This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2414) JMIR Theme Issue: COVID-19 Special Issue (2452) Human Factors and Usability Case Studies (787) Machine Learning (1465) Clinical Information and Decision Making (1407) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517)

Published on in Vol 6, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35114, first published .
Exploring Socioeconomic Status as a Global Determinant of COVID-19 Prevalence, Using Exploratory Data Analytic and Supervised Machine Learning Techniques: Algorithm Development and Validation Study

Exploring Socioeconomic Status as a Global Determinant of COVID-19 Prevalence, Using Exploratory Data Analytic and Supervised Machine Learning Techniques: Algorithm Development and Validation Study

Exploring Socioeconomic Status as a Global Determinant of COVID-19 Prevalence, Using Exploratory Data Analytic and Supervised Machine Learning Techniques: Algorithm Development and Validation Study

Authors of this article:

Luke Winston1 Author Orcid Image ;   Michael McCann1 Author Orcid Image ;   George Onofrei2 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Luke Winston   1 , MA ;   Michael McCann   1 , PhD ;   George Onofrei   2 , PhD

1 Department of Computing, Atlantic Technological University, Letterkenny, Ireland

2 Department of Business, Atlantic Technological University, Letterkenny, Ireland

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