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Unleashing the Potentials of Blockchain Technology for Healthcare Industries (Paperback): Amar Das, Yulei Wu, Pradeep N.,... Unleashing the Potentials of Blockchain Technology for Healthcare Industries (Paperback)
Amar Das, Yulei Wu, Pradeep N., Mangesh M. Ghonge, Om Pal
R3,435 Discovery Miles 34 350 Ships in 12 - 17 working days

Unleashing the Potentials of Blockchain Technology for Healthcare Industries discusses blockchain and its adaptation in healthcare industries to provide a secured framework to safeguard healthcare data, both patient and hospital data. The book integrates key pillars of blockchain such as foundations, architecture, smart contracts, adoption, standards, service (BaaS), security, consensus algorithms, drug discovery process, among others, for fortifying the current practices in the healthcare industries. In addition, it offers solutions to the pressing issues currently being faced by the healthcare processes due to the COVD-19 pandemic. This will be a valuable resource for medical informaticians, researchers, healthcare professionals and members of the biomedical field who are interested in learning more about the potentials of blockchain in healthcare.

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics (Paperback): Pradeep N., Sandeep Kautish,... Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics (Paperback)
Pradeep N., Sandeep Kautish, Sheng-Lung Peng
R3,588 Discovery Miles 35 880 Ships in 12 - 17 working days

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians.

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