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Using machine learning to understand microgeographic determinants of the Zika vector, Aedes aegypti
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Jagger Alexander ,
Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing
* E-mail: jagger.alexander@vanderbilt.edu
Affiliation University of Miami Department of Public Health, Miami, FL, United States of America
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André Barretto Bruno Wilke,
Roles Conceptualization, Data curation, Methodology, Supervision, Writing – review & editing
Affiliation Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, United States of America
⨯ - Alejandro Mantero,
- Chalmers Vasquez,
- William Petrie,
- Naresh Kumar,
- John C. Beier
https://orcid.org/0000-0002-7128-5512
Using machine learning to understand microgeographic determinants of the Zika vector, Aedes aegypti
- Jagger Alexander,
- André Barretto Bruno Wilke,
- Alejandro Mantero,
- Chalmers Vasquez,
- William Petrie,
- Naresh Kumar,
- John C. Beier
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- Published: December 30, 2022
- https://doi.org/10.1371/journal.pone.0265472