Predictive Models for Decision Support in the COVID 19 Crisis 1st Edition by Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier Neto, Simon James Fong ISBN 3030619125 978-3030619121

Predictive Models for Decision Support in the COVID-19 Crisis 1st Edition by Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois , José Xavier-Neto , Simon James Fong – Ebook PDF Instant Download/Delivery: 3030619125, 978-3030619121

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Product details:

ISBN 10: 3030619125  

ISBN 13: 978-3030619121

Author: Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong

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.

Table of contents: 

1. Prediction for Decision Support During the COVID-19 Pandemic

2. Epidemiology Compartmental Models—SIR, SEIR, and SEIR with Intervention

3. Forecasting COVID-19 Time Series Based on an Autoregressive Model

4. Nonlinear Prediction for the COVID-19 Data Based on Quadratic Kalman Filtering

5. Artificial Intelligence Prediction for the COVID-19 Data Based on LSTM Neural Networks and H2O AutoML

6. Predicting the Geographic Spread of the COVID-19 Pandemic: A Case Study from Brazil

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Tags: Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier Neto, Simon James Fong, Predictive Models, Decision Support, COVID 19 Crisis