Predictive Models for Decision Support in the COVID-19 Crisis (Record no. 78741)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 04191nam a22006495i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-61913-8 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220801220614.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 201130s2021 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783030619138 |
| -- | 978-3-030-61913-8 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 658.5 |
| 100 1# - AUTHOR NAME | |
| Author | Marques, Joao Alexandre Lobo. |
| 245 10 - TITLE STATEMENT | |
| Title | Predictive Models for Decision Support in the COVID-19 Crisis |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2021. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | VII, 98 p. 48 illus., 41 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | SpringerBriefs in Applied Sciences and Technology, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Chapter 1. Prediction for Decision Support during the COVID-19 Pandemic -- Chapter 2. Epidemiology Compartmental Models - SIR, SEIR and SEIR with Intervention -- Chapter 3. Forecasting COVID-19 Time Series based on an Auto Regressive Model -- Chapter 4. Nonlinear Prediction for the COVID-19 Data based on Quadratic Kalman Filtering -- Chapter 5. Artificial Intelligence Prediction for the COVID-19 Data based on LSTM Neural Networks and H2O AutoML -- Chapter 6. Predicting the Geographic Spread of the COVID-19 Pandemic: a case study from Brazil. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Gois, Francisco Nauber Bernardo. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Xavier-Neto, José. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Fong, Simon James. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-030-61913-8 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 100 1# - AUTHOR NAME | |
| -- | (orcid)0000-0002-6472-8784 |
| -- | https://orcid.org/0000-0002-6472-8784 |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2021. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Industrial Management. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Epidemiology. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Operations research. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Medicine, Preventive. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health promotion. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Industrial Management. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Epidemiology. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Operations Research and Decision Theory. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health Promotion and Disease Prevention. |
| 700 1# - AUTHOR 2 | |
| -- | (orcid)0000-0001-9361-8659 |
| -- | https://orcid.org/0000-0001-9361-8659 |
| 700 1# - AUTHOR 2 | |
| -- | (orcid)0000-0003-4648-789X |
| -- | https://orcid.org/0000-0003-4648-789X |
| 700 1# - AUTHOR 2 | |
| -- | (orcid)0000-0002-1848-7246 |
| -- | https://orcid.org/0000-0002-1848-7246 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2191-5318 |
| 912 ## - | |
| -- | ZDB-2-ENG |
| 912 ## - | |
| -- | ZDB-2-SXE |
No items available.