Predictive Models for Decision Support in the COVID-19 Crisis

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Predictive Models for Decision Support in the COVID-19 Crisis

Management and management techniques Management decision making Operational research Public health and preventive medicine Epidemiology and Medical statistics Engineering: general Data mining Expert systems / knowledge-based systems

Authors: João Alexandre Lobo Marques, Francisco Nauber Bernardo Góis, Jose Xavier-Neto, Simon James Fong

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Collection: SpringerBriefs in Applied Sciences and Technology

Language: English

Published by: Springer

Published on: 30th November 2020

Format: LCP-protected ePub

Size: 22 Mb

ISBN: 9783030619138


COVID-19 and the Role of Artificial Intelligence

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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