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  1. Home
  2. Academic Research Output
  3. Book
  4. Predictive Models for Decision Support in the COVID-19 Crisis
 
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Predictive Models for Decision Support in the COVID-19 Crisis

Date Issued
2021
Author(s)
Lobo Marques, Joao Alexandre 
Faculty of Business and Law 
Gois, Francisco Nauber Bernardo
Xavier-Neto, Jose
Fong, Simon James
Abstract
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.
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Waiting for Repository Version.pdf

Size

37.66 KB

Format

Adobe PDF

Checksum

(MD5):70439f9ac5a8bde2f366653765cefe3c


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