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

BACKGROUND: Limited access to drug-susceptibility tests (DSTs) and delays in receiving DST results are challenges for timely and appropriate treatment of multi-drug resistant tuberculosis (TB) in many low-resource settings. We investigated whether data collected as part of routine, national TB surve...

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Detalles Bibliográficos
Autores principales: You, Shiying, Chitwood, Melanie H., Gunasekera, Kenneth S., Crudu, Valeriu, Codreanu, Alexandru, Ciobanu, Nelly, Furin, Jennifer, Cohen, Ted, Warren, Joshua L., Yaesoubi, Reza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518704/
https://www.ncbi.nlm.nih.gov/pubmed/36177394
http://dx.doi.org/10.1371/journal.pdig.0000059

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518704/
https://www.ncbi.nlm.nih.gov/pubmed/36177394
http://dx.doi.org/10.1371/journal.pdig.0000059

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