Predictive Models for Decision Support in the COVID-19 Crisis
Author | : Joao Alexandre Lobo Marques |
Publisher | : Springer Nature |
Total Pages | : 103 |
Release | : 2020-11-30 |
ISBN-10 | : 9783030619138 |
ISBN-13 | : 3030619133 |
Rating | : 4/5 (38 Downloads) |
Download or read book Predictive Models for Decision Support in the COVID-19 Crisis written by Joao Alexandre Lobo Marques and published by Springer Nature. This book was released on 2020-11-30 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.