Healthcare And Big Data

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Big Data Analytics in Healthcare

Author : Anand J. Kulkarni,Patrick Siarry,Pramod Kumar Singh,Ajith Abraham,Mengjie Zhang,Albert Zomaya,Fazle Baki
Publisher : Springer Nature
Page : 187 pages
File Size : 42,8 Mb
Release : 2019-10-01
Category : Technology & Engineering
ISBN : 9783030316723

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Big Data Analytics in Healthcare by Anand J. Kulkarni,Patrick Siarry,Pramod Kumar Singh,Ajith Abraham,Mengjie Zhang,Albert Zomaya,Fazle Baki Pdf

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.

Transforming Healthcare with Big Data and AI

Author : Mingbo Gong,Anna Farzindar,Alex Liu
Publisher : IAP
Page : 185 pages
File Size : 50,7 Mb
Release : 2020-04-01
Category : Computers
ISBN : 9781641138994

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Transforming Healthcare with Big Data and AI by Mingbo Gong,Anna Farzindar,Alex Liu Pdf

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.

Big Data Analytics for Intelligent Healthcare Management

Author : Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera
Publisher : Academic Press
Page : 312 pages
File Size : 55,5 Mb
Release : 2019-04-15
Category : Science
ISBN : 9780128181478

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Big Data Analytics for Intelligent Healthcare Management by Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera Pdf

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

Healthcare and Big Data

Author : Mary F.E. Ebeling
Publisher : Springer
Page : 170 pages
File Size : 52,7 Mb
Release : 2016-09-27
Category : Social Science
ISBN : 9781137502216

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Healthcare and Big Data by Mary F.E. Ebeling Pdf

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.

Artificial Intelligence and Big Data Analytics for Smart Healthcare

Author : Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui
Publisher : Academic Press
Page : 292 pages
File Size : 45,9 Mb
Release : 2021-10-22
Category : Medical
ISBN : 9780128220627

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Artificial Intelligence and Big Data Analytics for Smart Healthcare by Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui Pdf

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

Big Data, Big Challenges: A Healthcare Perspective

Author : Mowafa Househ,Andre W. Kushniruk,Elizabeth M. Borycki
Publisher : Springer
Page : 144 pages
File Size : 43,9 Mb
Release : 2019-02-26
Category : Medical
ISBN : 9783030061098

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Big Data, Big Challenges: A Healthcare Perspective by Mowafa Househ,Andre W. Kushniruk,Elizabeth M. Borycki Pdf

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.

Applications of Big Data in Healthcare

Author : Ashish Khanna,Deepak Gupta,Nilanjan Dey
Publisher : Academic Press
Page : 311 pages
File Size : 41,6 Mb
Release : 2021-03-10
Category : Science
ISBN : 9780128204511

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Applications of Big Data in Healthcare by Ashish Khanna,Deepak Gupta,Nilanjan Dey Pdf

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

Demystifying Big Data and Machine Learning for Healthcare

Author : Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
Publisher : CRC Press
Page : 233 pages
File Size : 44,7 Mb
Release : 2017-02-15
Category : Medical
ISBN : 9781315389301

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Demystifying Big Data and Machine Learning for Healthcare by Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz Pdf

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.

Big Data and Health Analytics

Author : Katherine Marconi,Harold Lehmann
Publisher : CRC Press
Page : 382 pages
File Size : 53,8 Mb
Release : 2014-12-20
Category : Business & Economics
ISBN : 9781482229257

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Big Data and Health Analytics by Katherine Marconi,Harold Lehmann Pdf

Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery.Written for healt

Big Data Analytics and Intelligence

Author : Poonam Tanwar,Vishal Jain,Chuan-Ming Liu,Vishal Goyal
Publisher : Emerald Group Publishing
Page : 392 pages
File Size : 51,8 Mb
Release : 2020-09-30
Category : Business & Economics
ISBN : 9781839090998

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Big Data Analytics and Intelligence by Poonam Tanwar,Vishal Jain,Chuan-Ming Liu,Vishal Goyal Pdf

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.

Healthcare and Big Data Management

Author : Bairong Shen
Publisher : Springer
Page : 164 pages
File Size : 51,8 Mb
Release : 2017-10-20
Category : Science
ISBN : 9789811060410

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Healthcare and Big Data Management by Bairong Shen Pdf

The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare; physiological and gut microbiota – data collection and analysis; big data standardization and ontology; and personal data privacy and systems level modeling in the healthcare context. The book offers a valuable resource for biomedical informaticians, clinicians, health practitioners and researchers alike.

Big Data and Artificial Intelligence for Healthcare Applications

Author : Ankur Saxena,Nicolas Brault,Shazia Rashid
Publisher : CRC Press
Page : 286 pages
File Size : 46,7 Mb
Release : 2021-06-15
Category : Computers
ISBN : 9781000387315

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Big Data and Artificial Intelligence for Healthcare Applications by Ankur Saxena,Nicolas Brault,Shazia Rashid Pdf

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

Author : Mayuri Mehta,Kalpdrum Passi,Indranath Chatterjee,Rajan Patel
Publisher : CRC Press
Page : 362 pages
File Size : 46,6 Mb
Release : 2021-12-09
Category : Computers
ISBN : 9781000477764

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Knowledge Modelling and Big Data Analytics in Healthcare by Mayuri Mehta,Kalpdrum Passi,Indranath Chatterjee,Rajan Patel Pdf

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.

Philosophical Foundations of Medical Law

Author : Andelka M. Phillips,Thana C. de Campos,Jonathan Herring
Publisher : Oxford University Press, USA
Page : 353 pages
File Size : 42,7 Mb
Release : 2019-11-28
Category : Law
ISBN : 9780198796558

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Philosophical Foundations of Medical Law by Andelka M. Phillips,Thana C. de Campos,Jonathan Herring Pdf

With advances in personalised medicine, the field of medical law is being challenged and transformed. The nature of the doctor-patient relationship is shifting as patients simultaneously become consumers. The regulation of emerging technologies is being thrown into question, and we face new challenges in the context of global pandemics. This volume identifies significant questions and issues underlying the philosophy of medical law. It brings together leading philosophers, legal theorists, and medical specialists to discuss these questions in two parts. The first part deals with key foundational theories, and the second addresses a variety of topical issues, including euthanasia, abortion, and medical privacy. The wide range of perspectives and topics on offer provide a vital introduction to the philosophical underpinnings of medical law.

Machine Learning and AI for Healthcare

Author : Arjun Panesar
Publisher : Apress
Page : 390 pages
File Size : 47,6 Mb
Release : 2019-02-04
Category : Computers
ISBN : 9781484237991

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Machine Learning and AI for Healthcare by Arjun Panesar Pdf

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.