Machine Learning Model for Predicting Number of COVID-19 Cases in Countries with Low Number of Tests | Zendy

Samy Hashim | Zendy; Sally Farooq | Zendy; Eleni Syriopoulos | Zendy; Kai de la Lande Cremer | Zendy; Alexander Vogt | Zendy; Nol de Jong | Zendy; Victor L. Aguado | Zendy; Mihai Popescu | Zendy; Ashraf K. Mohamed | Zendy; Muhamed Amin | Zendy

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Machine Learning Model for Predicting Number of COVID-19 Cases in Countries with Low Number of Tests

Author(s) -

Samy Hashim,

Sally Farooq,

Eleni Syriopoulos,

Kai de la Lande Cremer,

Alexander Vogt,

Nol de Jong,

Victor L. Aguado,

Mihai Popescu,

Ashraf K. Mohamed,

Muhamed Amin

Publication year - 2022

Publication title -

the open bioinformatics journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.259

H-Index - 8

ISSN - 1875-0362

DOI - 10.2174/18750362-v15-e2208290

Subject(s) - covid-19 , population , statistics , pandemic , regression , correlation , linear regression , artificial neural network , gini coefficient , regression analysis , computer science , econometrics , demography , machine learning , artificial intelligence , medicine , mathematics , inequality , environmental health , economic inequality , mathematical analysis , geometry , disease , pathology , sociology , infectious disease (medical specialty)

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