it possible to estimate the frame conditions and possibilities of the automation of daily (medical) routine. Can Big Data in medical science help to better understand fundamental problems of health and illness, and draw consequences accordingly? Big Data also means the overcoming of sector borders in healthcare management. The specialty of Big Data analysis will be the new quality of the outcomes of the combination of data that were not related before. That is why the editor of the book gives a voice to 30 experts, working in a variety of fields, such as in hospitals, in health insurance or as medical practitioners. The authors show potentials, risks, concrete practical examples, future scenarios, and come up with possible answers for the field of information technology and data privacy.

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: 0128181478
Category: Science
Language: EN, FR, DE, ES & NL

Big Data Analytics for Intelligent Healthcare Management Book Excerpt:

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

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: 1466666129
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics in Bioinformatics and Healthcare Book Excerpt:

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.

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: 3030061094
Category: Medical
Language: EN, FR, DE, ES & NL

Big Data Big Challenges A Healthcare Perspective Book Excerpt:

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.

Healthcare and Big Data

Healthcare and Big Data
Author: Mary F.E. Ebeling
Publsiher: Springer
Total Pages: 170
Release: 2016-09-27
ISBN: 1137502215
Category: Social Science
Language: EN, FR, DE, ES & NL

Healthcare and Big Data Book Excerpt:

This highly original book is an ethnographic noir of how Big Data profits from patient private health information. The book follows personal health data as it is collected from inside healthcare and beyond to create patient consumer profiles that are sold to marketers. Primarily told through a first-person noir narrative, Ebeling as a sociologist-hard-boiled-detective, investigates Big Data and the trade in private health information by examining the information networks that patient data traverses. The noir narrative reveals the processes that the data broker industry uses to create data commodities—data phantoms or the marketing profiles of patients that are bought by advertisers to directly market to consumers. Healthcare and Big Data considers the implications these “data phantoms” have for patient privacy as well as the very real harm that they can cause.

Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

Demystifying Big Data  Machine Learning  and Deep Learning for Healthcare Analytics
Author: Pradeep N,Sandeep Kautish,Sheng-Lung Peng
Publsiher: Academic Press
Total Pages: 372
Release: 2021-06-25
ISBN: 0128220449
Category: Science
Language: EN, FR, DE, ES & NL

Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics Book Excerpt:

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Security and Privacy Trends in Cloud Computing and Big Data

Security and Privacy Trends in Cloud Computing and Big Data
Author: Muhammad Imran Tariq,Valentina Emilia Balas,Shahzadi Tayyaba
Publsiher: CRC Press
Total Pages: 232
Release: 2022-06-09
ISBN: 1000583708
Category: Computers
Language: EN, FR, DE, ES & NL

Security and Privacy Trends in Cloud Computing and Big Data Book Excerpt:

It is essential for an organization to know before involving themselves in cloud computing and big data, what are the key security requirements for applications and data processing. Big data and cloud computing are integrated together in practice. Cloud computing offers massive storage, high computation power, and distributed capability to support processing of big data. In such an integrated environment the security and privacy concerns involved in both technologies become combined. This book discusses these security and privacy issues in detail and provides necessary insights into cloud computing and big data integration. It will be useful in enhancing the body of knowledge concerning innovative technologies offered by the research community in the area of cloud computing and big data. Readers can get a better understanding of the basics of cloud computing, big data, and security mitigation techniques to deal with current challenges as well as future research opportunities.

Big Data Analytics and Artificial Intelligence in the Healthcare Industry

Big Data Analytics and Artificial Intelligence in the Healthcare Industry
Author: Machado, José,Peixoto, Hugo,Sousa, Regina
Publsiher: IGI Global
Total Pages: 360
Release: 2022-04-29
ISBN: 1799891739
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics and Artificial Intelligence in the Healthcare Industry Book Excerpt:

Developing new approaches and reliable enabling technologies in the healthcare industry is needed to enhance our overall quality of life and lead to a healthier, innovative, and secure society. Further study is required to ensure these current technologies, such as big data analytics and artificial intelligence, are utilized to their utmost potential and are appropriately applied to advance society. Big Data Analytics and Artificial Intelligence in the Healthcare Industry discusses technologies and emerging topics regarding reliable and innovative solutions applied to the healthcare industry and considers various applications, challenges, and issues of big data and artificial intelligence for enhancing our quality of life. Covering a range of topics such as electronic health records, machine learning, and e-health, this reference work is ideal for healthcare professionals, computer scientists, data analysts, researchers, practitioners, scholars, academicians, instructors, and students.

