Big Data Analytics for Intelligent Healthcare Management

• Author : Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera
• Publisher : Academic Press
• Release : 15 April 2019

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

• Author : Aboul-Ella Hassanien,Nilanjan Dey,Sally Elghamrawy
• Publisher : Springer Nature
• Release : 13 November 2020

This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses

• Author : Nilanjan Dey,Amira S. Ashour,Simon James Fong,Chintan Bhatt
• Publisher : Academic Press
• Release : 15 November 2018

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

• Author : Sun, Zhaohao
• Publisher : IGI Global
• Release : 22 February 2019

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective

• Author : Ashish Khanna,Deepak Gupta,Nilanjan Dey
• Publisher : Academic Press
• Release : 10 March 2021

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

• Author : Pethuru Raj,Anupama Raman,Dhivya Nagaraj,Siddhartha Duggirala
• Publisher : Springer
• Release : 16 October 2015

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics

• Author : Sergio Consoli,Diego Reforgiato Recupero,Milan Petković
• Publisher : Springer
• Release : 22 March 2019

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

• Author : Bouchemal, Nardjes
• Publisher : IGI Global
• Release : 07 December 2018

With the growing use of new technologies and artificial intelligence (AI) applications, intelligent systems can be used to manage large amounts of existing data in healthcare domains. Having more intelligent methods for accessing data allows medical professionals to more efficiently identify the best medical practices and more concrete solutions for diagnosing and treating a multitude of rare diseases. Intelligent Systems for Healthcare Management and Delivery provides relevant and advanced methodological, technological, and scientific approaches related to the application of sophisticated

• Author : Christo El Morr,Hossam Ali-Hassan
• Publisher : Springer
• Release : 21 January 2019

This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records,

• Author : Hasmat Malik,Nuzhat Fatema,Jafar A. Alzubi
• Publisher : Springer
• Release : 15 February 2021

This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health,

• Author : Peter K. Ghavami, Ph.d.
• Publisher : Createspace Independent Pub
• Release : 21 April 2014

This book offers concepts, methods and a framework to analyze healthcare data in new ways to improve patient health outcomes, improve population health and reduce costs. The framework takes the reader step-by-step through data warehouse and data management architectures, analytics algorithms and modeling techniques for applications in predictive medicine, optimization, machine learning, natural language processing, classification and data clustering. This book introduces the reader to data science for healthcare. It provides a clinical perspective to data including sources of open

• Author : Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
• Publisher : CRC Press
• Release : 15 February 2017

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

• Author : Kun Chang Lee,Sanjiban Sekhar Roy,Pijush Samui,Vijay Kumar
• Publisher : Academic Press
• Release : 23 October 2020

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction

• Author : Michael Minelli,Michele Chambers,Ambiga Dhiraj
• Publisher : John Wiley & Sons
• Release : 22 January 2013

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a

• Author : Peter Langkafel
• Publisher : Walter de Gruyter GmbH & Co KG
• Release : 27 November 2015

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