Please use this identifier to cite or link to this item: https://doi.org/10.53383/100354
DC FieldValue
dc.titleForecasting COVID-19 Infection Rates with Artificial Intelligence Model
dc.contributor.authorYang, Jesse Jingye
dc.date.accessioned2023-07-26T04:54:09Z
dc.date.available2023-07-26T04:54:09Z
dc.date.issued2022
dc.identifier.citationYang, Jesse Jingye (2022). Forecasting COVID-19 Infection Rates with Artificial Intelligence Model. International Real Estate Review 1 (1) : 525-542. ScholarBank@NUS Repository. https://doi.org/10.53383/100354
dc.identifier.issn2154-8919
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/243503
dc.description.abstract<jats:p>This study applies an artificial intelligence (AI) based model to predict the infection rate of coronavirus disease 2019 (COVID-19). The results provide information for managing public and global health risks regarding pandemic controls, disease diagnosis, vaccine development, and socio-economic responses. The machine learning algorithm is developed with the Python program to analyze pathways and evolutions of infection. The finding is robust in predicting the virus spread situation. The machine learning algorithms predict the rate of spread of COVID -19 with an accuracy of nearly 90%. The algorithms simulate the virus spread distance and coverage. We find that self-isolation for suspected cases plays an important role in containing the pandemic. The COVID-19 virus could spread asymptotically (silent spreader); therefore, earlier doctor consultation and testing of the virus could reduce its spread in local communities.</jats:p>
dc.publisherGlobal Social Science Institute
dc.sourceElements
dc.typeArticle
dc.date.updated2023-07-26T03:07:43Z
dc.contributor.departmentINSTITUTE OF REAL ESTATE & URBAN STUDIES
dc.description.doi10.53383/100354
dc.description.sourcetitleInternational Real Estate Review
dc.description.volume1
dc.description.issue1
dc.description.page525-542
dc.published.statePublished online
Appears in Collections:Elements
Staff Publications

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
v25-no4-5_COVID-19-Infection-Rates-with-Artificial-Intelligence.pdfPublished version853.4 kBAdobe PDF

OPEN

NoneView/Download

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.