Classification of community-acquired outbreaks for the global transmission of COVID-19: Machine learning and statistical model analysis | Zendy

Wei Wang | Zendy; TingYu Lin | Zendy; Sherry YuehHsia Chiu | Zendy; ChiungNien Chen | Zendy; Pongdech Sarakarn | Zendy; Mohd Yusof Ibrahim | Zendy; Sam LiSheng Chen | Zendy; ChienJen Chen | Zendy; YenPo Yeh | Zendy

Open Access

Classification of community-acquired outbreaks for the global transmission of COVID-19: Machine learning and statistical model analysis

Author(s) -

Wei Wang,

TingYu Lin,

Sherry YuehHsia Chiu,

ChiungNien Chen,

Pongdech Sarakarn,

Mohd Yusof Ibrahim,

Sam LiSheng Chen,

ChienJen Chen,

YenPo Yeh

Publication year - 2021

Publication title -

journal of the formosan medical association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.708

H-Index - 54

eISSN - 1876-0821

pISSN - 0929-6646

DOI - 10.1016/j.jfma.2021.05.010

Subject(s) - medicine , covid-19 , outbreak , transmission (telecommunications) , virology , pandemic , artificial intelligence , machine learning , infectious disease (medical specialty) , pathology , telecommunications , disease , computer science

As Coronavirus disease 2019 (COVID-19) pandemic led to the unprecedent large-scale repeated surges of epidemics worldwide since the end of 2019, data-driven analysis to look into the duration and case load of each episode of outbreak worldwide has been motivated.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research