Computerized Systems for Diagnosis and Treatment of COVID-19

ISBN 10: 3031307879 / ISBN 13: 9783031307874

Edité par Springer, 2023

A propos de cet article

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Détails bibliographiques

• Titre: Computerized Systems for Diagnosis and Treatment of COVID-19
• Éditeur: Springer
• Date de parution: 2023
• Langue: anglais
• ISBN à 10 chiffres: 3031307879
• ISBN à 13 chiffres: 9783031307874
• Reliure: hardcover
• État de l'article: Very Good

A propos de ce titre

Synopsis

This book describes the application of signal and image processing technologies, artificial intelligence, and machine learning techniques to support Covid-19 diagnosis and treatment. The book focuses on two main applications: critical diagnosis requiring high precision and speed, and treatment of symptoms, including those affecting the cardiovascular and neurological systems.

The areas discussed in this book range from signal processing, time series analysis, and image segmentation to detection and classification. Technical approaches include deep learning, transfer learning, transformers, AutoML, and other machine learning techniques that can be considered not only for Covid-19 issues but also for different medical applications, with slight adjustments to the problem under study.

The Covid-19 pandemic has impacted the entire world and changed how societies and individuals interact. Due to the high infection and mortality rates, and the multiple consequences of the virusinfection in the human body, the challenges were vast and enormous. These necessitated the integration of different disciplines to address the problems. As a global response, researchers across academia and industry made several developments to provide computational solutions to support epidemiologic, managerial, and health/medical decisions. To that end, this book provides state-of-the-art information on the most advanced solutions.

À propos de l?auteur

Prof. Joao Alexandre Lobo Marques is the Head of Department / Research Coordinator / Associate Professor at the University of Saint Joseph - USJ, Macau SAR, China (2017-). Co-founder Institute of Data Engineering and Sciences (IDEAS)/USJ - 2021. Founder of the Laboratory of Applied Neurosciences/USJ - 2019. Adjunct Professor - Post Graduate Program of Telecommunications Engineering - IFCE - Brazil. Visiting Associate Professor at the Chinese Academy of Sciences (CAS) - Shenzhen Institutes of Advanced Technologies (SIAT) (2018-). Post Doctorate and Honorary Research Fellow from the University of Leicester-UK. Member of the Board of Advisors - Master in Global Marketing Management - Boston University Metropolitan College (BU-MET) - USA. Solid international career with academic positions and relevant research developed in Asia (China), Europe (England, Germany and Portugal), Africa (Angola) and America (United States and Brazil). Strong leadership and team development skills in severalinternational research projects. Research Areas: Artificial Intelligence, Medical Image Processing, Machine Learning, Applied Neurosciences, Deep Learning, Neuroeconomics, Biofeedback, Mathematical Transforms, Business Analytics, Nonlinear Analysis.