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Predictive Models for Decision Support in the COVID-19 Crisis by Joao Alexandre Lobo Marques

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9783030619121
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9783030619121
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Description

COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations.

Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.



About the Author
Professor Joao Alexandre Lobo Marques gained his master's degree in 2007 and his PhD in 2009, both from the Federal University of Ceara, UFC, Brasil. He works as an associate professor at the University of Saint Joseph, Macau, and as a visiting associate professor at the Chinese Academy of Sciences. He is the CEO and co-founder of the XS Innovation Group in Brazil, which is focused on bioengineering innovation for education. He has published over 60 journal and conference papers, and has co-authored three books. His research interests include computational and artificial intelligence, data sciences, and neuroeconomics.

Professor Francisco Nauber Bernardo Gois is an adjunct professor at the Federal University of Ceara. He holds a master's degree and a PhD from the University of Fortaleza, gained in 2010 and 2017 respectively. He has experience in computer science, with emphasis on machine learning and software testing, deep learning, continuous integration, testing and extreme programming.

Dr Jose Xavier Neto holds a medical degree from Federal University of Ceara and a PhD from the University of Sao Paulo, which he gained in 1989 and 1993 respectively. He has worked in medical research for decades, including his current role as the Chief Health Scientist of Ceara and a Visiting Professor at the Federal University of Ceara. He has been involved in creating an experimental model for developmental neuropathy induced by the Zika virus, as well as leading a multidisciplinary team which described the first fossilised heart.

Professor Simon James Fong gained his master's degree and PhD from La Trobe University in 1994 and 1998 respectively. He has worked in several academic positions, including his current role as Associate Professor at the University of Macau. He has been on the committee for several conferences, including acting as chair, and has worked as a book series editor. His research interests include data mining, artificial intelligence, machine learning, and biomedical applications.



Reviews
"This book is ... of great interest for mathematical modelers--it nicely summarizes many important tools, with concrete examples, that could be adapted for other situations. ... I strongly recommend this book to advanced undergraduate engineers and mathematicians as well as specialists dealing with dynamical system modeling." (Arturo Ortiz-Tapia, Computing Reviews, July 26, 2022)



Book Information
ISBN 9783030619121
Author Joao Alexandre Lobo Marques
Format Paperback
Page Count 98
Imprint Springer Nature Switzerland AG
Publisher Springer Nature Switzerland AG

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