Big Data, Big Challenges: A Healthcare Perspective, Househ
Автор: Corea Название: Big Data Analytics: A Management Perspective ISBN: 3319389912 ISBN-13(EAN): 9783319389912 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively.
Автор: Edited By I. Glenn C Название: Big data, health law, and bioethics ISBN: 1107193656 ISBN-13(EAN): 9781107193659 Издательство: Cambridge Academ Рейтинг: Цена: 24077.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores the legal and ethical implications - both challenges and opportunities - of using big data in health care and research.
Автор: Wang, Li & Perrizo Название: Big Data Analytics In Bioinformatics And Healthcare ISBN: 1466666110 ISBN-13(EAN): 9781466666115 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 37145.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Описание: Features statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting–edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data–driven healthcare analytics in an effort to provide more personalized and efficient healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance care quality and operational efficiency. Organized into two main sections, Part One features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part Two focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: Contributions from well–known international experts who shed light on new approaches in this growing area Discussions on contemporary methods and techniques to address the handling of rich and large–scale healthcare data as well as the overall optimization of healthcare system operations Numerous real–world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry Plentiful applications that showcase the various analytical methods and tools that can be applied to successful predictive modeling The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate–level courses typically offered within operations research, industrial engineering, business, and public health departments. Hui Yang, PhD, is Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University. His research interests include sensor–based modeling and analysis of complex systems for process monitoring/control; system diagnostics/prognostics; quality improvement; and performance optimization with special focus on nonlinear stochastic dynamics and the resulting chaotic, recurrence, self–organizing behaviors. Eva K. Lee, PhD, is Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, Director of the Center for Operations Research in Medicine and HealthCare, and Distinguished Scholar in Health System, Health Systems Institute at both Emory University School of Medicine and Georgia Institute of Technology. Her research interests include health risk prediction; early disease prediction and diagnosis; optimal treatment strategies and drug delivery; healthcare outcome analysis and treatment prediction; public health and medical preparedness; large–scale healthcare/medical decision analysis and quality improvement; clinical translational science; and business intelligence and organization transformation.
Автор: Dey, Nilanjan Название: Big Data Analytics for Intelligent Healthcare Management ISBN: 012818146X ISBN-13(EAN): 9780128181461 Издательство: Elsevier Science Рейтинг: Цена: 19875.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
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
Описание: Addressing global environmental challenges from a peace ecology perspective, the present book offers peer-reviewed texts that build on the expanding field of peace ecology and applies this concept to global environmental challenges in the Anthropocene. Hans G?nter Brauch (Germany) offers a typology of time and turning points in the 20th century; Juliet Bennett (Australia) discusses the global ecological crisis resulting from a “tyranny of small decisions”; Katharina Bitzker (Canada) debates “the emotional dimensions of ecological peacebuilding” through love of nature; Henri Myrttinen (UK) analyses “preliminary findings on gender, peacebuilding and climate change in Honduras” while ?rsula Oswald Spring (Mex?co) offers a critical review of the policy and scientific nexus debate on “the water, energy, food and biodiversity nexus”, reflecting on security in Mexico. In closing, Brauch discusses whether strategies of sustainability transition may enhance the prospects for achieving sustainable peace in the Anthropocene.
This book describes how the creation of new digital services--through vertical and horizontal integration of data coming from sensors on top of existing legacy systems--that has already had a major impact on industry is now extending to healthcare. The book describes the fourth industrial revolution (i.e. Health 4.0), which is based on virtualization and service aggregation. It shows how sensors, embedded systems, and cyber-physical systems are fundamentally changing the way industrial processes work, their business models, and how we consume, while also affecting the health and care domains. Chapters describe the technology behind the shift of point of care to point of need and away from hospitals and institutions; how care will be delivered virtually outside hospitals; that services will be tailored to individuals rather than being designed as statistical averages; that data analytics will be used to help patients to manage their chronic conditions with help of smart devices; and that pharmaceuticals will be interactive to help prevent adverse reactions. The topics presented will have an impact on a variety of healthcare stakeholders in a continuously global and hyper-connected world.
- Presents explanations of emerging topics as they relate to e-health, such as Industry 4.0, Precision Medicine, Mobile Health, 5G, Big Data, and Cyber-physical systems;
- Provides overviews of technologies in addition to possible application scenarios and market conditions;
- Features comprehensive demographic and statistic coverage of Health 4.0 presented in a graphical manner.
Описание: Internet of Things Driven Connected Healthcare.-Internet of Things in HealthcareEnergy Efficient Network Design for IoT Healthcare Applications.-Exploring Formal Strategy Framework for the Security in IoT in e-health using Computational Intelligence.-Vitality of Robotics in Healthcare Industry: An Internet of Things (IoT) Perspective.-Internet of Things Meets Mobile Health Systems in Smart Spaces: An Overview.-Information and Communication Emerging Technology: Making Sense of Healthcare Innovation.-Health Informatics as a Service (HIaaS) for Developing Countries.- Analysis of Power Aware Protocols and Standards for Critical E-Health Applications.-Social Networking and Analytics.-A decision support system in brain tumor detection and localization in nominated areas in MR images.-Detecting Unusual Human Activities Using GPU-enabled Neural Network and Kinect Sensors.
Автор: Bairong Shen Название: Healthcare and Big Data Management ISBN: 9811060401 ISBN-13(EAN): 9789811060403 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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;
Автор: Mary F.E. Ebeling Название: Healthcare and Big Data ISBN: 1137502207 ISBN-13(EAN): 9781137502209 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This highly original book is an ethnographic noir of how Big Data profits from patient private health information. 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.
Автор: Edited By I. Glenn C Название: Big data, health law, and bioethics ISBN: 1108449670 ISBN-13(EAN): 9781108449670 Издательство: Cambridge Academ Рейтинг: Цена: 11563.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores the legal and ethical implications - both challenges and opportunities - of using big data in health care and research.
Автор: Li Xiaoli Et Al Название: Biological Data Mining And Its Applications In Healthcare ISBN: 9814551007 ISBN-13(EAN): 9789814551007 Издательство: World Scientific Publishing Цена: 22176.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. Practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. This book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.
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