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Global Digital Transformation and the Covid-19 Pandemic
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Global Digital Transformation and the Covid-19 Pandemic

Book Details

Format Hardback or Cased Book
ISBN-10 1774915502
ISBN-13 9781774915509
Publisher Apple Academic Press Inc.
Imprint Apple Academic Press Inc.
Country of Manufacture GB
Country of Publication GB
Publication Date Nov 22nd, 2024
Print length 286 Pages
Weight 453 grams
Ksh 23,400.00
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Looks at post-Covid adoption of artificial intelligence, machine learning, and the IoT technologies effective in the medical field. Discusses basics of computer intelligence, related techniques and procedures, and latest IT methods used in healthcare, addressing problem of effective data analysis and storage in healthcare institutions.

COVID-19 has pushed companies, schools, and healthcare institutions over the technology tipping point—and transformed the business of healthcare forever. This timely book, Global Digital Transformation Due to the COVID-19 Pandemic, explores this transformation by looking at the adoption of artificial intelligence, machine learning, and the Internet of Things (IoT) technologies that have proven effective in the medical context. These technologies are now being used to improve treatment efficiency, avoid the risk of false diagnosis, make therapeutic decisions, and predict the outcome of many clinical scenarios, especially the COVID-19 pandemic.

The book begins with the fundamentals of computer intelligence, related techniques, and procedures. This book describes the cutting-edge methods of new information technology used in healthcare, addressing the problem of effective data analysis and storage in healthcare institutions.

The volume provides an overview of communication technology for combating the COVID-19 pandemic and delves into mobile application technology, medical diagnosis technology, transmission dynamics prediction models, social media and technology instruction design in teaching amid COVID-19, post-pandemic crowd safety provisioning applications, to name a few.

The interdisciplinary and transdisciplinary research advances discussed here will be valuable for academics, engineers, industry professionals, researchers, scientists, and students working in the fields of data and information science.


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