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

Formative Evaluation of Digital Health Interventions (2422) JMIR Theme Issue: COVID-19 Special Issue (2453) Human Factors and Usability Case Studies (792) Machine Learning (1471) Clinical Information and Decision Making (1411) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1518)

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

Journals

  1. Reyes Z, Stovall M, Punyamurthula S, Longo M, Maraganore D, Solch-Ottaiano R. The impact of gut microbiome and diet on post-acute sequelae of SARS-CoV-2 infection. Journal of the Neurological Sciences 2024;467:123295 View