Advancing Big Data Analytics For Healthcare Service Delivery
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Advancing Big Data Analytics for Healthcare Service Delivery
In recent years, there has been steady increase in the interest shown in both big data analytics and the use of information technology (IT) solutions to improve healthcare services. Despite the growing interest, there are limited materials, to addressing the needs and challenges posed by the activities and processes including the use of big data. From IT solutions’ perspectives, this book aims to advance the deployment and use of big data analytics to increase patients’ big data usefulness and improve healthcare service delivery. The book provides significant insights and useful guide on how to access and manage big data, in improving healthcare service delivery. The book contributes a fresh perspective, which primarily comes from the complementary use of analytics approach with actor-network theory (ANT), and other techniques, in advancing healthcare service delivery. Accessing and managing healthcare big data have always been a challenging exercise. Due to the sensitivity of the health sector, the focus on patients’ big data is from either technical or social perspective. Thus, the book employs sociotechnical theories, ANT and structuration theory (ST) as lenses to examine and explain the factors that enable and constrain the use of patients’ big data for health services. By doing so, the book brings a different dimension and advance health service delivery. Providing a timely and important contribution to this critical area, this book is a valuable, international resource for academics, postgraduate students and researchers in the areas of IT, big data analytics, data management and health informatics.
Artificial Intelligence and Big Data Analytics for Smart Healthcare
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 Analytics for Intelligent Healthcare Management
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