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Open Access
Peer-reviewed
Research Article
Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods
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Shiying You,
Roles Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing
Affiliations Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, United States of America, Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, United States of America
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Melanie H. Chitwood,
Roles Data curation, Writing – review & editing
Affiliations Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, United States of America, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
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Kenneth S. Gunasekera,
Roles Data curation, Investigation, Writing – review & editing
Affiliations Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, United States of America, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
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Valeriu Crudu,
Roles Data curation, Writing – review & editing
Affiliation Phthisiopneumology Institute, Chisinau, Republic of Moldova
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Alexandru Codreanu,
Roles Writing – review & editing
Affiliation Phthisiopneumology Institute, Chisinau, Republic of Moldova
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Nelly Ciobanu,
Roles Writing – review & editing
Affiliation Phthisiopneumology Institute, Chisinau, Republic of Moldova
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Jennifer Furin,
Roles Supervision, Writing – review & editing
Affiliations Department of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America, Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
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Ted Cohen,
Roles Conceptualization, Funding acquisition, Supervision, Writing – review & editing
Affiliations Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, United States of America, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
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Joshua L. Warren,
Roles Supervision, Writing – review & editing
Affiliations Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, United States of America, Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
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Reza Yaesoubi
Roles Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing
* E-mail: reza.yaesoubi@yale.edu
Affiliations Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, United States of America, Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, United States of America
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Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods
- Shiying You,
- Melanie H. Chitwood,
- Kenneth S. Gunasekera,
- Valeriu Crudu,
- Alexandru Codreanu,
- Nelly Ciobanu,
- Jennifer Furin,
- Ted Cohen,
- Joshua L. Warren,
- Reza Yaesoubi
- Published: June 30, 2022
- https://doi.org/10.1371/journal.pdig.0000059