Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods

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Machine learning model helps identify resistance to key antibiotics for treating tuberculosis YaleSPH PLOSDigiHealth

Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editingDepartment 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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YaleSPH PLOSDigiHealth bacterial infections globalhealth foodsystems aging agedcare helicobacter gastriccancer healthequity tuberculosis respiratory pulmonary lungs sustainability ecology microbiome antimicrobial peptides melatonin gramnegative nutrition housing stomachcancer

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