Big Data Analytics for Intelligent Healthcare Management PDF Download

Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 0128181478
Category : Science
Languages : en
Pages : 312

View

Book Description
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

Author: Peter Langkafel
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110445743
Category : Computers
Languages : en
Pages : 290

View

Book Description
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.

Author: Peter Langkafel
Publisher:
ISBN: 9783110445756
Category :
Languages : en
Pages : 280

View

Book Description

Author: Bairong Shen
Publisher: Springer
ISBN: 981106041X
Category : Science
Languages : en
Pages : 164

View

Book Description
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.

Author: Farrokh Alemi
Publisher:
ISBN: 9781640550636
Category : Data mining
Languages : en
Pages : 553

View

Book Description
Big Data in Healthcare: Statistical Analysis of the Electronic Health Record provides the statistical tools that healthcare leaders need to organize and interpret their data. Designed for accessibility to those with a limited mathematics background, the book demonstrates how to leverage EHR data for applications as diverse as healthcare marketing, pay for performance, cost accounting, and strategic management. Topics include:* Using real-world data to compare hospitals' performance. * Measuring the prognosis of patients through massive data* Distinguishing between fake claims and true improvements* Comparing the effectiveness of different interventions using causal analysis* Benchmarking different clinicians on the same set of patients* Remove confounding in observational dataThis book can be used in introductory courses on hypothesis testing, intermediate courses on regression, and advanced courses on causal analysis. It can also be used to learn SQL language. Its extensive online instructor resources include course syllabi, PowerPoint and video lectures, Excel exercises, individual and team assignments, answers to assignments, and student-organized tutorials. Big Data in Healthcare applies the building blocks of statistical thinking to the basic challenges that healthcare leaders face every day. Prepare for those challenges with the clear understanding of your data that statistical analysis can bring--and make the best possible decisions for maximum performance in the competitive field of healthcare.

Author: Pantea Keikhosrokiani
Publisher: Academic Press
ISBN: 0323985165
Category : Medical
Languages : en
Pages : 356

View

Book Description
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

Author: Anand J. Kulkarni
Publisher: Springer Nature
ISBN: 3030316726
Category : Technology & Engineering
Languages : en
Pages : 187

View

Book Description
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.

Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799812057
Category : Medical
Languages : en
Pages : 2071

View

Book Description
Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that 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. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.

Author: David L. Olson
Publisher: Springer Nature
ISBN: 3031281136
Category : Medical
Languages : en
Pages : 195

View

Book Description
This book presents data mining methods in the field of healthcare management in a practical way. Healthcare quality and disease prevention are essential in today’s world. Healthcare management faces a number of challenges, e.g. reducing patient growth through disease prevention, stopping or slowing disease progression, and reducing healthcare costs while improving quality of care. The book provides an overview of current healthcare management problems and highlights how analytics and knowledge management have been used to better cope with them. It then demonstrates how to use descriptive and predictive analytics tools to help address these challenges. In closing, it presents applications of software solutions in the context of healthcare management. Given its scope, the book will appeal to a broad readership, from researchers and students in the operations research and management field to practitioners such as data analysts and decision-makers who work in the healthcare sector.

Author: Edmon Begoli
Publisher: Springer
ISBN: 9783319671857
Category : Computers
Languages : en
Pages : 0

View

Book Description
This book constitutes the thoroughly refereed conference proceedings of the Third International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2017, in Munich, Germany, in September 2017, held in conjunction with the 43rd International Conference on Very Large Data Bases, VLDB 2017. The 9 revised full papers presented together with 2 keynote abstracts were carefully reviewed and selected from 16 initial submissions. The papers are organized in topical sections on data privacy and trustability for electronic health records; biomedical data management and Integration; online mining of Health related data; and clinical data analytics.