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Smart Health Technologies for the COVID-19 Pandemic: Internet of medical things perspectives

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Editors: Chinmay Chakraborty 1 ; Joel J.P.C. Rodrigues 2
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Publication Year: 2022

Smart Health Technologies for the COVID-19 Pandemic: Internet of medical things perspectives looks at the role technology has played to monitor, map and fight the global COVID-19 pandemic. Chapters outline risk assessment methodologies and social distancing and infection control technologies in the face of this disease outbreak.

The applications of Big Data and artificial intelligence in the fight against the spread of COVID-19 are explored in this edited book, as well as advances in early diagnostic testing and remote monitoring systems, and blockchain-based solutions for secure data handling. The implementation of machine learning for reviewing and analysing biomedical data and assisting with drug design is also discussed.

Emphasising the vital role that intelligent advanced healthcare informatics has played during this crucial time, this book is a valuable resource for researchers in the fields of biomedical engineering, bioengineering, electronics engineering, health informatics, wireless body area networks (WBAN), data analytics, telemedicine, and those in related fields.

Inspec keywords: diseases; neural nets; Internet of Things; medical image processing; computerised tomography; microorganisms; epidemics; edge detection; learning (artificial intelligence); molecular biophysics

Other keywords: microorganisms; computerised tomography; patient diagnosis; edge detection; neural nets; learning (artificial intelligence); Internet of medical things; image segmentation; COVID-19 pandemics; image recognition; molecular biophysics; diseases; smart health technology

Subjects: Computer vision and image processing techniques; Biomedical measurement and imaging; Molecular biophysics; Textbooks; Neural nets; Mobile, ubiquitous and pervasive computing; Medical and biomedical uses of fields, radiations, and radioactivity; health physics; Optical, image and video signal processing; Biomedical engineering; Biology and medical computing

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