Data Science for Effective Healthcare Systems

Data Science for Effective Healthcare Systems
Author: Hari Singh,Ravindara Bhatt,Prateek Thakral,Dinesh Chander Verma
Publsiher: CRC Press
Total Pages: 224
Release: 2022-07-27
ISBN: 1000618838
Category: Computers
Language: EN, FR, DE, ES & NL

Data Science for Effective Healthcare Systems Book Excerpt:

Data Science for Effective Healthcare Systems has a prime focus on the importance of data science in the healthcare domain. Various applications of data science in the health care domain have been studied to find possible solutions. In this period of COVID-19 pandemic data science and allied areas plays a vital role to deal with various aspect of health care. Image processing, detection & prevention from COVID-19 virus, drug discovery, early prediction, and prevention of diseases are some thrust areas where data science has proven to be indispensable. Key Features: The book offers comprehensive coverage of the most essential topics, including: Big Data Analytics, Applications & Challenges in Healthcare Descriptive, Predictive and Prescriptive Analytics in Healthcare Artificial Intelligence, Machine Learning, Deep Learning and IoT in Healthcare Data Science in Covid-19, Diabetes, Coronary Heart Diseases, Breast Cancer, Brain Tumor The aim of this book is also to provide the future scope of these technologies in the health care domain. Last but not the least, this book will surely benefit research scholar, persons associated with healthcare, faculty, research organizations, and students to get insights into these emerging technologies in the healthcare domain.

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: 1641138998
Category: Computers
Language: EN, FR, DE, ES & NL

Transforming Healthcare with Big Data and AI Book Excerpt:

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.

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: 3319497367
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

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

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.

Increasing Importance of Patients generated Real World Data for Healthcare Policy Decisions About Medicinal Products

Increasing Importance of Patients generated Real World Data for Healthcare Policy Decisions About Medicinal Products
Author: Kenneth K. C. Lee,Wai Yee Choon,Chee Jen Chang,Jeff Guo,Paul Scuffham
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2022-05-03
ISBN: 2889760685
Category: Science
Language: EN, FR, DE, ES & NL

Increasing Importance of Patients generated Real World Data for Healthcare Policy Decisions About Medicinal Products Book Excerpt:

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics
Author: Sunil Kumar Dhal,Srinivas Prasad,Sudhir Kumar Mohapatra,Subhendu Kumar Pani
Publsiher: John Wiley & Sons
Total Pages: 352
Release: 2022-05-20
ISBN: 1119792355
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics Book Excerpt:

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

Big Data Analytics in Healthcare to Assist Medical Diagnosis

Big Data Analytics in Healthcare to Assist Medical Diagnosis
Author: Christian Marheine
Publsiher: GRIN Verlag
Total Pages: 8
Release: 2018-07-24
ISBN: 3668757259
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Big Data Analytics in Healthcare to Assist Medical Diagnosis Book Excerpt:

Academic Paper from the year 2018 in the subject Computer Sciences - Industry 4.0, grade: A: 90/100 ODER 1,0, Lund University (Informatik), course: Business Intelligence, language: English, abstract: This seminar paper discusses how big data analytics might support healthcare organizations (e.g., hospitals) in medical diagnosis. The paper proceeds as follows: First, an overview of big data analytics in healthcare is provided with a focus on medical image analytics. Second, two large-scale image analysis cases are presented to materialize the theory upon which an integrated framework is proposed that illustrates how big data analytics might assist medical diagnosis. Third, the contemporary challenges of IT adoption in healthcare are discussed, and lastly, a brief conclusion is drawn.

Big Data and Knowledge Sharing in Virtual Organizations

Big Data and Knowledge Sharing in Virtual Organizations
Author: Gyamfi, Albert,Williams, Idongesit
Publsiher: IGI Global
Total Pages: 313
Release: 2019-01-25
ISBN: 1522575200
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data and Knowledge Sharing in Virtual Organizations Book Excerpt:

Knowledge in its pure state is tacit in nature—difficult to formalize and communicate—but can be converted into codified form and shared through both social interactions and the use of IT-based applications and systems. Even though there seems to be considerable synergies between the resulting huge data and the convertible knowledge, there is still a debate on how the increasing amount of data captured by corporations could improve decision making and foster innovation through effective knowledge-sharing practices. Big Data and Knowledge Sharing in Virtual Organizations provides innovative insights into the influence of big data analytics and artificial intelligence and the tools, methods, and techniques for knowledge-sharing processes in virtual organizations. The content within this publication examines cloud computing, machine learning, and knowledge sharing. It is designed for government officials and organizations, policymakers, academicians, researchers, technology developers, and students.