Miltiadis Lytras

Abdulrahman Housawi

Basim Alsaywid

Digital Transformation in Healthcare in Post-Covid19 Times discusses recent advances in patient care and offers critical comparative insights into their application across multiple domains in healthcare. By showcasing key problems, best practices and emerging challenges, the book offers a state-of-art review of opportunities and prospects in the process of delivering smart sustainable healthcare services. Topics discussed include healthcare challenges in the post-COVID-19 era, enabling technologies for digital transformation, value driven approaches to the delivery of patient centric top-quality health services, and analytics and enhanced decision making. In addition, the book updates knowledge on best practices for training towards digital transformation and sustainable health. This is a valuable resource for healthcare professionals, medical doctors, researchers, graduate students and members of the biomedical field who are interested in learning more about the use of emerging technologies in healthcare. Holistically discusses the new landscape of digital transformation and sustainability in health Presents a case study driven approach based on real-world scenarios to help readers apply the knowledge gained into practice Promotes sound research on the impact of emerging technologies in health and life specialties and their relevant role during the COVID-19 pandemic

Digital Transformation in Healthcare in Post-COVID-19 Times

Anna Visvizi

Kwok Tai Chui

Akila Sarirete

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

Miltiadis Lytras

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