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

Formative Evaluation of Digital Health Interventions (2832) JMIR Theme Issue: COVID-19 Special Issue (2496) Human Factors and Usability Case Studies (896) Machine Learning (1745) Clinical Information and Decision Making (1662) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1531)

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

Conference Proceedings

  1. Lakshmi B, N J S, Dhake S, N M J, Barri H, Dash M. 2023 International Conference on Network, Multimedia and Information Technology (NMITCON). AI Based Novel Feature Engineering using ANN Applied on Women SES Classification View