Basim Alsaywid – författare

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

Next Generation eHealth: Applied Data Science, Machine Learning and Extreme Computational Intelligence discusses the emergence, the impact, and the potential of sophisticated computational capabilities in healthcare. This book provides useful therapeutic targets to improve diagnosis, therapies, and prognosis of diseases, as well as helping with the establishment of better and more efficient next-generation medicine and medical systems. Machine learning as a field greatly contributes to next-generation medical research with the goal of improving medicine practices and medical Systems. As a contributing factor to better health outcomes, this book highlights the need for advanced training of professionals from various health areas, clinicians, educators, and social professionals who deal with patients. Content illustrates current issues and future promises as they pertain to all stakeholders, including informaticians, professionals in diagnostics, key industry experts in biotech, pharma, administrators, clinicians, patients, educators, students, health professionals, social scientists and legislators, health providers, advocacy groups, and more. With a focus on machine learning, deep learning, and neural networks, this volume communicates in an integrated, fresh, and novel way the impact of data science and computational intelligence to diverse audiences.Allows medical scientists, computer science experts, researchers, and health professionals to better educate themselves on machine Learning practices and applications and to benefit from the improvement of their knowledge skillsProvides various tested and current techniques of health literacy as a determinant of health and well-beingProvides insight into international research successfully implemented in patient care and education through the proper training of health professionalsOffers detailed guidance for diverse communities on their need to get timely, trusted, and integrated knowledge for the adoption of ML in healthcare processes and decisions. professionals involved with healthcare to leverage productive partnerships with technology developers