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

Applications of AI (373) Public (e)Health, Digital Epidemiology and Public Health Informatics (1142) mHealth for Data Collection and Research (1286) Big Data (320) GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (148) Obesity and Nutrition as Public Health Problem (452) Development and Evaluation of Research Methods, Instruments and Tools (845) Artificial Intelligence (2437)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64362, first published .
Geospatial Modeling of Deep Neural Visual Features for Predicting Obesity Prevalence in Missouri: Quantitative Study

Geospatial Modeling of Deep Neural Visual Features for Predicting Obesity Prevalence in Missouri: Quantitative Study

Geospatial Modeling of Deep Neural Visual Features for Predicting Obesity Prevalence in Missouri: Quantitative Study

Authors of this article:

Butros M Dahu1 Author Orcid Image ;   Solaiman Khan1 Author Orcid Image ;   Imad Eddine Toubal1 Author Orcid Image ;   Mariam Alshehri1 Author Orcid Image ;   Carlos I Martinez-Villar1 Author Orcid Image ;   Olabode B Ogundele1 Author Orcid Image ;   Lincoln R Sheets1 Author Orcid Image ;   Grant J Scott1 Author Orcid Image
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